Bridging the Academia Industry Divide: Innovation and Industrialisation Perspective using Systems Thinking Research in Sub-Saharan Africa 3030704920, 9783030704926

Table of contents :
Preface
Acknowledgements
Abbreviations
Contents
List of Figures
List of Tables
About the Authors
Chapter 1: Introduction
1.1 Research Background
1.2 Initiatives to Enhance Engineering Education
1.3 NUSESA, EEEP and HEP SSA
1.4 Macroeconomic Situations and Policies
1.5 Engineering Skills Development and Training
1.6 Synopsis and Scope of the Book
1.7 Collaborating Institutions and Industry Partners
1.8 Significance and Contributions to Knowledge
1.9 Summary and Outline of the Book
References
Chapter 2: Industrialisation and Technology Dynamics: Recent Research Trends
2.1 Introduction
2.2 Industrial Revolutions
2.2.1 Origins and Transformations in Industry
2.2.2 Transformations in Other Sectors
2.3 Technology Dynamics and Complexities
2.3.1 Challenges and Opportunities
2.3.2 Effects on Industrialising Countries
2.3.3 Techniques for Productivity in Industry
2.4 Fourth Industrial Revolution and Engineering Training
2.4.1 Rapid Transformation to Integration
2.4.2 Engineering Education Transformations
2.4.3 Parallel Transformations in Industry
2.5 Impact on Engineering Education and Policies
2.5.1 Polytechnics to Universities
2.5.2 Shortages and Mismatch of Skills
2.5.3 Double Degrees and Double Majors
2.5.4 Collaborations in Southern Africa
2.6 Training Challenges and Possible Solutions
2.6.1 Complexities and Uncertainties
2.6.2 From AI to IA
2.6.3 Promotion of Creativity and Innovation
2.6.4 Online Learning Resources
2.7 Conclusion
References
Chapter 3: Systems Thinking Research: Adapting for Engineering Change Management
3.1 Introduction
3.2 Systems Thinking Tools
3.2.1 Analysis and Synthesis
3.2.2 Interconnectedness
3.2.3 Process and Systems Mapping
3.2.4 Emergence (Outcome of Systems Interactions)
3.3 Systems Thinking Operations
3.3.1 System Dynamics and Complexities
3.3.2 Feedback Loops and Control of System Performance
3.3.3 Causal Loop Flow Diagrams
3.4 Implementation of Systems Thinking
3.5 Successes and Failures in Systems Thinking
3.6 Conclusion
References
Chapter 4: Academia and Industry Collaborations: A Research and Professional Perspective
4.1 Introduction
4.1.1 Importance of Academia–Industry Partnerships
4.1.2 Building Robust and Successful Collaborations
4.2 Collaborations in Southern Africa
4.2.1 Shortages and Mismatch of Skills in the Region
4.2.2 Knowledge-Sharing Workshops
4.2.3 Sharing of Resources Under Distress
4.2.4 Focus Areas of Discussion and Key Resolutions
4.2.5 Foundations for Systems Thinking Modelling
4.3 Industrial Secondments
4.4 Continuous Professional Development
4.5 Project Resources and Equipment
4.6 International Backstopping
4.7 Academia Dialogue with Captains of Industry
4.8 Conclusion
References
Chapter 5: Problem- and Industry-Based Learning: Research, Theory and Practice
5.1 Introduction
5.2 Problem-Based Learning
5.2.1 Fundamentals of Problem-Based Learning
5.2.2 Designing Problem-Based Learning Pedagogy
5.2.3 Implementation of Problem-Based Learning
5.2.4 Challenges and Possible Solutions for PBL
5.3 Industry-Based Learning (IBL)
5.3.1 Overview of Industry-Based Learning
5.3.2 Objectives and Importance of Industry-Based Learning
5.3.3 Formulation and Evaluation of IBL Projects
5.4 Implementation of IBL in Southern Africa
5.4.1 University of Johannesburg
5.4.2 Universidade Eduardo Mondlane
5.4.3 Harare Institute of Technology
5.4.4 National University of Science and Technology
5.4.5 Chinhoyi University of Technology
5.4.6 Namibia University of Science and Technology
5.4.7 University of Zimbabwe
5.5 Industrial Secondments: UK Perspective
5.5.1 Criteria for Successful Secondments
5.5.2 Establishing Academia Industry Secondments
5.6 Industrial Design and Design Thinking
5.7 Systems Thinking Synchronisation of PBL and IBL
5.8 Conclusion
References
Chapter 6: Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results
6.1 Introduction
6.2 Modelling Systems
6.3 Simulation of Operations
6.4 Process Mapping and Optimisation
6.5 Case Studies
6.5.1 Plant Reorganisation Using Machine Distance Matrices
6.5.1.1 Research Methodology
6.5.1.2 Reorganisation and Optimisation
6.5.1.3 Achievements and Conclusion
6.5.2 Optimisation for a Multi-product Assembling Plant
6.5.2.1 Research Methodology
6.5.2.2 Results, Verification and Validation
6.5.2.3 Achievements and Conclusion
6.5.3 Process Flows and Layout for a Foundry
6.5.3.1 Research Methodology
6.5.3.2 Results and Optimisation of the Foundry
6.5.3.3 Achievements and Conclusion
6.5.4 Casting Technology for Sustainable Manufacture
6.5.4.1 Research Methodology
6.5.4.2 Results and Optimisation of the Gating System
6.5.4.3 Achievements and Conclusion
6.5.5 Comminution and Flotation Circuits in Mineral Processing
6.5.5.1 Research Methodology
6.5.5.2 Simulation and Experimentation
6.5.5.3 Results and Optimisation
6.5.5.4 Achievements and Conclusion
6.6 Conclusion
References
Chapter 7: Capacity Building and Sustainability: Research Findings and Recommendations
7.1 Introduction
7.2 Sustainability Planning and Implementation
7.3 Capacity Utilisation in Industry
7.4 Capacity Building in Engineering Education
7.5 Centres of Excellence and Doctoral Training Centres
7.5.1 Doctoral Training Centres: UK Perspective
7.5.2 Doctoral Training Centres in Sub-Saharan Africa
7.5.3 DTC Initiation and Funding
7.5.4 DTC Potential Areas of Research in Southern Africa
7.5.5 DTC Implementation and Self-Sustenance
7.6 Chairs and Adjunct Appointments
7.6.1 Professorial Chairs
7.6.2 Adjunct or Visiting Professorships
7.7 Integrated Approaches Using Systems Thinking
7.8 Continuity of Donor-Funded Projects
7.9 Conclusion
References
Chapter 8: Access to Modern Technology: Smart Partnerships for Research and Practice
8.1 Introduction
8.2 Situational Analysis
8.2.1 Age of Equipment and Origins
8.2.2 Condition and Utilisation of the Equipment
8.2.3 Maintenance Expertise and Sources of Spares
8.2.4 Combined Analysis of Factors
8.3 Build-Operate-Transfer Scheme
8.4 Smart Procurement, Use and Maintenance of Equipment
8.5 Consultancy and Research
8.6 Conclusion
References
Chapter 9: Coopetition and Virtual Collaborations: Global Competitiveness in Research and Practice
9.1 Introduction
9.2 Coopetition in Higher Education
9.2.1 Virtual Collaborations and Networks in Higher Education
9.2.2 Coopetition at Multiple Levels in Higher Education
9.3 Higher Education Partnerships in Sub-Saharan Africa
9.3.1 NUSESA and EEEP Coopetition Models
9.3.2 HEP SSA Coopetition and Virtual Model: SAE2Net
9.3.3 HEP SSA Coopetition Model Objectives
9.4 HEP SSA Coopetition Model Outcomes and Impact
9.5 Challenges and Opportunities in Virtual Collaborations
9.6 Conclusion
References
Chapter 10: Incubation and Technology Parks: Recent Trends, Research and Approaches
10.1 Introduction
10.2 Business Incubation Principles
10.2.1 Business Incubators and Accelerators
10.2.2 Classification of Business Incubators
10.2.3 Academia Business Incubation Process and Selection
10.2.4 Incubation Performance and Impacts
10.3 Innovation Hubs and Industrial Technology Parks
10.3.1 Innovation Hub and Agro-Industrial Park: University of Zimbabwe
10.3.2 Centre for Minerals Research: University of Cape Town
10.3.3 Institute for Intelligent Systems: University of Johannesburg
10.3.4 Technopreneurship Development Centre: Harare Institute of Technology
10.3.5 Food Science and Technology: Universidade Eduardo Mondlane
10.3.6 Renewable Energy: Namibia University of Science and Technology
10.4 Incubation Success Variables and Factors
10.5 Customisation of Incubators for Flexibility
10.6 Conclusion
References
Chapter 11: Commercialisation and Industrialisation: Research Prognosis for Academia Entrepreneurships
11.1 Introduction
11.1.1 The Triple Helix Model
11.1.2 Background to Commercialisation and Industrialisation
11.1.3 Entrepreneurships in Academia
11.2 Knowledge and Technology Transfer as Tools for Commercialisation
11.3 Academia Start-Ups and Spin-Offs
11.4 Intellectual Property Rights in Academia Research
11.5 Support Infrastructure
11.6 Entrepreneurship Models and Mechanisms
11.7 Academia Entrepreneurship in Southern Africa
11.8 Performance Measurement and Sustainability
11.8.1 Importance-Performance Analysis
11.8.2 Analysis of Inputs and Outputs
11.9 Drivers and Barriers to Academia Entrepreneurship
11.9.1 Stimulants for Academia Entrepreneurship
11.9.2 Obstacles to Academia Entrepreneurship
11.9.3 Packaging a Winning Start-Up to Attract Business Incubators
11.10 Conclusion
References
Chapter 12: Modelling the ‘Bridge’: Research Verification and Validation
12.1 Introduction
12.2 Equipment and Technology
12.3 Skills Development and Training
12.4 Professional Development Policies
12.5 Integrated Universal Systems Thinking Model
12.6 Model Verification and Validation
12.7 Conclusion
References
Chapter 13: Challenges and Opportunities: Discussion and Predictions from Research Findings
13.1 Introduction
13.2 Practices and Shortfalls in Academia and Industry
13.3 Capacity Utilisation and Productivity in Industry
13.4 Capacity Building and Sustainability
13.5 Build-Operate-Transfer: Smart Procurement of Equipment
13.6 Community Service and Spin-Off Activities
13.7 Constraints and Limitations
13.8 Regional Collaborations and Integration
13.9 Conclusion
References
Chapter 14: Conclusions: Consolidated Research Findings and Recommendations
14.1 Introduction
14.2 Industrial Transformations
14.3 Academia and Industry Partnerships
14.4 Capacity Building and Sustainability
14.5 Regional Integration and Internationalisation
14.6 Commercialisation of Research and Wealth Creation
14.7 Systems Modelling and Integration
14.8 Contributions to Research and Knowledge
14.9 Limitations, Challenges and Opportunities
14.10 Recommendations for Further Research
Appendix
References
Index

Citation preview

EAI/Springer Innovations in Communication and Computing

Wilson R. Nyemba Charles Mbohwa Keith F. Carter

Bridging the Academia Industry Divide Innovation and Industrialisation Perspective using Systems Thinking Research in Sub-Saharan Africa

EAI/Springer Innovations in Communication and Computing Series editor Imrich Chlamtac, European Alliance for Innovation, Ghent, Belgium

Editor’s Note The impact of information technologies is creating a new world yet not fully understood. The extent and speed of economic, life style and social changes already perceived in everyday life is hard to estimate without understanding the technological driving forces behind it. This series presents contributed volumes featuring the latest research and development in the various information engineering technologies that play a key role in this process. The range of topics, focusing primarily on communications and computing engineering include, but are not limited to, wireless networks; mobile communication; design and learning; gaming; interaction; e-health and pervasive healthcare; energy management; smart grids; internet of things; cognitive radio networks; computation; cloud computing; ubiquitous connectivity, and in mode general smart living, smart cities, Internet of Things and more. The series publishes a combination of expanded papers selected from hosted and sponsored European Alliance for Innovation (EAI) conferences that present cutting edge, global research as well as provide new perspectives on traditional related engineering fields. This content, complemented with open calls for contribution of book titles and individual chapters, together maintain Springer’s and EAI’s high standards of academic excellence. The audience for the books consists of researchers, industry professionals, advanced level students as well as practitioners in related fields of activity include information and communication specialists, security experts, economists, urban planners, doctors, and in general representatives in all those walks of life affected ad contributing to the information revolution. Indexing: This series is indexed in Scopus, Ei Compendex, and zbMATH. About EAI EAI is a grassroots member organization initiated through cooperation between businesses, public, private and government organizations to address the global challenges of Europe’s future competitiveness and link the European Research community with its counterparts around the globe. EAI reaches out to hundreds of thousands of individual subscribers on all continents and collaborates with an institutional member base including Fortune 500 companies, government organizations, and educational institutions, provide a free research and innovation platform. Through its open free membership model EAI promotes a new research and innovation culture based on collaboration, connectivity and recognition of excellence by community. More information about this series at http://www.springer.com/series/15427

Wilson R. Nyemba • Charles Mbohwa Keith F. Carter

Bridging the Academia Industry Divide Innovation and Industrialisation Perspective using Systems Thinking Research in Sub-Saharan Africa

Wilson R. Nyemba Quality Assurance and Operations Management University of Johannesburg Johannesburg, South Africa

Charles Mbohwa Pro-Vice Chancellor responsible for Strategic Partnerships and Industrialisation University of Zimbabwe Harare, Zimbabwe

Keith F. Carter School of Engineering University of Leicester Leicester, UK

ISSN 2522-8595     ISSN 2522-8609 (electronic) EAI/Springer Innovations in Communication and Computing ISBN 978-3-030-70492-6    ISBN 978-3-030-70493-3 (eBook) https://doi.org/10.1007/978-3-030-70493-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

We sincerely dedicate this book to our families and colleagues who made it possible! To all the engineers and system thinkers who have helped and continue to engineer a better world in a creative and innovative manner, disruptive as it may be, but necessary!

“You cannot carry out fundamental change without a certain amount of madness. In this case, it comes from non-conformity, the courage to turn your back on the old formulas, the courage to invent the future. It took the madmen of yesterday for us to be able to act with extreme clarity today. I want to be one of those madmen. We must dare to invent the future”. —Thomas Sankara (1985): President of Burkina Faso “Are engineers better at business than business people? It’s debatable. Business people certainly seem to have bigger houses, drive fancier cars, wear nicer clothes and have better looking mates. Engineers lack the time and management skills to spend that kind of money. They waste all their time inventing ways to make the most money in the quickest, most efficient way possible. And then when they figure it out, they optimise the process”. —Raul Perez

Preface

Bridging the Academia Industry Divide: Innovation and Industrialisation Perspective Using Systems Thinking Research in Sub-Saharan Africa is a book that culminated from years of research following a realisation of the gap and mismatch of engineering skills produced by universities and those that industry required. Based on case studies in Sub-Saharan Africa, the initiatives included collaborations and secondments with the aim of bridging the gap between academia and industry through systems thinking research, aided initially by the Swedish International Development Cooperation Agency (Sida) through the Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) (1989–2005). The initiatives were later revamped and supported by the Royal Academy of Engineering through the Enriching Engineering Education Program (EEEP) (2013–2015) and the Higher Education Partnerships for Sub-Saharan Africa (HEP SSA) (2019–2021) in partnership with tertiary institutions in Southern Africa and the University of Leicester in the UK, anchored by SADC governments, regional industry, research institutions, professional engineering and regulatory bodies, out of which the Southern Africa Engineering Education Network (SAE2Net) was established. The book provides information on how to model, simulate, adjust and implement integrated systems thinking frameworks to improve the quality of engineering education and training for capacity building and sustainability. The book also covers approaches to address research gaps and mismatch of skills while capitalising on the successes of the NUSESA, EEEP and HEP SSA initiatives. The book primarily consists of the novel research and innovation approach of modelling and building systems thinking sub-models which were eventually integrated into the Universal Systems Thinking (UST) model (“bridge”) to assist engineering academics and engineers in industry to build capacity and cope with the rapid and dynamic trends in technology in view of the widespread implementation and impact of the 4th Industrial Revolution and in preparation for the Digital Ecosystem, an era predicted to be dominated by critical and system thinkers equipped with creative and innovative skills. The book is also useful for policy-making researchers in academia, industrial and public sector researchers, and implementers in governments that vii

viii

Preface

provide required funding for the development of human resources and engineering skills to drive industry. Not only is the book a reference guide for engineering practitioners but is also a cocktail of experiences benchmarked on industrialised and semi-industrialised economies to create a blend and best practices for bridging the gap between academia and industry in industrialising economies. Johannesburg, South Africa Harare, Zimbabwe Leicester, UK

Wilson R. Nyemba Charles Mbohwa Keith F. Carter

Acknowledgements

We wish to thank the Swedish International Development Cooperation Agency (Sida) who opened the doors to pursue this research through the Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) which formed a firm foundation for the collaborations in engineering education in Sub-­Saharan Africa. Our sincere gratitude and appreciation to the Royal Academy of Engineering who revamped the Sida support and expanded it to include the vital missing link of industry players through the Enriching Engineering Education Program (EEEP) and the scaled up Higher Education Partnerships for Sub-Saharan Africa (HEP SSA). Their decade-long support helped to strengthen the ties between academia and industry in Southern Africa, apart from other support initiatives such as the Industry Academia Partnership Program, Africa Catalyst and the Africa Prize for Engineering Innovation. We are also grateful for the different contributions made by several industry partners, government ministries, professional engineering and regulatory bodies as well as research institutes in Southern Africa, inclusive of technology transfer, equipment and the UZ-Zimplats Professorial Chair in Mining Engineering. We are equally indebted to the assistance and work carried out by students and engineering academics who were attached or seconded to the different sectors of industry and for the valuable work carried out and information gathered, culminating in several scholarly publications. Our colleagues from the University of Zimbabwe HEP SSA Implementation Committee (Management) and the regional HEP SSA Steering Committee (Board) contributed immensely in shaping the direction and eventual compilation of this book and the establishment of the Southern Africa Engineering Education Network (SAE2Net). We are all indebted to our families for the sacrifice and time spent away from them to ensure that this work was completed and above all the Almighty for giving us the strength and wisdom to continue. “It always seems impossible until it’s done”. – Nelson Mandela. Wilson R. Nyemba Charles Mbohwa Keith F. Carter ix

Abbreviations

BMR Base Metal Refinery BOT Build-Operate-Transfer BUSH Biomass Utilisation by Sustainable Harvest CNC Computer Numerical Control CREEE Centre for Renewable Energy and Energy Efficiency CUT Chinhoyi University of Technology DAM Day Ahead Marketing EDF European Development Fund EEEP Enriching Engineering Education Program FAO Food and Agricultural Organisation GCRF Global Challenges Research Fund GSM Global System for Mobile Communications GTZ German Technical Cooperation Agency (GIZ) HEP SSA Higher Education Partnerships for Sub-Saharan Africa HIT Harare Institute of Technology HPGR High Pressure Grinding Rolls IBL Industry Based Learning IDT Industrial Design Thinking JICA Japan International Cooperation Agency MU Makerere University NEED Network of Energy Excellence for Development NEPAD New Partnerships for Africa’s Development NUSESA Network of Users of Scientific Equipment in Eastern and Southern Africa NUST Namibia University of Science and Technology NUST Z National University of Science and Technology, Zimbabwe ODA Overseas Development Authority OECD Organisation for Economic Cooperation and Development OEM Original Equipment Manufacturers PARTICIPA Participatory Integrated Assessment of Energy Systems to Promote Energy Access and Efficiency xi

xii

PBL PhD PMR PPP R&D RAEng SADC SAE2Net Sida SPP UDSM UEM UN UNESCO-IHE USAID UJ UZ ZIMDEF ZNDU

Abbreviations

Problem Based Learning Doctor of Philosophy Precious Metal Refinery Public Private Partnerships Research and Development Royal Academy of Engineering Southern Africa Development Community Southern Africa Engineering Education Network Swedish International Development Co-operation Agency Smart Procurement Partnerships University of Dar es Salaam Universidade Eduardo Mondlane United Nations United Nations Education, Scientific and Cultural Organisation – Institute for Water Education United States Agency for International Development University of Johannesburg University of Zimbabwe Zimbabwe Manpower Development Fund Zimbabwe National Defence University

Nomenclature Au Gold c Concentrate f Feedrate E(t) Residence time distribution for continuous flotation F(k) Distribution function for mineral types with different flotation rates H Half-width k Kinetic rate constant for sub-processes n Number of replications N Number of parts Pd Palladium Pt Platinum R Recovery of minerals at time t Maximum recovery at infinite time R∞ Rh Rhodium s Sample standard deviation S Number of stages in a process t Time in minutes ta Tailings Ts Total time in system Tq Total queueing time Time spent by N parts through W workstations Tw W Number of workstations

Abbreviations

xiii

Symbols

Systems Thinking Process Flow Systems Thinking Elements

Constraints/Challenges Process Flow Outputs/Decisions/Functions Feedback Process for Improvement Compulsory Link/Interconnection and Direction Flexible or Optional Link/Interconnection and Direction

Processing: Simulating/Controlling/Optimising

Adjustments  Acceptable Outcome Recommendations R B

-



for

Decision

Positive Reinforcing Feedback Loop +



Negative Balancing Feedback Loop Positive Link/Feedback Negative Link/Feedback

Making,

Conclusions

or

Contents

1 Introduction����������������������������������������������������������������������������������������������    1 1.1 Research Background ����������������������������������������������������������������������    1 1.2 Initiatives to Enhance Engineering Education����������������������������������    2 1.3 NUSESA, EEEP and HEP SSA��������������������������������������������������������    3 1.4 Macroeconomic Situations and Policies ������������������������������������������    5 1.5 Engineering Skills Development and Training ��������������������������������    8 1.6 Synopsis and Scope of the Book������������������������������������������������������    9 1.7 Collaborating Institutions and Industry Partners������������������������������   11 1.8 Significance and Contributions to Knowledge����������������������������������   12 1.9 Summary and Outline of the Book ��������������������������������������������������   13 References��������������������������������������������������������������������������������������������������   16 2 Industrialisation and Technology Dynamics: Recent Research Trends��������������������������������������������������������������������������   19 2.1 Introduction��������������������������������������������������������������������������������������   19 2.2 Industrial Revolutions ����������������������������������������������������������������������   21 2.2.1 Origins and Transformations in Industry������������������������������   21 2.2.2 Transformations in Other Sectors ����������������������������������������   22 2.3 Technology Dynamics and Complexities ����������������������������������������   23 2.3.1 Challenges and Opportunities ����������������������������������������������   23 2.3.2 Effects on Industrialising Countries��������������������������������������   24 2.3.3 Techniques for Productivity in Industry��������������������������������   25 2.4 Fourth Industrial Revolution and Engineering Training ������������������   26 2.4.1 Rapid Transformation to Integration������������������������������������   26 2.4.2 Engineering Education Transformations������������������������������   27 2.4.3 Parallel Transformations in Industry������������������������������������   29 2.5 Impact on Engineering Education and Policies��������������������������������   30 2.5.1 Polytechnics to Universities��������������������������������������������������   30 2.5.2 Shortages and Mismatch of Skills����������������������������������������   31 2.5.3 Double Degrees and Double Majors������������������������������������   32 2.5.4 Collaborations in Southern Africa����������������������������������������   33 xv

xvi

Contents

2.6 Training Challenges and Possible Solutions������������������������������������   34 2.6.1 Complexities and Uncertainties��������������������������������������������   34 2.6.2 From AI to IA�����������������������������������������������������������������������   34 2.6.3 Promotion of Creativity and Innovation ������������������������������   35 2.6.4 Online Learning Resources��������������������������������������������������   36 2.7 Conclusion����������������������������������������������������������������������������������������   37 References��������������������������������������������������������������������������������������������������   38 3 Systems Thinking Research: Adapting for Engineering Change Management ������������������������������������������������������������������������������   41 3.1 Introduction��������������������������������������������������������������������������������������   41 3.2 Systems Thinking Tools��������������������������������������������������������������������   42 3.2.1 Analysis and Synthesis ��������������������������������������������������������   43 3.2.2 Interconnectedness����������������������������������������������������������������   44 3.2.3 Process and Systems Mapping����������������������������������������������   45 3.2.4 Emergence (Outcome of Systems Interactions)��������������������   46 3.3 Systems Thinking Operations ����������������������������������������������������������   47 3.3.1 System Dynamics and Complexities������������������������������������   48 3.3.2 Feedback Loops and Control of System Performance����������   48 3.3.3 Causal Loop Flow Diagrams������������������������������������������������   49 3.4 Implementation of Systems Thinking ����������������������������������������������   51 3.5 Successes and Failures in Systems Thinking������������������������������������   52 3.6 Conclusion����������������������������������������������������������������������������������������   55 References��������������������������������������������������������������������������������������������������   55 4 Academia and Industry Collaborations: A Research and Professional Perspective����������������������������������������������   57 4.1 Introduction��������������������������������������������������������������������������������������   57 4.1.1 Importance of Academia–Industry Partnerships������������������   58 4.1.2 Building Robust and Successful Collaborations������������������   59 4.2 Collaborations in Southern Africa����������������������������������������������������   60 4.2.1 Shortages and Mismatch of Skills in the Region������������������   60 4.2.2 Knowledge-Sharing Workshops��������������������������������������������   62 4.2.3 Sharing of Resources Under Distress ����������������������������������   64 4.2.4 Focus Areas of Discussion and Key Resolutions������������������   66 4.2.5 Foundations for Systems Thinking Modelling���������������������   67 4.3 Industrial Secondments��������������������������������������������������������������������   68 4.4 Continuous Professional Development��������������������������������������������   72 4.5 Project Resources and Equipment����������������������������������������������������   74 4.6 International Backstopping ��������������������������������������������������������������   75 4.7 Academia Dialogue with Captains of Industry��������������������������������   76 4.8 Conclusion����������������������������������������������������������������������������������������   78 References��������������������������������������������������������������������������������������������������   79

Contents

xvii

5 Problem- and Industry-Based Learning: Research, Theory and Practice ��������������������������������������������������������������   81 5.1 Introduction��������������������������������������������������������������������������������������   81 5.2 Problem-Based Learning������������������������������������������������������������������   82 5.2.1 Fundamentals of Problem-Based Learning��������������������������   82 5.2.2 Designing Problem-Based Learning Pedagogy��������������������   84 5.2.3 Implementation of Problem-Based Learning������������������������   86 5.2.4 Challenges and Possible Solutions for PBL ������������������������   87 5.3 Industry-Based Learning (IBL)��������������������������������������������������������   89 5.3.1 Overview of Industry-Based Learning����������������������������������   89 5.3.2 Objectives and Importance of Industry-Based Learning������   90 5.3.3 Formulation and Evaluation of IBL Projects������������������������   92 5.4 Implementation of IBL in Southern Africa��������������������������������������   93 5.4.1 University of Johannesburg��������������������������������������������������   93 5.4.2 Universidade Eduardo Mondlane������������������������������������������   94 5.4.3 Harare Institute of Technology ��������������������������������������������   95 5.4.4 National University of Science and Technology������������������   95 5.4.5 Chinhoyi University of Technology��������������������������������������   96 5.4.6 Namibia University of Science and Technology������������������   97 5.4.7 University of Zimbabwe ������������������������������������������������������   98 5.5 Industrial Secondments: UK Perspective������������������������������������������   98 5.5.1 Criteria for Successful Secondments������������������������������������   99 5.5.2 Establishing Academia Industry Secondments ��������������������   99 5.6 Industrial Design and Design Thinking��������������������������������������������  100 5.7 Systems Thinking Synchronisation of PBL and IBL������������������������  102 5.8 Conclusion����������������������������������������������������������������������������������������  103 References��������������������������������������������������������������������������������������������������  104 6 Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results ��������������������������������������  107 6.1 Introduction��������������������������������������������������������������������������������������  107 6.2 Modelling Systems���������������������������������������������������������������������������  108 6.3 Simulation of Operations������������������������������������������������������������������  109 6.4 Process Mapping and Optimisation��������������������������������������������������  110 6.5 Case Studies��������������������������������������������������������������������������������������  112 6.5.1 Plant Reorganisation Using Machine Distance Matrices������  112 6.5.2 Optimisation for a Multi-product Assembling Plant������������  119 6.5.3 Process Flows and Layout for a Foundry������������������������������  125 6.5.4 Casting Technology for Sustainable Manufacture����������������  130 6.5.5 Comminution and Flotation Circuits in Mineral Processing ����������������������������������������������������������  134 6.6 Conclusion����������������������������������������������������������������������������������������  141 References��������������������������������������������������������������������������������������������������  142

xviii

Contents

7 Capacity Building and Sustainability: Research Findings and Recommendations��������������������������������������������  145 7.1 Introduction��������������������������������������������������������������������������������������  145 7.2 Sustainability Planning and Implementation������������������������������������  146 7.3 Capacity Utilisation in Industry��������������������������������������������������������  147 7.4 Capacity Building in Engineering Education ����������������������������������  150 7.5 Centres of Excellence and Doctoral Training Centres����������������������  153 7.5.1 Doctoral Training Centres: UK Perspective��������������������������  153 7.5.2 Doctoral Training Centres in Sub-Saharan Africa����������������  154 7.5.3 DTC Initiation and Funding��������������������������������������������������  155 7.5.4 DTC Potential Areas of Research in Southern Africa����������  156 7.5.5 DTC Implementation and Self-Sustenance��������������������������  157 7.6 Chairs and Adjunct Appointments����������������������������������������������������  158 7.6.1 Professorial Chairs����������������������������������������������������������������  159 7.6.2 Adjunct or Visiting Professorships ��������������������������������������  159 7.7 Integrated Approaches Using Systems Thinking������������������������������  160 7.8 Continuity of Donor-Funded Projects����������������������������������������������  163 7.9 Conclusion����������������������������������������������������������������������������������������  164 References��������������������������������������������������������������������������������������������������  165 8 Access to Modern Technology: Smart Partnerships for Research and Practice ����������������������������������������������������������������������  167 8.1 Introduction��������������������������������������������������������������������������������������  167 8.2 Situational Analysis��������������������������������������������������������������������������  170 8.2.1 Age of Equipment and Origins ��������������������������������������������  173 8.2.2 Condition and Utilisation of the Equipment ������������������������  174 8.2.3 Maintenance Expertise and Sources of Spares ��������������������  175 8.2.4 Combined Analysis of Factors����������������������������������������������  176 8.3 Build-Operate-Transfer Scheme ������������������������������������������������������  178 8.4 Smart Procurement, Use and Maintenance of Equipment����������������  180 8.5 Consultancy and Research����������������������������������������������������������������  182 8.6 Conclusion����������������������������������������������������������������������������������������  185 References��������������������������������������������������������������������������������������������������  185 9 Coopetition and Virtual Collaborations: Global Competitiveness in Research and Practice��������������������������������  189 9.1 Introduction��������������������������������������������������������������������������������������  189 9.2 Coopetition in Higher Education������������������������������������������������������  190 9.2.1 Virtual Collaborations and Networks in Higher Education��������������������������������������������������������������  193 9.2.2 Coopetition at Multiple Levels in Higher Education������������  194 9.3 Higher Education Partnerships in Sub-Saharan Africa ��������������������  195 9.3.1 NUSESA and EEEP Coopetition Models����������������������������  195 9.3.2 HEP SSA Coopetition and Virtual Model: SAE2Net������������  197 9.3.3 HEP SSA Coopetition Model Objectives ����������������������������  199 9.4 HEP SSA Coopetition Model Outcomes and Impact ����������������������  202 9.5 Challenges and Opportunities in Virtual Collaborations������������������  204 9.6 Conclusion����������������������������������������������������������������������������������������  206 References��������������������������������������������������������������������������������������������������  207

Contents

xix

10 Incubation and Technology Parks: Recent Trends, Research and Approaches ����������������������������������������������������������������������  209 10.1 Introduction������������������������������������������������������������������������������������  209 10.2 Business Incubation Principles ������������������������������������������������������  212 10.2.1 Business Incubators and Accelerators ������������������������������  214 10.2.2 Classification of Business Incubators��������������������������������  215 10.2.3 Academia Business Incubation Process and Selection������  216 10.2.4 Incubation Performance and Impacts��������������������������������  217 10.3 Innovation Hubs and Industrial Technology Parks ������������������������  218 10.3.1 Innovation Hub and Agro-Industrial Park: University of Zimbabwe����������������������������������������������������  219 10.3.2 Centre for Minerals Research: University of Cape Town ��������������������������������������������������  219 10.3.3 Institute for Intelligent Systems: University of Johannesburg ����������������������������������������������  220 10.3.4 Technopreneurship Development Centre: Harare Institute of Technology������������������������������������������  221 10.3.5 Food Science and Technology: Universidade Eduardo Mondlane��������������������������������������  221 10.3.6 Renewable Energy: Namibia University of Science and Technology������������������������������������������������  222 10.4 Incubation Success Variables and Factors��������������������������������������  223 10.5 Customisation of Incubators for Flexibility������������������������������������  225 10.6 Conclusion��������������������������������������������������������������������������������������  227 References��������������������������������������������������������������������������������������������������  228 11 Commercialisation and Industrialisation: Research Prognosis for Academia Entrepreneurships ������������������������  229 11.1 Introduction������������������������������������������������������������������������������������  229 11.1.1 The Triple Helix Model ����������������������������������������������������  230 11.1.2 Background to Commercialisation and Industrialisation����������������������������������������������������������  230 11.1.3 Entrepreneurships in Academia����������������������������������������  231 11.2 Knowledge and Technology Transfer as Tools for Commercialisation������������������������������������������������������  233 11.3 Academia Start-Ups and Spin-Offs������������������������������������������������  234 11.4 Intellectual Property Rights in Academia Research������������������������  236 11.5 Support Infrastructure ��������������������������������������������������������������������  238 11.6 Entrepreneurship Models and Mechanisms������������������������������������  239 11.7 Academia Entrepreneurship in Southern Africa ����������������������������  241 11.8 Performance Measurement and Sustainability��������������������������������  243 11.8.1 Importance-Performance Analysis������������������������������������  244 11.8.2 Analysis of Inputs and Outputs ����������������������������������������  245 11.9 Drivers and Barriers to Academia Entrepreneurship����������������������  247 11.9.1 Stimulants for Academia Entrepreneurship����������������������  247

xx

Contents

11.9.2 Obstacles to Academia Entrepreneurship��������������������������  248 11.9.3 Packaging a Winning Start-Up to Attract Business Incubators ������������������������������������������  249 11.10 Conclusion��������������������������������������������������������������������������������������  251 References��������������������������������������������������������������������������������������������������  252 12 Modelling the ‘Bridge’: Research Verification and Validation������������  255 12.1 Introduction������������������������������������������������������������������������������������  255 12.2 Equipment and Technology������������������������������������������������������������  258 12.3 Skills Development and Training����������������������������������������������������  262 12.4 Professional Development Policies������������������������������������������������  264 12.5 Integrated Universal Systems Thinking Model������������������������������  266 12.6 Model Verification and Validation��������������������������������������������������  269 12.7 Conclusion��������������������������������������������������������������������������������������  271 References��������������������������������������������������������������������������������������������������  271 13 Challenges and Opportunities: Discussion and Predictions from Research Findings��������������������������������������������������������������������������  273 13.1 Introduction������������������������������������������������������������������������������������  273 13.2 Practices and Shortfalls in Academia and Industry������������������������  275 13.3 Capacity Utilisation and Productivity in Industry��������������������������  277 13.4 Capacity Building and Sustainability���������������������������������������������  279 13.5 Build-Operate-Transfer: Smart Procurement of Equipment����������  280 13.6 Community Service and Spin-Off Activities����������������������������������  282 13.7 Constraints and Limitations������������������������������������������������������������  285 13.8 Regional Collaborations and Integration����������������������������������������  287 13.9 Conclusion��������������������������������������������������������������������������������������  288 References��������������������������������������������������������������������������������������������������  289 14 Conclusions: Consolidated Research Findings and Recommendations������������������������������������������������������������������������������������  291 14.1 Introduction������������������������������������������������������������������������������������  291 14.2 Industrial Transformations��������������������������������������������������������������  292 14.3 Academia and Industry Partnerships����������������������������������������������  293 14.4 Capacity Building and Sustainability���������������������������������������������  293 14.5 Regional Integration and Internationalisation��������������������������������  293 14.6 Commercialisation of Research and Wealth Creation��������������������  294 14.7 Systems Modelling and Integration������������������������������������������������  294 14.8 Contributions to Research and Knowledge������������������������������������  294 14.9 Limitations, Challenges and Opportunities������������������������������������  295 14.10 Recommendations for Further Research����������������������������������������  295 Appendix ����������������������������������������������������������������������������������������������������������  297 References ��������������������������������������������������������������������������������������������������������  303 Index������������������������������������������������������������������������������������������������������������������  315

List of Figures

Fig. 1.1 Zimbabwe’s Trade Balance (1995–2015). Source: Zimstat (2014)���������������������������������������������������������������������������������������� 6 Fig. 1.2 SADC gross domestic product (1960–2012). Source: SADC (2014)���������������������������������������������������������������������������� 7 Fig. 2.1 Successive stages of the Industrial Revolutions������������������������������������ 21 Fig. 3.1 Interconnected system with nodes and feedback loops������������������������ 44 Fig. 3.2 Unconnected systems map for stakeholders in academia and industry������������������������������������������������������������������������������������������ 46 Fig. 3.3 Academia–Industry causal loop flow diagram�������������������������������������� 50 Fig. 4.1 University of Zimbabwe engineering graduation statistics. (Source: Nyemba (2018)) �������������������������������������������������������������������� 61 Fig. 4.2 Focus areas of discussion and responsibilities�������������������������������������� 67 Fig. 4.3 Connecting activities, attributes and competences������������������������������� 72 Fig. 5.1 Systems thinking causal loop feedback between PBL and IBL �������� 102 Fig. 6.1 Furniture manufacturing plant layout and process flow for bunk beds�������������������������������������������������������������������������������������� 114 Fig. 6.2 Product assembly tree for the bunk bed showing quantities of parts�������������������������������������������������������������������������������� 115 Fig. 6.3 Production flow processes for the bunk bed �������������������������������������� 116 Fig. 6.4 Schematic of the reorganised furniture manufacturing plant�������������� 118 Fig. 6.5 Five-stage process flows for industrial pallets������������������������������������ 120 Fig. 6.6 Ten-stage process flows for domestic baby tenders���������������������������� 120 Fig. 6.7 Mathematical and simulation model for an s-stage process flows������ 121 Fig. 6.8 Process and waiting times before and after optimisation�������������������� 130 Fig. 6.9 Gating system concepts���������������������������������������������������������������������� 132 Fig. 6.10 The platinum company’s comminution and flotation circuits������������ 137 Fig. 6.11 (a) Comminution resource utilisation, (b) flotation resource utilisation�������������������������������������������������������������������������������������������� 139 xxi

xxii

List of Figures

Fig. 7.1 Relationships of industry with higher education institutions�������������� 151 Fig. 7.2 Joint projects and sharing of resources between industry and HEIs���������������������������������������������������������������������������������������������� 152 Fig. 7.3 Factors influencing integration������������������������������������������������������������ 161 Fig. 7.4 Systems integration of technology training and policies�������������������� 163 Fig. 8.1 (a) Analog process control simulator, (b) conventional lathe machines (Source: Nyemba and Mbohwa 2018) ���������������������� 169 Fig. 8.2 (a) Average age of equipment and (b) countries of origin (Source: Nyemba et al. 2017) ������������������������������������������������������������ 173 Fig. 8.3 (a) Condition of equipment, (b) utilisation of equipment (Source: Nyemba et al. 2017) ������������������������������������������������������������ 174 Fig. 8.4 (a) Maintenance expertise, (b) sources of spares (Source: Nyemba et al. 2017) ������������������������������������������������������������ 175 Fig. 8.5 Systems thinking causal flow diagram for the BOT �������������������������� 180 Fig. 8.6 Smart procurement and partnerships model (Source: Nyemba and Mbohwa 2018)������������������������������������������������ 182 Fig. 8.7 Equipment acquired through the SPP model�������������������������������������� 184 Fig. 9.1 Value net system for coopetition in higher education������������������������ 192 Fig. 9.2 EEEP hub and spoke arrangement (Source: Nyemba et al. 2019) ������������������������������������������������������������ 196 Fig. 9.3 Revamped hub and spoke HEP SSA arrangement coopetition model�������������������������������������������������������������������������������� 198 Fig. 10.1 Incubation systems thinking process�������������������������������������������������� 227 Fig. 11.1 Systems thinking integration of academia and industry �������������������� 234 Fig. 11.2 A typical importance-performance analysis. (Source: Warner et al. 2016) �������������������������������������������������������������� 245 Fig. 11.3 Importance-performance analysis for SAE2Net institutions�������������� 246 Fig. 12.1 Equipment and technology (ET) systems thinking sub-model ���������� 260 Fig. 12.2 Skills Development and Training (SDT) systems thinking sub-model�������������������������������������������������������������������������������������������� 263 Fig. 12.3 Professional development policies (PDP) systems thinking sub-model�������������������������������������������������������������������������������������������� 265 Fig. 12.4 Conceptualised universal systems thinking (UST) model of the ‘Bridge’�������������������������������������������������������������������������� 267 Fig. 13.1 Systems thinking groundwater enterprise model�������������������������������� 284 Fig. 13.2 Stages in the development and implementation of the groundwater enterprise ������������������������������������������������������������ 285

List of Tables

Table 1.1 EEEP and HEP SSA collaborating institutions in Southern Africa������������������������������������������������������������������������������ 11 Table 1.2 Case study companies in Southern Africa������������������������������������������ 12 Table 2.1 Academic and technological attributes of the Industrial Revolutions�������������������������������������������������������������� 28 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5 Table 4.6

Knowledge-sharing workshops and conference �������������������������������� 63 Key resolutions, purposes and stakeholders �������������������������������������� 66 Systems thinking elements, functions and purposes�������������������������� 68 Summary of secondments and attachments under EEEP ������������������ 70 Summary of secondments under the HEP SSA scheme�������������������� 71 Dialogue with captains of industry (engineering experts)������������������ 77

Table 5.1 Traditional versus problem-based learning pedagogies �������������������� 83 Table 6.1 Machinery and functions for the furniture manufacturing plant�������������������������������������������������������������������������� 114 Table 6.2 Machine distance matrix among interacting workstations – bunk beds ���������������������������������������������������������������� 117 Table 6.3 Comparison of component travel distances (m) for bunk beds������������������������������������������������������������������������������������ 118 Table 6.4 Parameters, variables and probability distribution for industrial pallets�������������������������������������������������������������������������� 122 Table 6.5 Parameters, variables and probability distribution for baby tenders�������������������������������������������������������������������������������� 123 Table 6.6 Average queue times for (a) industrial pallets and (b) domestic baby tenders���������������������������������������������������������������������� 124 Table 6.7 Stages and time for a typical batch of the 80 mm grinding balls������������������������������������������������������������������������������������ 127 Table 6.8 Number of movements per day in the production of 80mm grinding balls�������������������������������������������������������������������� 128 Table 6.9 Distances between interacting workstations������������������������������������ 128 xxiii

xxiv

List of Tables

Table 6.10 Distances and times between workstations before and after rerouting ���������������������������������������������������������������� 129 Table 6.11 Binary dominance matrix for selection of optimal gating system������������������������������������������������������������������������������������ 132 Table 6.12 (a) Average pouring time, (b) average mass of balls before and after fettling�������������������������������������������������������������������� 133 Table 6.13 Sample SAG mill feed���������������������������������������������������������������������� 137 Table 6.14 Sample cone crusher feed���������������������������������������������������������������� 138 Table 7.1 Factors affecting sustainability planning and operational strategies ���������������������������������������������������������������� 148 Table 9.1 Southern Africa doctoral training centres under the HEP SSA coopetition model������������������������������������������������������ 201 Table 10.1 Selected Southern African institutions and incubation variables ������������������������������������������������������������������ 225

About the Authors

Wilson R. Nyemba  is a senior lecturer in mechanical engineering at the University of Zimbabwe with over 30 years of experience both in industry and academia. He designed and developed a wide range of engineering products in different capacities in industry from product development to engineering management. He also formulated and led a number of successful ventures at the University of Zimbabwe where he served as Dean of the Faculty of Engineering. He also served as Chairman of WaterNet and project manager for the Royal Academy of Engineering projects for enhancing the quality of engineering education in Southern Africa. He is an accomplished consultant and researcher with interests in engineering education, capacity building and sustainability, systems thinking and modelling. He holds a BSc honours degree in mechanical engineering from the University of Zimbabwe, an MSc degree in advanced mechanical engineering from the University of Warwick in England and a Doctor of Engineering degree in mechanical engineering from the University of Johannesburg in South Africa. He is also currently co-appointed as a senior research associate in the Department of Quality Assurance and Operations Management at the University of Johannesburg. He has authored and published 55 peer-reviewed papers in journals and conference proceedings as well as several consultancy reports. He has received several awards and recognition for outstanding research.

xxv

xxvi

About the Authors

Charles Mbohwa  is the University of Zimbabwe provice chancellor responsible for strategic partnerships and industrialisation as well as a visiting professor at the University of Johannesburg. He previously worked for the National Railways of Zimbabwe and the University of Zimbabwe as a senior lecturer and head of Department of Mechanical Engineering. He has extensively published papers in peer-reviewed journals and conferences as well as book chapters and 5 books. He holds a BSc honours degree in mechanical engineering from the University of Zimbabwe, a Master of Science in operations management and manufacturing systems from the University of Nottingham and a Doctor of Engineering from the Tokyo Metropolitan Institute of Technology in Japan. He was a Fulbright scholar in 2006–2007 at the Supply Chain and Logistics Institute, School of Industrial and Systems Engineering, Georgia Institute of Technology, as well as a Japan Foundation fellow. He is also a reviewer for more than 20 international journals and is a member of the editorial boards/committees of 5 journals. Keith F. Carter  is a chartered mechanical and nuclear consultant engineer who has also trained as a naval architect. He is a director and principal consultant for Keimar Consultancy in Leicester, England. Over the last 15 years, Keith has been associated with a wide variety of engineering projects for Rolls-Royce at Derby, England, in both the nuclear marine and aerospace divisions principally specialising in structural integrity issues. He has also carried out other significant projects in a variety of fields, including the analysis of AGR graphite cores for British Energy (EDF). Dr. Carter also holds the post of visiting design professor within the School of Engineering at the University of Leicester in England, bringing in considerable engineering and industrial experience to the teaching of students and to various research projects. He holds a Bachelor of Science degree in chemistry and a PhD in statistical mechanics using computer simulation, both from the Royal Holloway College at the University of London and has authored over 30 academic papers as well as numerous reports for client companies.

Chapter 1

Introduction

Abstract  Skills deficits in engineering, science and technology throughout the world require innovative strategies in order to drive industry in view of the rapid changes in technology and the demands for the fourth industrial revolution and prepare for the Digital Ecosystem. Several initiatives have been developed and implemented to improve the quality of engineering education. However, while most of these initiatives have been quite helpful, particularly in Sub-Saharan Africa, one major limitation was lack of continuity. This chapter analyses some of these initiatives as a base for the research by focussing on the achievements, shortfalls and scaling-up for sustainability. The chapter also focusses on how engineering education has been affected by the rapid trends in technology vis-a-vis macro-economic situations and policies for engineering skills development. This synopsis was aimed at developing strategies to ensure that the acquisition of engineering skills at tertiary institutions was done in such a way as to match those required by industry. Keywords  Collaborations · Education · Engineering capacity · EEEP · HEI · HEP SSA · Industry partnerships · Mismatch and shortage of skills · NUSESA · Skills development · Sustainability · Training

1.1  Research Background According to studies carried out in various countries in Sub-Saharan Africa such as Malawi (ICE and GDC 2002a), Mozambique (ICE and GDC 2002b), Rwanda (Goodsir et al. 2009), South Africa (Lawless 2007), Tanzania (ICE and GDC 2002c), Nigeria, Ghana and Zimbabwe (Afonja et  al. 2005), the region has been heavily affected by a perennial and persistent lack of adequate engineering skills and capacity to drive the various sectors of industry. Not only did the studies reveal shortages © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_1

1

2

1 Introduction

of engineering skills but also inadequacies in the education and training of engineers due to the use of old equipment and outdated technology, which often resulted in mismatches of skills imparted to graduates and those required by industry (Bubou et al. 2017). This was exacerbated by the wide gap between academia and industry (Matthews et al. 2012) as well as the high dependence on the limited foreign aid, which often resulted in the lack of continuity or sustainability in engineering education and training. More recently and despite having over 20 Higher Education Institutions (HEIs), a national critical skills audit revealed that Zimbabwe had an average skills deficit of 62% but more specifically over 90% for science and technology (Government of Zimbabwe 2018).

1.2  Initiatives to Enhance Engineering Education Foreign aid dependence for Sub-Saharan Africa dates back to the colonial era of the early to the late 1900s. Western governments provided all the necessary and required support for both tertiary institutions and industry. This ranged from skilled personnel to machine tools and infrastructure. Workshop and laboratory equipment and staff for most of the engineering faculties were supplied as part of the agreements to establish these institutions as colleges of universities mostly from Europe. These were supported by aid agencies such as the Overseas Development Authority (ODA) for countries such as Zimbabwe, Zambia, Malawi, etc. that were under British rule (Zinyemba 2010), while the Organisation for Economic Cooperation and Development (OECD) supported countries such as Angola and Mozambique that were under Portuguese rule (Macauhub 2013). With time and as the colonial countries became independent, the colleges were weaned off to run as independent institutions while the expatriate staff gradually returned to their home countries (Zinyemba 2010). Regrettably, in many of the cases, no sustainability plans were left in place to ensure continuity. Although the ODA continued to support staff development at tertiary institutions through scholarships to study abroad, the equipment that had originally been provided was not replenished, leading to deterioration, obsolescence and in some cases underutilisation due to lack of expertise. According to the World Bank (2010), this was worsened by recession, particularly in Southern Africa during the period 2000–2010, which inevitably forced some of the trained and skilled personnel to flee the region for greener pastures abroad. The other reason for failure to replenish or maintain the equipment was the limited financial capacities by the local institutions as they relied almost entirely on government grants that came from scarce government resources. As such, although some of the equipment was still functional, most of it had gone beyond 25 years, hence outdated technology which contributed to the mismatch of skills from tertiary institutions and those that industry required. This also resulted in the production of engineering graduates who may have been qualified but unemployable. The underlying philosophy of the industrial revolutions was the rapid

1.3  NUSESA, EEEP and HEP SSA

3

changes in technology at a much faster pace than it did a few years ago. This trend forced Original Equipment Manufacturers (OEMs) to modify laboratory and engineering equipment and in some cases completely change the machine tools and the technologies that drove them (Martinez et  al. 2010). While global competition forced the OEMs to reduce their equipment prices in order to remain profitable, the cost of new equipment remained unaffordable to tertiary institutions in the industrialising world (Allais and Gobert 2016). The introduction of microchips, robotics and machine learning has considerably simplified operations in the fourth industrial revolution (Broadbent and McCann 2016). However, such changes and complexities required continuous professional development of the users as well as those training new engineers to drive these systems in future, a costly requirement especially for industrialising countries (Ahuja and Khamba 2008). In most cases, expertise to train these could only be found at the OEMs. In addition, the maintenance required regular calibration, thus more problematic compared to conventional machines (Ju 2012). While countries in the industrialised world, where the OEMs are domiciled, could cope with these changes and afford to replenish their machine tools in tandem with rapid changes in technology, in the industrialising world, such as most of those in Sub-Saharan Africa, this was a costly challenge. In addition, lack of synergies and formal links and collaborations between industry and academia created another cost centre for prospective employers who ended up training engineering graduates beyond what they would have done had there been adequate grounding before graduation (World Bank 2010). Most of these challenges demotivated academics and students who advertently lost interest or developed a fear for working with machines. All these challenges partly contributed to the need to establish projects such as the Network of Users for Scientific Equipment in Eastern and Southern Africa (NUSESA), financially supported by the Swedish International Development Cooperation Agency (Sida), the Enriching Engineering Education Program (EEEP) and the Higher Education Partnerships for Sub-Saharan Africa (HEP SSA), both funded by the Royal Academy of Engineering of the United Kingdom.

1.3  NUSESA, EEEP and HEP SSA Research output in the region was seriously affected by obsolescent equipment and lack of skills to maintain the same, prompting the establishment of NUSESA in 1989, supported by Sida with five founding members, Malawi, Mozambique, Tanzania, Zambia and Zimbabwe, and by the new millennium, the membership had risen to 14 (Lindgren 2001). The establishment of NUSESA was aimed at developing long-term strategies for sustainability through the improvement of procurement, use and maintenance of scientific equipment while building capacity through the development of collaborative training, research and exchange of staff among the faculties of engineering in Eastern and Southern Africa (Lindgren 2001). A secretariat was established for the initiative and was based at the University of Zimbabwe,

4

1 Introduction

coordinating the sharing of equipment and exchange of skilled staff in the use and maintenance of the equipment. However, this initiative could only survive during the period of financial support from Sida, purportedly due to the failure to put in sustainability plans for the initiative and the failure to secure support from local and regional governments. Despite funds running out after the first 5 years of NUSESA, the project continued with resources derived from member institutions until the mid-2000s when it could not be sustained by local and regional governments. However, engineering academics in Sub-Saharan Africa continued to engage with their counterparts in the United Kingdom. Initiatives such as the Africa-UK Partnership for Development supported by the Department for International Development (DFID) (Matthews et  al. 2012) were established. From these engagements, engineering managers revealed the lack of engineering capacity and capability in Southern Africa as the main bottleneck to meeting the economic, social and environmental needs of nations within the region (Matthews et  al. 2012). Additionally, inadequate infrastructure and a shortage of engineers coupled with a mismatch of skills affected the region’s ability to tap into its abundant resources, such as solar radiation, minerals and agricultural land, in order to meet the UN Sustainable Development Goals. Since then, the Africa-UK Partnership for Development engaged extensively with engineering communities in the region through thematic workshops and a search for long-lasting solutions to enhance the quality of engineering education and the acquisition of appropriate skills to drive industry. The continued engagements with the Africa-UK Partnership for Development saw the Universities of Zimbabwe (UZ) and Dar es Salaam (UDSM) being awarded grants by the Royal Academy of Engineering (RAEng) to enhance the training of engineers both for academia as well as industry under the auspices of a 2-year project (2013–2015), Enriching Engineering Education Program (EEEP) (RAEng 2017a). The project operated on a hub and spoke arrangement where UDSM and UZ were the hubs for Eastern and Southern Africa, respectively, while other regional institutions were the spoke institutions. In order to enhance the skills for engineering academics, the programs in the two regions focussed on continuous professional development training to raise the standards of academics’ skills in tandem with changes in technology, research collaborations and sharing of experiences in the region through knowledge-sharing workshops and conferences, as well as secondment to industry to familiarise with modern equipment, systems and technology. The objectives were all largely achieved and successful as demonstrated through feedback seminars where young and inexperienced engineering academics expressed their satisfaction and confidence in delivering their duties as lecturers. This was also evidenced by student evaluations at the end of semesters. A significant number of industry-based projects were generated as a result of the interactions and secondments. Some of the significant achievements from the EEEP included the UZ’s engineering academics’ development of a groundwater project to supply the entire campus of 20,000 students and 5000 staff with uninterrupted supplies of clean water abstracted from 13 boreholes that were sunk around the campus. This community service provision by engineering academics consisted of four main

1.4  Macroeconomic Situations and Policies

5

segments, that is Geoinformatics and Surveying for designing of the pipe routes and levelling, Civil Engineering for excavations and construction of the sump and pump-house, Mechanical Engineering for all the pump-house pipe fabrications and installations and setting up the purification plant and electrical engineering for the design of the electrical network and control system. The project was commissioned in 2014 and has been running uninterrupted, providing a solution to the perennial problems of water shortages on campus. The other significant result was the provision of a fully funded Professorial Chair for Mining Engineering by Zimbabwe Platinum Mines (Zimplats), one of the industry partners in the EEEP. The position was filled in by a professor from Penn State University in the United States and provided a perfect link between industry and academia as part of the requirements for the position, that is mentoring young engineering academics while also providing a service and solutions to industry. The continued interactions between industry and academia not only saw more industry partners coming on board with various interventions such as provision of scholarships for students and places for attachment (students) and secondments (academics) but also resulted in the UZ engaging a full-time Industrial Liaison Officer to provide the bridge between all industry players and the institution. Following the successful execution of the EEEP and the various interventions as articulated above, the RAEng upscaled their support to have more hubs and spokes in both regions, Eastern and Southern Africa under the new grant for Higher Education Partnerships for Sub-Saharan Africa (HEP SSA) from 2016 (RAEng 2017b). More recently, the UZ in partnership with seven other institutions in the region, that is Chinhoyi University of Technology, National University of Science and Technology, Harare Institute of Technology and the Zimbabwe National Defence University from Zimbabwe and the University of Johannesburg, Universidade Eduardo Mondlane and Namibia University of Science and Technology together with the University of Leicester as the UK partner, as well as five industry partners from Zimbabwe, successfully applied for another grant from the RAEng to expand the scope for enhancing the quality of engineering education through a broad and expanded version of the objectives. This book focusses on building on those objectives and achievements from NUSESA, EEEP and HEP SSA by outlining a cocktail of engineering change management techniques using systems thinking in handling problem-based learning (PBL), industry-based learning (IBL) for capacity building and sustainability of these noble initiatives.

1.4  Macroeconomic Situations and Policies The need to bring industry closer to academia was prompted by the global financial crisis of 2008 which had a severe impact on most countries in Southern Africa (Bakrania and Lucas 2009). Many companies, especially those in engineering and manufacturing, scaled down operations. In some cases, some of these companies were liquidated or their capacity utilisation negatively affected. Despite having

6

1 Introduction

Fig. 1.1  Zimbabwe’s Trade Balance (1995–2015). Source: Zimstat (2014)

weak global linkages, industrialising countries, most of which make up the Southern Africa Development Community (SADC), were severely affected by the crisis due to their heavy reliance on foreign aid for equipment, technology and engineering skills (SADC 2014). The impact was however felt to different degrees depending on each country’s macroeconomic situation and political stability. Zimbabwe was probably the worst affected as in early 2009, it experienced the second highest hyperinflation recorded in world history (Munangagwa 2011), attributed to several reasons such as economic sanctions (Hove 2012), macroeconomic imbalances, political instability or mismanagement (Aisen and Veiga 2013). Whichever the reason was, the country went through its worst ever economic crisis at unprecedented levels that affected both tertiary institutions and industry. Most of the companies that remained operational in Zimbabwe at that time produced or provided services just enough to survive from one day to the next. These companies depended heavily on imported engineering skills and spare parts for their machine tools. They lacked strategies for import substitution resulting in a rapid decline of exports. The balance of payments skewed heavily towards a consumptive society relying heavily on imports, leading to an annualised rate of 13.2% from 2009 for a period of 5  years (Monyau and Bandara 2017), with a rapidly declining trade balance, as shown in Fig.  1.1 (Zimstat 2014). The worsening macroeconomic situation and hyperinflation which peaked towards the end of 2008 led to the complete collapse of the Zimbabwean currency and the adoption of multiple foreign currencies for trade locally from early 2009 (Kramarenko et al. 2010). Albeit at different and better scales, the trend from Fig. 1.1 was a mirror reflection of the other countries in the SADC region, evidenced by the declining gross domestic product (GDP) per capita as shown in Fig. 1.2 (SADC 2014), which was

1.4  Macroeconomic Situations and Policies

7

Fig. 1.2  SADC gross domestic product (1960–2012). Source: SADC (2014)

however buoyed by the semi-industrialised South Africa and diamond-rich Botswana (SADC 2014). The capacity utilisation at engineering and manufacturing companies that remained operational dropped to the lowest average of about 10% in 2008. With the introduction of multiple currencies, this average gradually eased upwards to 32.2% in 2009, 43.7% in 2010 and a peak of 57.2% in 2011 (Gadzikwa 2013). Despite this relief for engineering and manufacturing companies in Zimbabwe, the use of foreign denominated currencies was not sustainable as evidenced by cash shortages that started emerging after less than 5 years of the collapse of the local currency (Bussiere et al. 2012). The foreign currency cash shortages forced the Zimbabwean authorities to introduce small denominations of the bond note, a surrogate currency for local trade only (Mangudya 2016). Although the surrogate currency was meant to address the foreign currency cash shortages, this was not sustainable either as the bond notes were soon in short supply, forcing the prices of goods and services to skyrocket. The authorities were also not keen on introducing higher denominations or printing more bond notes for fear of returning to hyperinflation (Makochekanwa 2016). Further measures were introduced to address the worsening balance of payments by introducing Statutory Instrument 64(SI 64) in 2016, which restricted imports through issuing import licences for a small selection of goods in order to protect local manufacturers (ZIMRA 2017). This intervention was also not sustainable as it was too punitive and lacked the spirit of consumers sourcing competitive goods and services.

8

1 Introduction

The intended local manufacturers did not benefit much from the intervention evidenced by the stagnant capacity utilisation in their firms (Murangwa and Njaya 2017). The liquidity challenges continued to affect the intended beneficiaries as they still needed cash or foreign exchange for retooling or to import spare parts to maintain their machine tools. The introduction of the SI 64 was probably a rushed decision instead of assisting the local firms to retool or recapitalise, let alone support the development of the much needed engineering skills required to operate the machine tools (Murangwa and Njaya 2016). The problems associated with low capacity utilisation and productivity needed to be dealt with first before introducing measures such as SI 64. Evidently, this chronicle of events in a short space of time (2009–2015) appeared to lack a holistic approach to solving different but related and complex challenges. One of the key objectives and deliverables of this book is to present holistic approaches to solving complex problems by decimating them through an integrated approach where all aspects such as technology dynamics, human resources and skills development as well as the policies required, in order to realise a full potential for bridging the gap between academia and industry.

1.5  Engineering Skills Development and Training Inadequate engineering skills and shortage of engineers is a worldwide challenge. However, this varies from country to country. According to data from UNESCO (2010), industrialised countries had 20–50 scientists and engineers for a population of 10,000, while most industrialising countries such as those in Sub-Saharan Africa approximately have one scientist/engineer for the same population count. However, the general trend throughout the world has been the insufficiency of engineering skills required to drive industry. According to surveys carried out in different parts of the world, various reasons have been advanced for the shortages. In the United Kingdom for instance, one of the reasons given has been the perception of lower rewards in the engineering profession compared to other professions (Harrison 2012). For Southern Africa, most engineers, particularly those in academia, have been demotivated due to lack of modern equipment and exposure to modern technology, often resulting in insufficient training and poor quality of engineering education (Matthews et al. 2012). Most of the tertiary institutions in Southern Africa still make use of old and conventional equipment in their laboratories, most of which were donated by colonial governments as far back as 20–30  years ago (Mwamila and Thulstrup 2001). Initiatives such as NUSESA, EEEP and HEP SSA were all aimed at improving the quality of engineering education and building capacity through the development of collaborative training, research and exchange of human resources among the tertiary institutions offering engineering education. A NUSESA end-of-project report revealed that laboratory equipment in the collaborating institutions were in poor working conditions, obsolete or underutilised due to maintenance challenges, aging or lack of expertise (Lindgren 2001). This was mainly due to lack of capacity to maintain or replenish the equipment, thus leading to inappropriate skills imparted

1.6  Synopsis and Scope of the Book

9

on graduate engineers. Evidently, this demotivated engineering academics, who failed to match their counterparts in the industrialised world in terms of research output and relevance, hence the need for collaborations with institutions in those countries, for accessing new technologies and keeping in tandem with the rest of the world (Lucas et al. 2014). For the purposes of collaborative research and technology transfer, the mobility of engineers throughout the world, whether internally or externally, has been encouraged and in practice in most industrialised countries (Uhly et al. 2017). However, the same mobility of engineers in Southern Africa has been somewhat limited, and if anything, it only happened when engineers were seeking greener pastures (Matthews et al. 2012). This also contributed to the low capacity utilisation and productivity at manufacturing companies in the region (Matthews et al. 2012). This intervention was mooted after extensive engagements by NGOs such as Africa-UK Partnership for Development, DFID and Engineers Against Poverty with tertiary institutions and industry in the region. Further, the interactions between engineering academics and industry through this initiative revealed that the key to building engineering capacity and skills in Southern Africa entirely depended on the improvement of tertiary engineering education (Matthews et al. 2012). While this initiative was largely successful, evidenced by the number of engineering academics seconded to industry, professional training and workshops held to share knowledge and practice, tapping from collaborating institutions from the United Kingdom, such as the University of Leicester, Imperial College of London and University College of London, a lot still needed to be accomplished in order to make such initiatives sustainable. The success of the EEEP, which led to the scaling of support by the RAEng to HEP SSA, saw more tertiary institutions benefitting from collaborating with UK institutions and cementing linkages with industry. Additionally, more industry partners have come on board to provide secondment facilities for engineering academics and attachments for students, apart from the financial contributions, such as provision of scholarships and equipment and Professorial Chairs. However, for the continuity of such noble initiatives, a holistic approach was necessary to attract buy-ins from other industry players. Ideally, each discipline in a tertiary institution should have at least one Professorial Chair funded by industry, similar to the one that was funded by the Zimbabwe Platinum Mines following the successful execution of the EEEP. This book aims at developing systems thinking models that can be used to create win-win situations for both industry and academia, and if adhered to and applied, self-sustenance for capacity building and sustainability can be achieved by bringing industry closer to academia.

1.6  Synopsis and Scope of the Book This book culminated from years of consultancy and research that also provided a platform for one of the authors to carry out and successfully complete their doctoral studies at the University of Johannesburg. The work came out of a realisation of the mismatch of engineering skills produced by universities and those that industry

10

1 Introduction

required. This was coupled with the challenges of rapid changes in technology and conventional methods employed by industry in the region. The various initiatives developed in this work ranged from collaborations, attachments and secondments with the ultimate aim of bridging the gap between industry and academia. Apart from producing relevant and required engineering skills, expertise provided by engineering academics to industry helped in optimising process flows and production through reorganisations for efficiency as well as maximised productivity and throughput. This research was also motivated by a number of factors, chief among them the decline in capacity utilisation at engineering and manufacturing companies, rapid decline in trade balances and the GDP per capita and the need for continuity and sustainability of the noble initiatives. This was derived from interactions with industry through secondment of engineering academics and attachment of students during the period spanning from 2012 to 2019, based on the following hypothetical conundrums: 1. A graduate engineer without the requisite and continual exposure to modern equipment is unproductive in a modern day industry. 2. A fully equipped and automated engineering or manufacturing company without appropriate expertise and policies is a recipe for low capacity utilisation and accelerates obsolescence of machine tools. 3. Documented statutory and company policies without the requisite engineering skills supported by modern equipment and technology suffer from the effects of global competition. 4. Industry working in isolation from academia and vice-versa is tantamount to creating unsustainable strategies to solve problems in this dynamic era. Resolving these challenges in an industrialising environment can be a mammoth task, hence the need for holistic and systems thinking approaches to keep industry closer to academia. Various techniques such as Design for Manufacture and Assembly (DFMA), Concurrent or Simultaneous Engineering, Flexible Manufacturing Systems (FMS) etc. have been developed to improve capacity utilisation, efficiency and productivity in industry, but for these to be realised fully in the era of rapid technological changes, a paradigm shift was necessary, hence the need for collaborations and synergies between industry and academia. The focus for the book is to enhance the collaborations in order to resolve the cocktail of challenges drawn from the hypothetical conundrums while also providing avenues to build capacity for industry and academia in a sustainable manner. The various sections and chapters of this book revolved around answering the following research questions, which then culminated in the development of systems thinking sub-models that were integrated to a universal model to enhance the quality of engineering education and engineering practice in the region, thus bridging the gap between industry and academia. • Role of tertiary institutions in addressing skills challenges to meet industry needs • Interventions by policy-makers to create enabling environments to resolve the skills deficit

1.7  Collaborating Institutions and Industry Partners

11

• Industry’s contributions in human resources development required to drive industry • Professional bodies mediation to narrow the gap between industry and academia • Regulatory bodies’ role for accreditation through regional qualification frameworks • Promotion of innovations and commercialisation among engineering academics and students • Lessons that can be derived from the industrialised world From this general list, the major task for the work in the book was the application of reductionism to the broad categories of technology, training and policies related to the various challenges aforementioned that contributed to low capacity utilisation and productivity at engineering and manufacturing companies and synthesising and mapping them in the process of developing systems thinking models.

1.7  Collaborating Institutions and Industry Partners The work in this book was derived from collaborations of nine tertiary institutions and 14 industry partners in the Southern African region, although most of them were based in Zimbabwe, for logistical reasons. All the tertiary institutions as aforementioned offered training in different engineering disciplines, and the industry partners were carefully chosen on the basis of different portfolios and in line with the engineering disciplines that the institutions offered, that is Civil, Electrical, Mechanical, Mining and Metallurgical Engineering. The various tertiary institutions that participated in this research are shown in Tables 1.1. Apart from industry partners, other indirect stakeholders included the Government of Zimbabwe through the Ministry of Higher and Tertiary Education, Innovation, Science and Technology Development, regulatory bodies such as the Engineering Council of Zimbabwe and the Postal and Telecommunications Regulatory Authority of Zimbabwe and the Zimbabwe Institution of Engineers as a professional body. Although most of the companies were based in Zimbabwe, at least each of the Table 1.1  EEEP and HEP SSA collaborating institutions in Southern Africa Name University of Zimbabwe Chinhoyi University of Technology Harare Institute of Technology National University of Science and Technology University of Botswana Universidade Eduardo Mondlane Namibia University of Science and Technology University of Johannesburg University of Leicester

Location Harare Chinhoyi Harare Bulawayo Gaborone Maputo Windhoek Johannesburg Leicester

Country Zimbabwe Zimbabwe Zimbabwe Zimbabwe Botswana Mozambique Namibia South Africa United Kingdom

Status Hub Spoke Spoke Spoke Spoke Spoke Spoke Spoke UK Partner

12

1 Introduction

Table 1.2  Case study companies in Southern Africa Company Craster Engineers Adam Bede

Location Harare, Zimbabwe Harare, Zimbabwe

Masimba Holdings Econet Zimplats PPC SINET Africa

Harare, Zimbabwe Harare, Zimbabwe Selous, Zimbabwe Bulawayo, Zimbabwe Harare, Zimbabwe

Design Team Consultants Petroline Zim Chloride Zimbabwe Turnall Holdings MikroDev Southern Africa Virgo Energy Investments Electricidade de Moçambique

Harare, Zimbabwe Harare, Zimbabwe Harare, Zimbabwe Bulawayo, Zimbabwe Johannesburg, South Africa Windhoek, Namibia Maputo, Mozambique

Business Foundry and General Engineering Timber Processing and Furniture Manufacturing Civil and Construction Engineering Telecommunications Engineering Mining and Processing of Platinum Manufacturing and Processing Renewable Energy and Environmental Monitoring Civil Engineering Consultants Fuels and Energy Battery Manufacturing Asbestos Products Manufacturing Mechanical Engineering Technology Renewable Energy Power Plant

collaborating countries had one industry partner where engineering academics from those institutions were seconded, as shown in Table 1.2. The work utilised a systemic philosophy and systems thinking methodology of reductionism, synthesis and mapping (Senge 2006; Borrego et  al. 2015) through detailed work studies and data collected during secondments and attachments at the various companies. The secondments and to some extent student attachments were used to model operations at the companies to create optimised layouts and process flows as a means to demonstrate the contribution that academia could make to resolve industry problems under the broad problem-based learning initiatives. In addition, collaborative research and knowledge sharing workshops and conferences were also held between academia and industry partners, the outcomes of which formed the foundation for the systems thinking models. The various projects carried out at the respective companies as well as structured and organised interviews were also used as feeders to verify and validate the models created.

1.8  Significance and Contributions to Knowledge As demonstrated throughout the book, the work focussed on the industrial evolution and the rapid changes in technology driven by appropriate engineering skills and training coupled with relevant policies for human resources development. The development of systems thinking sub-models that were integrated into the novel universal model were done in order to ensure continuity of noble initiatives such as

1.9  Summary and Outline of the Book

13

NUSESA, EEEP and HEP SSA both in building capacity and sustaining the activities beyond the finite but grateful sponsorship from cooperating partners and aid agencies. The integration of the sub-models into the universal model, upon which this work was hypothesised, was done in such a way as to demonstrate that the success or failure of one aspect was dependent on the other and ultimately the need for industry to work closely with academia. Systems thinking provided the conceptual frameworks that made use of different theories and techniques to resolve complex problems (Behl and Ferreira 2014). The incorporation of the systems thinking approach in deciphering elements within and outside the boundaries of the universal model was a new phenomenon that was expected to contribute to research and knowledge through provision of solutions to improve productivity and capacity utilisation at engineering and manufacturing companies as demonstrated, verified and validated at the various industry partners in this work. The ultimate objective of the synchronisation of the sub-­ models into a universal model was with a thrust and aim to get industry to execute its Research and Development activities through academia, while at the same time, academia needed to pursue industry-based projects. There are several benefits anticipated from utilising the universal model, particularly in industrialising countries with minimal financial capacity to cope with the rapid changes in technology and engineering skills required to drive the technology. Some of these benefits include but are not limited to: • • • • • • • •

Access to modern equipment and technology by engineering academics Provision of solutions to industry challenges by engineering academics Continuous professional development of engineers and academics Coping with the effects of global competition and technology changes Boosting capacity utilisation, productivity and efficiency for industry Optimisation of process flows and factory layouts Capacity building, self-sustenance and sustainability of operations Ultimate bridging of the gap between industry and academia

1.9  Summary and Outline of the Book The building of the systems thinking sub-models, which were then integrated to a universal model, demonstrated the impact and influence of such initiatives on engineering education and training as well as the application of those skills in driving industry in this era of dynamic trends in technology and the industrial revolutions, thus bridging the gap between industry and academia. The philosophy and thrust for this book are anchored on the overall hypothesis that the acquisition of engineering skills in academia must be directly linked to the application of those engineering skills in industry to maintain global competitiveness and cope with the rapid changes in technology and the industrial transformations. The book comprises 14 Chapters as follows: 1. Introduction. Presents an introductory background to the work that started in 2012, drawing from initiatives that had been done earlier and builds on this to

14

1 Introduction

justify the need to model solutions to complex problems using systems thinking through collaborations of tertiary institutions and industry players in Southern Africa. The chapter also contains the statement of the problem, the synopsis and scope of the work, aims and objectives and a summary of how they were accomplished and summarises and anticipates the contributions of this work to research and knowledge. 2. Industrialisation and Technology Dynamics: Recent Research Trends. Provides an overview of the various transformations that industry has gone through since the steam engine and how these transformations have impacted on the acquisition of skills at tertiary institutions and their applications in industry. The chapter also provides an insight on what to expect from the rapid changes in technology and transformations. 3. Systems Thinking Research: Adapting for Engineering Change Management. The methodology for the research, ultimately presented in this book, is based on systemic theory and systems thinking. The chapter outlines the underlying principles and how systems can be broken into elements and built up again to resolve complex problems emanating from different aspects that may not necessarily be related but are interconnected. This chapter formed the foundation for the development of systems thinking sub-models that were later integrated to form the universal model to bridge the gap between industry and academia. 4. Academia and Industry Collaborations: A Research and Professional Perspective. The ultimate objective for the entire book is to bring industry closer to academia. This chapter focusses on the collaborations between various tertiary institutions and industry partners in Southern Africa. This also includes outcomes and impact of the collaborations and the contributions made by both parties to the success of bridging the gap between industry and academia and how these fed into the systems thinking sub-models. 5. Problem- and Industry-Based Learning: Research, Theory and Practice. Using the secondment of engineering academics and to a limited extent student attachments to industry, this chapter outlines the various activities carried out by the 2 groups in so far as to demonstrate the importance and impact of problem-­ based learning coupled with industry-based learning and how engineers were expected to respond to the demands of the fourth Industrial Revolution and Sustainable Development Goals (SDGs). 6. Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results. Apart from the general secondments and attachments, various projects were also carried out by engineering academics on secondment and these were broadly for modelling, simulating and optimising company operations. The results obtained from these projects were used to demonstrate how engineering academics can contribute to solving industry problems by the provision of solutions to improve capacity utilisation, productivity and efficiency, all aimed at demonstrating the impact of utilising academia in industry in exchange for access to modern equipment. The chapter consists of the details of five selected case studies.

1.9  Summary and Outline of the Book

15

7. Capacity Building and Sustainability: Research Findings and Recommendations. One of the ultimate aims and deliverables for this book is to build capacity both for academia (acquisition of skills) and industry (application of the skills). This was demonstrated through the various interventions by both industry and academia, such as through provision of Professorial Chairs by industry and continuous professional development of practicing engineers and how these impacted on the relationship between industry and academia. This chapter mainly consists of the research findings derived from interactive interviews, observations and surveys carried out during the secondments. 8. Access to Modern Technology: Smart Partnerships for Research and Practice. Apart from engineering academics accessing modern equipment in industry through secondments, this chapter also looks at smart procurement, use and maintenance of engineering equipment at tertiary institutions through a variation of the Build-Operate-Transfer phenomenon and how this can be employed between industry and academia, thereby bringing both parties closer. Based on the interactions and collaborations with industry during the period 2011–2020, this chapter also details how some of the tertiary institutions in the regional research and partnership acquired engineering equipment from industry partners. 9. Coopetition and Virtual Collaborations: Global Competitiveness in Research and Practice. The philosophy of coopetition (competition and cooperation) is not only applicable to industry but can also be extended to academia. This chapter focusses on the application of the principle to collaborations between tertiary institutions and also for partnerships with industry. Ultimately, the chapter aims at demonstrating how partnerships among institutions and between institutions and industry can help to boost their fortunes and thus bring industry closer to academia. The chapter also looks at challenges brought on by COVID-19 and how virtual collaborations can help academia to cope with the effects in order to sustain operations in difficult times. 10. Incubation and Technology Parks: Recent Trends, Research and Approaches. Drawing from experiences and hence partnerships with institutions from the industrialised world, this chapter demonstrates how tertiary institutions can promote their innovations through innovation hubs that have been developed and how the extension of these to technology and industrial parks can help in commercialising promising research and products through working in close partnership with industry. 11. Commercialisation and Industrialisation: Research Prognosis for Academia Entrepreneurships. The ultimate objective for bridging the gap between academia and industry is to ensure industry are supplied with appropriate solutions and innovations to drive and manage the dynamic nature of the fourth Industrial Revolution and beyond. This can be achieved by the provision of innovative ideas that can also be translated to business enterprises. This chapter focusses on how engineering academics can start up or spin off companies from their projects. The chapter also provides guidelines for commercialisation policies

16

1 Introduction

and intellectual property rights as derived from collaborating institutions and countries within Southern Africa. 12. Modelling the “Bridge”: Research Verification and Validation. Having considered the various aspects covered from Chaps. 2, 3, 4, 5, 6, 7, 8, 9, 10 and 11, these were then synthesised into sub-models focussing on Equipment and Technology, Engineering Skills Development, Problem- and Industry-Based Learning, Industrialisation and Innovations, Coopetition, Commercialisation, Centres of Excellence and Doctoral Training Centres. The chapter also looked at how each of the sub-models were integrated to formulate the universal model that was verified and validated before being used as a bridge between industry and academia. 1 3. Challenges and Opportunities: Discussion and Predictions from Research Findings. The various problems and opportunities outlined from Chaps. 2, 3, 4, 5, 6, 7, 8, 9, 10 and 11 were assembled in this chapter to provide a platform for the readers of this book to explore other avenues by either providing solutions to the challenges or taking advantage of the opportunities availed. The chapter also details results and discussion from the research, particularly from the bridge model in Chap. 12. 14. Conclusions: Consolidated Research Findings and Recommendations. Based on the results and discussion provided in Chap. 13, this chapter provides a summary and overview of the work and how the aims and objectives are met, contributions to knowledge, impact on the relationship between industry and academia and applications of the universal model, limitations and recommendations for future work to enhance the aim of bridging the gap between industry and academia.

References Afonja, A. A., Sraku-Lartey, K., & Oni, A. A. (2005). Engineering education for industrial development. Case studies of Nigeria, Ghana and Zimbabwe. Nairobi: African Technology Policy Study Network. Ahuja, I. P. S., & Khamba, J. S. (2008). Strategies and success factors for overcoming challenges in TPM implementation in Indian manufacturing industry. Journal of Quality in Maintenance Engineering, 14(2), 123–147. Aisen, A., & Veiga, F. J. (2013). How does political instability affect economic growth?. European Journal of Political Economy, 29(2013), 51–167. Allais, R., & Gobert, J. (2016). A multidisciplinary method for sustainability assessment of PSS: Challenges and developments. CIRP Journal of Manufacturing Science and Technology, 15, 56–64. Bakrania, S., & Lucas, B. (2009). The impact of the financial crisis on conflict and state fragility in Sub-Saharan Africa. GSDRC Applied Knowledge Series. Available: http://www.gsdrc.org/go/ emerging-­issues#crisis. Accessed 24 Mar 2016. Behl, D. V., & Ferreira, S. (2014). Systems thinking: An analysis of key factors and relationships. Procedia Computer Science, 36(2014), 104–109. Borrego, M., Foster, M. J., & Froyd, J. E. (2015). What is the state of the art of systematic review in Engineering Education? Journal of Engineering Education, 104(2), 212–242.

References

17

Broadbent, O., & McCann, E. (2016). Effective industrial engagement in engineering education – A good practice guide, London: Royal Academy of Engineering. ISBN: 978-1-909327-14-6. Bubou, G. M., Offor, I. T., & Bappa, A. S. (2017). Why research-informed teaching in engineering education? A review of the evidence. European Journal of Engineering Education, 42(3), 323–335. Bussiere, M., Saxena, S. C., & Tovar, C. E. (2012). Chronicle of currency collapses: Reexamining the effects on output. Journal of International Money and Finance, 31, 680–708. Gadzikwa, E. C. (2013). The future of the manufacturing sector in Zimbabwe. Institute of Chartered Accountants of Zimbabwe Congress, 18–20 July 2013, Victoria Falls. Available: https://www. icaz.org.zw/iMISDocs/manufacture.pdf. Accessed 8 April 2017. Goodsir, S., Murray, M., Jowitt, P. (2009). Engineering capability in Rwanda. Final project report. Edinburgh: Scottish Institute of Sustainable Technology (SISTECH) & UNESCO. Government of Zimbabwe. (2018). National Critical Skills Audit report. Harare: Government of Zimbabwe Printers. 2018. Available: https://safrap.files.wordpress.com/2018/12/2018-­ zimbabwe-­nationalcritical-­skills-­audit-­report.pdf. Accessed 22 Oct 2019. Harrison, M. (2012). Jobs and growth: The importance of engineering skills to the UK economy. London: Royal Academy of Engineering. ISBN: 1-903496-92-6, Available: http://www.raeng. org.uk/publications/reports/jobs-­and-­growth. Accessed: 18 July 2016. Hove, M. (2012). The debates and impact of sanctions: The Zimbabwean experience. International Journal of Business and Social Science, 3(5), 72–84. ICE (Institution of Civil Engineers) and GDC (Global Development Consultancy). (2002a). Report on the development of the engineering profession in Malawi. London: ICE and GDC. ICE (Institution of Civil Engineers) and GDC (Global Development Consultancy). (2002b). Report on the Development of the Engineering Profession in Mozambique. London: ICE and GDC. ICE (Institution of Civil Engineers) and GDC (Global Development Consultancy). (2002c). Report on the Development of the Engineering Profession in Tanzania. London: ICE and GDC. Ju, H. (2012). Design a training and maintenance system based on code identification. IERI Procedia, 1(2012), 155–159. Kramarenko, V., Engstrom, L., Verdier, G., Fernandez, G., Oppers, S. E., Hughes, R., McHugh, J., & Coats, W., (2010). Zimbabwe: challenges and policy options after hyperinflation. Washington: International Monetary Fund. ISBN 978-1-58906-997-8. Lawless, A. (2007). Numbers and needs in  local government: Civil engineering  – The critical profession for service delivery. Johannesburg: South African Institute of Civil Engineering (SAICE). Lindgren, E.  S. (2001). Sida’s support to Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) Final Evaluation Report. Stockholm, Sweden: Swedish International Development Cooperation Agency (Sida). ISBN: 91-586-8824-2. Lucas, B., Hanson, J., & Claxton, G. (2014). Thinking like an engineer: Implications for the education system. London, UK: Royal Academy of Engineering. ISBN: 978-1-909327-08-5. Macauhub. (2013). Mozambique is 2nd largest recipient of public aid from Portugal. Available: http://www.macauhub.com.mo/en/2013/01/17/mozambique-­i s-­2 nd-­l argest-­r ecipient-­o f-­ public-­aidfrom-­portugal/. Accessed 23 April 2020. Makochekanwa, A. (2016). Zimbabwe to introduce Zimbabwe Bond Notes: reactions and perceptions of economic agents within the first seven days after the announcement. Munich Personal RePEc Archive, MPRA paper no. 71695, Munich. Available: https://mpra.ub.uni-­muenchen. de/71695/. Accessed 8 April 2017. Mangudya, J. (2016). Measures to deal with cash shortages and simultaneously stabilizing and stimulating the economy. Reserve Bank of Zimbabwe Policy Statement, Harare. Available: http://www.rbz.co.zw/assets/press-­s tatement%2D%2D-­m easures-­t o-­d eal-­w ith-­c ash-­ shortages%2D%2D-­04-­may-­2016.pdf. Accessed 7 April 2017. Martinez, V., Bastl, M., Kingston, J., & Evans, S. (2010). Challenges in transforming manufacturing organizations into product-service providers. Journal of Manufacturing Technology Management, 21(4), 449–469.

18

1 Introduction

Matthews, P., Ryan-Collins, L., Wells, J., Sillem, H., & Wright, H. (2012). Engineers for Africa: Identifying engineering capacity needs in Sub-Saharan Africa, analysis of stakeholder interviews. London: Royal Academy of Engineering. ISBN: 1-903496-91-8. Monyau, M.  M., & Bandara, A. (2017). Zimbabwe 2017. African Economic Outlook. Abidjan, African Development Bank. Available: www.africaneconomicoutlook.org. Accessed 4 Feb 2018. Munangagwa, C. L. (2011). The economic collapse of Zimbabwe. Gettysburg Economic Review, 3(1), 110–129. Murangwa, S. I., & Njaya, T. (2016). The effects of Statutory Instrument 64 of 2016 on clearing agents based at Beitbridge Border Post in Zimbabwe. International Journal of Business and Management Invention, 5(11), 45–49. Murangwa, S.  I., & Njaya, T. (2017). An evaluation of the effects of Statutory Instrument 64 of 2016 on Zimbabwe’s neighbours. International Journal of Management and Commerce Innovations, 5(1), 1–9. Mwamila, B. L. M., & Thulstrup, E. W. (Eds). (2001). Engineering and technology for sustainable development – Research, education and development. In Proceedings of a Regional Meeting, Bagamoyo, Tanzania, October 17–21. RAEng (Royal Academy of Engineering). (2017a). Enriching Engineering Education Programme (EEEP). Available: https://www.raeng.org.uk/publications/other/enriching-­engineering-­ education-­programme. Royal Academy of Engineering. Accessed 20 Mar 2018. RAEng (Royal Academy of Engineering). (2017b). Higher Education Partnerships for Sub Saharan Africa (HEP SSA). London: Royal Academy of Engineering. Available: https://www. raeng.org.uk/RAE/media/Grantapplications-­and-­guidelines/HEP%20SSA/Higher-­Education-­ Partnershipin-­sub-­Saharan-­Africa-­(HEP-­SSA)-­Guidance-­Notes.pdf. Accessed 20 Oct 2019. SADC. (2014). Integrated paper on recent economic developments in the Southern African Development Community. Central Bank of Lesotho. Available, https://www.sadcbankers. org/Lists/News%20and%20Publications/Attachments/195/Integrated%20Paper%20-­%20 Aug%202014%20Final.pdf. Accessed 8 Mar 2017. Senge, P. (2006). The fifth discipline: The art and practice of the learning organization. London: Random House Business Books. ISBN: 9781905211203. Uhly, K. M., Visser, L. M., & Zippel, K. S. (2017). Gendered patterns in international research collaborations in academia. Studies in Higher Education, 42(4), 760–782. UNESCO. (2010). Engineering: Issues, challenges and opportunities for development. Paris: UNESCO Publishing. ISBN: 978-92-3-104156-3. World Bank. (2010). Reform and regional integration of professional services in East Africa: Time for Action. World bank report No. 57672-AFR.  Washington: World Bank. Available: http://siteresources.worldbank.org/INTAFRREGTOPTRADE/Resources/ NEWReformProfessionaServicesEAC Report.pdf Zimbabwe Revenue Authority (ZIMRA). (2017). Statutory Instrument 64. In Value Added Tax Chapter 23:12, pp. 447–448. Harare, Zimbabwe Government Printers. Zimstat. (2014). Balance of payment and national accounts. In Facts and Figures 2014, pp 10–12. Harare, Zimbabwe: Zimbabwe National Statistics Agency (Zimstat) Accessed 16 June 2017. http://www.zimstat.co.zw/sites/default/files/img/publications/Other/FACT_2014.pdf Zinyemba, R. (Ed.). (2010). Academia and the dynamics of transformative leadership: The experience of the University of Zimbabwe in the first decade after Zimbabwe’s Independence (1981-1992). Harare: University of Zimbabwe Publications.

Chapter 2

Industrialisation and Technology Dynamics: Recent Research Trends

Abstract  Industrial operations have evolved through massive transformations and in recent years, the rate of change has been so rapid, equally requiring rapid transformations in the engineering education system. This chapter focusses on the various industrial transformations, particularly the current Industry 4.0, its impact and implications on the education and training of engineering personnel. The increased interconnections between the various facets of engineering processes and training give rise to complexities, hence the need to decipher these in a systems thinking approach in order to comprehend the behaviour and use them ultimately to narrow the gap between industry and academia. The increasing complexities in industrial systems and their interconnections require an integrated and systemic approach, particularly in the training and acquisition of appropriate skills required to drive industry. This chapter also focusses on how the engineering education systems and skills acquisition have responded to the various transformations with a special focus on industrialising countries. Keywords  Academia transformations · Automation · Creativity · Innovation · Engineering training and policies · Industrial revolutions · Industrialisation · Integration · Online learning · Productivity · Technology dynamics

2.1  Introduction The Industrial Revolution (IR) and the subsequent series of such transformations date back to the eighteenth century where the first Industrial Revolution was driven by the steam engine (Ayres 1990). The transformations, which were mainly in Europe and the USA, included but were not limited to the progression from manual

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_2

19

20

2  Industrialisation and Technology Dynamics: Recent Research Trends

production to simple machines and also included the introduction and increasing use of steam and water power, mechanisation of chemical manufacturing and ferrous processing and production, dominated by the textile industry in terms of capital expenditure, employment and value addition (Ayres 1990). The second Industrial Revolution, which was subsequently referred to as the Technological Revolution, occurred in the late nineteenth and early twentieth centuries, and it was an era of rapid standardisation and industrialisation (Mohajan 2020). While there were many overlaps with the first, particularly in innovations in manufacturing, the Technological Revolution saw the refinement of the machine tool industry and new production methods for manufacturing interchangeable parts. This phase was also referred to as mass production through assembly lines and the use of electricity to speed up processing. The need for rapid production, efficiency and productivity saw the introduction of computers, robotics and automation of assembly lines in the Technological Revolution (second Industrial Revolution). The Digital Revolution (third Industrial Revolution) embraced the use of technology not only in the fast production of goods and services but the same digital devices have been employed to control and monitor production. Increasingly, the use of robotics and automation in manufacturing and assembly lines saw the increased number of gadgets and machine tools interconnected to form cyber physical systems in the twenty-first century, and this has now become known as the fourth Industrial Revolution. Different parts of the world have entered the fourth Industrial Revolution at different rates and times, industrialised countries being fully in it while some industrialising countries are still battling to transform from the earlier revolutions (Zunino et al. 2020). All countries have to be competitive at the global level and in order to meet rapidly changing customer requirements, companies have to also deal with an increasing need for tailor-making products for customers (Zunino et al. 2020). This must be accomplished in the shortest lead time possible in order to remain in business otherwise the market share may dwindle and be taken over by other competitive players. While these changes have happened at a rapid pace, the same has occurred in academia and research and development where the technology to drive machine tools are developed. In order to remain competitive, some production companies have adopted different strategies and so have academic institutions in order to remain in tandem with the changes. Such strategies include Internet of Things (IoT), big data analytics, machine learning and robotics (Atzori et al. 2010). This translated to a paradigm shift to intelligent systems to cope with the rapid changes. The biggest challenge for industrialising countries is the ability to cope with the new technology, in terms of acquisition and application of skills to operate the modern equipment and ultimately drive industry.

2.2  Industrial Revolutions

21

2.2  Industrial Revolutions Industrial revolutions and the rapid changes in engineering, science, and technology have had a significant impact on all facets of life, from social, health, education and production of goods and services. These have been mainly driven by research and development in engineering, science and technology, an area that is generally between academia (education) and industry (production). Figure 2.1 shows a depiction of the successive four industrial revolutions over four centuries. Evidently, the first and second transformations, the steam engine, mass production and assembly lines were the driving forces for the successive revolutions that occurred thereafter. Progressively, the use of the micro-computer and issue of control became central in order to improve production.

2.2.1  Origins and Transformations in Industry Although the term ‘Industrial Revolution’ was first used by the French, it has been credited to and popularised by the British following immense economic development and boom in the eighteenth century (Nuvolari 2019). Since many of the drivers for the transformations were technological, most innovations and inventions at that time originated from the United Kingdom. Some of the major impacts of the various industrial revolutions were on the quality of life, which significantly improved due to the rise in wealth and incomes (Koc and Teker 2019), increased production

Fig. 2.1  Successive stages of the Industrial Revolutions

22

2  Industrialisation and Technology Dynamics: Recent Research Trends

capacities and competitiveness, evidenced by the gradual rise of the GDP per capita of the countries at the epicentres of the industrial revolutions (Zunino et al. 2020) and a boom in opportunities for research and development (Penprase 2018). However, with  these transformations and changes in the economic landscapes of countries and manufacturing companies, many challenges were  encountered but these created opportunities for the engineering education sector (Fomunyam 2019), the focus and purpose of this book. The advances in manufacturing technology as depicted in Fig. 2.1 also saw the widespread development of telecommunications technology, emergence of rail and road networks, equitable distribution of water and power supplies and general widespread adoption of technological systems, with increasing integration through the various stages. This also presented some challenges such as general migration of people from one place to another, culminating in the current wave of globalisation. While the mobility of professionals such as engineers presented excellent opportunities for collaboration and research, it also created challenges such as the spread of diseases like the Spanish influenza (Karlsson et  al. 2013) and lately COVID-19 (World Bank 2020).

2.2.2  Transformations in Other Sectors While there were these developments in the industrial sector, there were equally some changes and developments in other sectors as the industrial sector depended on other sectors for its inputs and outputs. These included the agricultural sector which provided the cotton for the textile industry as well as provision of raw materials for food production and processing factories, the social and economic sectors that saw the increased employment of people in industry away from agriculture and a wider distribution of wealth, as well as increased international markets and trade. There were also changes in the political arena, reflecting shifts in world economic power depending on which country was ahead in the transformations, coupled with social changes and the growth of infrastructure and cities, mobility of professionals around the world, as well as transformations and fusion of cultures (Duignan 2019). The resultant effect was that semi-skilled or skilled workers acquired new and broader skills as a result of the challenges they encountered in production as part of their knowledge acquisition post education. In addition to the new skills, they also became masters of their trades and in some instances interchangeably with other machine operators in different departments. While this broadened their skills, there was also a psychological challenge to continuously develop themselves academically or change and still have confidence in the ability to use available machine tools and resources (Duignan 2019).

2.3  Technology Dynamics and Complexities

23

2.3  Technology Dynamics and Complexities 2.3.1  Challenges and Opportunities The various transformations through the industrial revolution stages as shown in Fig. 2.1 have presented many challenges and opportunities for research and development through the need to upskill professionals in most of the technology driven sectors of economies around the world (UNESCO 2010). The challenges and opportunities have not only been dynamic but complex as well, to the extent that industries have strongly impressed on tertiary institutions to concentrate and focus on producing relevant graduates who are employable and skilled enough to address these issues especially as the facets of the industrial revolutions get increasingly intertwined. The focus for the future should therefore be on systems thinkers and human resources capable of developing and driving the technologies and equipment in the dynamically changing societies’ landscape. According to the same UNESCO (2010) report, while the challenges and opportunities varied in nature and severity depending on whether a country was industrialised or not, the focus should be on addressing skills shortages, mismatches, deficiencies in educational systems as well as regular curriculum review in tertiary institutions (Nguyen and Pudlowski 2007). This was coupled by the need to synergise formal links between industry and academia (Gandhi 2014; Broadbent and McCann 2016). A critical assessment by Global Manufacturing (2014), expanded the key issues to include regulatory policies, maintenance, productivity, product development, environmental and health issues, highlighting the need for a systems thinking approach. Despite the opportunities created for research by these challenges and complexities in industrialisation and the technology drivers, most of this has been concentrated in the industrialised world and the same solutions may not be applicable in the industrialising world, especially where there is still predominant use of conventional machine tools. The degrees of complexities and the level of industrialisation differed from one country to another and thus appropriate and tailor-made solutions were an absolute necessity to avoid ‘creating a square plug for a round hole’. While the challenges that came about as a result of the global financial crisis of 2008 (Bakrania and Lucas 2009) had different impacts in different parts of the world, in general, they forced the industrialised world to be competitive in order to secure global markets and for the industrialising world, a deeper sense of reorganisation and retooling was necessary to address the low capacity utilisation and productivity. For the work in this book, these challenges have been broadly classified under Technology, Training and Policies, the basis on which the systems thinking sub-models and the eventual universal model were developed to improve the linkages between academia, through enhancing the quality of engineering education and industry through boosting productivity and capacity utilisation.

24

2  Industrialisation and Technology Dynamics: Recent Research Trends

2.3.2  Effects on Industrialising Countries Undoubtedly, chief among the challenges faced by industrialising countries, as far as the industrial transformations were concerned, was the failure to access modern equipment and technology to match counterparts in the industrialised world. This challenge affected both industry and academia. However, many companies in Southern Africa were multi-nationals, that is, owned by parent companies in the industrialised world; hence, they had fairly modern and sophisticated equipment, but their major challenge was the availability of the necessary human resources and skills from local tertiary institutions mandated with the task to produce the requisite skills (Abu-Goukh et al. 2013). Despite the ability by the multi-national companies to invest in or acquire modern equipment from their parent companies, this challenge has been compounded by the dynamic and rapid changes in technology over the years, presenting another challenge of cost for further training engineering graduates (Ju 2012), whereas this could have been addressed while they were still students at tertiary institutions. The majority of the other regional companies were not multi-nationals and thus relied heavily on either importing machine tools and their spare parts using scarce foreign exchange reserves or they depended heavily on foreign aid for their survival (OECD 2016). Apart from limited capacities, these companies have also relied heavily on foreign expertise and skills from the suppliers of the equipment, the OEMs to maintain the ever-increasing complex machine tools or the seconding of their engineers abroad for training, both of which were costly. Unfortunately, due to global competition and the need to keep in tandem with the industrial revolutions, OEMs were sometimes forced to modify their machine tools and the software that drove them, thus forcing companies to endure the additional costs of upgrading or retooling (Martinez et al. 2010). The failure by industrialising countries to invest in new technology due to limited capacities, financial and skills incapacitation, forced many companies in industrialising countries to play ‘underdogs’ in global markets under the increasing complexities of industrialisation (Lwakabamba 2011). This invariably pushed these companies to be recipients of goods and services produced elsewhere and thus fuelled the consumptive societies where balance of payments was skewed towards imports. This challenge called for the adoption of responsive and appropriate integrated management systems that are flexible, adaptive and agile (Garg and Deshmukh 2010). According to an assessment carried out in Rwanda, the failure to access modern equipment and technology for the training of engineers at different levels inhibited the growth and development in most countries in Sub-­ Saharan Africa (Lwakabamba 2011), a mirror reflection of similar research findings carried out by Matthews et al. (2012) in East Africa.

2.3  Technology Dynamics and Complexities

25

2.3.3  Techniques for Productivity in Industry For all engineering disciplines, engineering design always usually ended up in the manufacture of products, whether through job or mass production. A wide range of techniques have been developed over the years and in conjunction with the various stages of the industrial revolutions, in order to improve productivity, efficiency and to some extent capacity utilisation. These techniques ranged from Design for Manufacture and Assembly (DFMA), popularised by Boothroyd et al. (2011) for the economical manufacture of products by reducing the number of parts that made up a product at minimal cost. Concurrent Engineering (CE), frequently referred to as Simultaneous Engineering (SE), has been adopted by engineers as a way of designing products and developing them in parallel to the developments and continuous improvements rather than carrying out the processes as fixed stages (Meybodi 2013), that way, reducing the lead time for developing the product in order to get it to the market faster, hence improved productivity and reduced costs. The progression in the industrial revolutions saw the emergence of digitalisation in the Third Industrial Revolution. This became useful for controlling production processes through some central computer systems, giving birth to yet another technique of Flexible Manufacturing System (FMS) in which the entire production system can be configured in such a way that all workstations can be linked, controlled and monitored from a central point. The inherent flexibility in an FMS was in the ability to adapt to changes in the type and amount of products being manufactured (Marques et al. 2013). FMSs are usually embedded with well-established Computer Aided Design (CAD) and Computer Aided Manufacture (CAM) systems. Aided by various computer modelling and simulation packages, these techniques are still readily in use today. However, the challenge in meeting the skills required to develop similar software or make use of off-the-shelf packages has been the continual updates, which required engineering personnel to be continually trained whenever a new version was released. Some of the modelling and simulation software used at the tertiary institutions in this research included Arena, WITNESS, ASPEN, STELLA, SolidWorks and Abacus, all tailored for certain and specific tasks in engineering design and manufacture. In recent years, upgrades of such software tools have been effected at a much faster pace as was the case 20 or so years ago (Basoglu et al. 2009). These changes were in response to the rapid and dynamic changes in technology, invariably requiring regular and continuous professional development for practising engineers in industry. This is another cost centre that industries have to create, but it can be minimised tremendously if tertiary institutions formulated ideal and formal links with industry in their regions. Engagements of the various tertiary institutions (Table 1.1) with the industry partners (Table 1.2) in the region, especially those in manufacturing or processing, revealed one common challenge of the backtracking of process flows in the manufacture or processing of products, which often resulted in long distances traversed by parts during manufacture or assembly. This quite simply translated to longer

26

2  Industrialisation and Technology Dynamics: Recent Research Trends

distances for the more complex products as more permutations and processes were required. This required process flow modelling and simulation skills to optimise the production processes, arrangements and layout of the factories and workstations within them. What was evident from the findings was the unavailability of the required skills, hence the involvement of the engineering academics to resolve these challenges, and the details are contained in Chaps. 5 and 6. Quite often, when companies invest in or develop new systems to run their plants, this usually ends up in creating challenges for the companies due to lack of skills to get the new systems or new machine tools off the ground (Martinez et al. 2010). Synergies or partnerships between academia and industry can help to resolve such challenges in order to avoid importing special skills to help the companies off the ground. Such synergies and complexities may not be executable in a simple way but required integrative and systems thinking approaches to characterise and develop contracts that both academia and industry can benefit and feel a part of (Arnold and Wade 2015), apart from developing programmes and systems for both parties to participate fully and equally. Typical systems such as these were often characterised by technical complexities and thus required a high degree of competence in terms of skills to cope with the rapid and dynamic changes. These complexities, coupled with the rapid developments in the industrial revolutions required highly skilled engineers, particularly in industrialising countries where conventional machine tools and traditional methods of engineering design and manufacture were still employed in conjunction with a few modern pieces of equipment and technology (El-Khasawneh 2012). The use of modern technology and equipment in manufacturing, improved productivity and efficiencies (El-Houssaine et al. 2016), but this can only be achieved by appropriately trained and skilled engineers exposed to and familiar with such technology dynamics and complexities.

2.4  Fourth Industrial Revolution and Engineering Training 2.4.1  Rapid Transformation to Integration Unlike the first three industrial revolutions, the fourth industrial revolution (Industry 4.0 or 4IR) has received so much attention and has been discussed at different fora from technical, social and economic. This has primarily been due to the impact that this particular revolution has had on all aspects of human endeavour and life. As shown in Fig. 2.1, the fourth industrial revolution is distinguishable by its integrated nature in which various tools have been brought together. The fourth Industrial Revolution has been characterised by the rapid changes from one technology to another, accelerated and driven by new innovations fed by research and development. These changes presented potential challenges to society and the way engineers and scientists are trained and equally how the technologies were applied in

2.4  Fourth Industrial Revolution and Engineering Training

27

industry (Faure and Joly 2016). While this technological revolution is aimed at improving productivity and efficiency, thus lowering costs and increasing competitiveness and market share, the consequences can be difficult to cope with, especially in terms of the necessary skills to drive the new technologies. The fourth Industrial Revolution has also resulted in a significant change in cultures and the way people live around the world. According to the World Economic Forum, the rapid changes in the Technological Revolution have resulted in the fusion of the physical, digital and biological aspects of life in a way that the developers sometimes also failed to keep pace with (Schwab 2016). The rate at which the changes have been occurring and the depth to which they have taken developers has inevitably forced professionals to rethink how their companies and countries can develop and add or create value in leaders, policy-makers, educationists and professionals alike. While the first Industrial Revolution was driven by the STEAM engine, skilled professionals forecast that the next industrial revolution, the Digital Ecosystem or Industry 5.0 will also be driven by STEAM although this will not be the thermodynamic steam of the First Industrial Revolution but instead, Science, Technology, Engineering, Arts and Mathematics, the interdisciplinary nature for the future. The STEAM for the future would thus be a blend of all skills as the technologies converge and become more integrated in nature. This would be an opportunity to look beyond just technology but finding ways to not only positively impact on people’s lives but to get everyone involved and be part of the technological changes (Schwab 2016). Table 2.1 is an extract of the attributes for the industrial revolutions as contained in Fig. 2.1, in which both the academic and technological attributes have been included to demonstrate the academic as well as the industrial transformations since the first industrial revolution. Taking cognisance that the first and second industrial revolutions have been overtaken and overridden by the next 2, the focus for this chapter will be on the Digital Revolution and fourth Industrial Revolution as both are still in use one way or the other.

2.4.2  Engineering Education Transformations Engineering education and training in the early industrial revolutions was dominated by apprenticeship training which was mainly characterised by on-the-job training and practice (Vasanthi and Basariya 2019). Tertiary institutions that included polytechnics and universities were still under development but were a necessity to ensure that skilled professionals had transferrable qualifications to make them employable at other companies that may not necessarily be in the same business. Over the years, the apprenticeship training was elevated from the lower National Certificate (NC) and Diploma (ND) to Higher National Diploma (HND) while in parallel engineering education at universities was limited to the traditional disciplines of Civil, Electrical and Mechanical Engineering.

28

2  Industrialisation and Technology Dynamics: Recent Research Trends

Table 2.1  Academic and technological attributes of the Industrial Revolutions Revolution Industry 1.0

Synonym

Academia

Industry

Industrial Revolution

Establishment of Tertiary Institutions Professional Bodies & Institutions Specialisations On the Job Apprenticeships

Steam Engine Mechanisation Hand to Machine Tools

Industry 2.0

Technology Revolution

Apprenticeship Training NC - ND Standard Curricula Engineering Education

19th Century Industry 3.0

Mass Production Assembly Lines Electrical Energy Transportation Telegraph Communications

Digital Revolution

International Curricula Apprenticeship Training NC - HND Accreditation of Qualifications Mobility of Professionals and Academics More Disciplines & Specialisations Globalisation & Integration Internationalisation Scholarships for Industrialising Countries

Telecommunication technologies, Robotics Automation Rapid Production

Cyber-Space

Significant Reduction in Apprenticeships Online and Virtual Learning Multidisciplinary Projects & Learning Systems Thinking Integrated Systems Double Degrees & Double Majors Accumulation & Transfer of Credits Institutional Agreements & Collaboration Interactive Educational Resources Problem & Industry Based Learning

Total Integrated Systems Networks Internet of Things Big Data Analytics Cyber-Physical Systems Automated Production Systems Artificial Neural Networks Robotics Machine Learning Simulations

Digital Ecosystem

Inter-Disciplinary Degrees? Multi-Disciplinary Projects? Systems Thinking Specialists? Scholarships for Innovations?

Autonomous Vehicles? Autonomous & Virtual Factories? Biotechnology?

18th Century

20th Century Industry 4.0

21st Century

Industry 5.0 2030??

The University of Zimbabwe, which had been weaned off as a College of the University of London, saw the first graduates in the three traditional disciplines in 1977. It was not until 1985 that there were additional Departments of Mining and Metallurgical Engineering as well as Land Surveying (Zinyemba 2010), followed by Agricultural Engineering in 1992 and Aeronautical Engineering in 2018. In 2020 and in line with the Government’s Heritage Education 5.0, Faculties and Departments began the task of rebranding to respond to local demands from industry. Universidade Eduardo Mondlane, formerly Estudos Gerais Universitários de Moçambique, was established in 1962 as a degree awarding institution. The University of Johannesburg was established in 2005, an amalgamation of existing institutions, the Rand Afrikaans University, the Technikon Witwatersrand and the Soweto and East Rand campuses of Vista University in 2005. The Namibia University of Science and Technology was established as a full-fledged degree-awarding university in 2015 following the upgrading of the previous Polytechnic of Namibia, which offered a wide range of diplomas including degrees since 1992.

2.4  Fourth Industrial Revolution and Engineering Training

29

In Zimbabwe, the other three institutions in this collaboration and offering engineering education and training are National University of Science and Technology (NUST), established in 1992 to complement programmes offered by the University of Zimbabwe but with a thrust towards science and technology. The Harare Institute of Technology was established as a National Vocational Training Centre in 1988, offering certificates and diplomas to artisans in various fields. In 2005, it was elevated to a degree awarding institution whose main thrust was in producing technologists as a technoprenuerial university. Chinhoyi University of Technology was established in 2001 following the upgrading of Chinhoyi Technical Teachers’ College, which had been established in 1991. The university produces technologists and focusses on mechatronics and production particularly for the agricultural sector. In 2020, all these institutions in Zimbabwe refocussed their curricula to include aspects of industrialisation and innovation.

2.4.3  Parallel Transformations in Industry While these transformations were ongoing in academia (polytechnics and universities), many changes were also occurring in industry. In particular, the transition from the Digital Revolution (third Industrial Revolution) to the Cyber Space (fourth Industrial Revolution) saw the emergence of mobile telecommunications technologies, rapid production in manufacturing through the use of automation and robotics. Some manufacturing plants, particularly in the industrialised world, were left to run continuously without human intervention as was the case with the earlier revolutions. More and more of the systems in industry became integrated and were easily manageable from either Wide Area Networks (WAN) or Local Area Networks (LAN). Big data analytics also emerged in the use of advanced analytical techniques against a backdrop of very large and variable information processing that included structured, semi-structured and unstructured data, coming from different sources and in different sizes (Belaud et al. 2014). Big data analytics in today’s environment can be very useful to uncover or predict behaviour of hidden patterns, little known interconnections or relationships including market forecasts and trends. With the widely available internet access around the world, big data analytics is usually used in conjunction with Internet of Things (IoT), a system of interconnected and usually interrelated digital computer devices and machine tools over a network and used to transfer big data without human or physical presence of human beings (full automation). Such integrated systems have made it possible to carry out simulations to predict the behaviour of systems, including advanced robotics, automated production systems and machine learning (Atzori et al. 2010). The integrated systems also included fully automated CAD and CAM systems.

30

2  Industrialisation and Technology Dynamics: Recent Research Trends

2.5  Impact on Engineering Education and Policies 2.5.1  Polytechnics to Universities Evidently from the foregoing, many universities were established after transforming them from polytechnics or technikons. This was in tandem with developments that were occurring in the UK and other industrialised countries where technical colleges were upgraded to degree awarding institutions (Mohamedbhai 2017). While there were good intentions pioneered by the British in 1992 to convert polytechnics to technical degree awarding universities as a way to provide wider opportunities to socially disadvantaged students, almost 30 years later, the results did not quite yield the intended purpose. As a consequence of the industrial revolutions, industrialised countries such as the UK were moving towards an integrated and service oriented economy. This change therefore required more degreed graduates. Ten years after the British embarked on these transformations, most industrialising countries, particularly those that were former colonies of the UK followed suit. At the dawn of the new millennium, many former polytechnics in Southern Africa were converted to technical universities, initially intended to produce technologists to provide the bridge between engineers and technicians. Equally, a number of either former polytechnics or smaller universities were merged to form bigger universities in order to complement efforts and compete on the international arena in terms of higher education institutions’ rankings. Unfortunately, many of the converted polytechnics were not replaced by additional technical colleges in order to train apprentices, thus leading to a serious skills gap. This had the net effect of reducing the number of artisans and journeymen, who were essentially the technical professionals who actually did the physical work but instead industry was now ‘crowded’ with degreed professionals with very few technicians to supervise. Many professionals, policy-makers and politicians now regard the transformations as erroneous and in fact, as published in The Guardian in 2017, the former Labour Minister, Lord Andrew Adonis felt that ‘the transformations were a mistake’ and actually urged authorities to either restore polytechnics or establish additional ones (Adams 2017). For the efficient operation of industry, engineers and technologists alone cannot manage or cope with developments, hence the importance of polytechnics needed to be given some priority, the desirable ratio being one engineer to every five technicians (Mohamedbhai 2017). Based on information extracted from both tertiary institutions and partnering industry in this collaboration, the general indication was that for every engineer, there was a technologist and one or two artisans/technicians, an indication that the transformations of polytechnics to universities managed to increase the number of engineers but unfortunately reduced the number of much needed artisans and technicians required to carry out the tasks. Ultimately, this implied that fresh graduate engineers and technologists were underemployed, performing the tasks meant for artisans.

2.5  Impact on Engineering Education and Policies

31

2.5.2  Shortages and Mismatch of Skills While the UN revealed that there was a persistent shortage of engineers around the world with 20–50 engineers for a population of 10,000, Sub-Saharan Africa faced an even more daunting situation with only one engineer for the same population count (UNESCO 2010), an even higher number of artisans and journeymen were necessary to provide a supporting service for the engineers and technologists, as well as to manage and run small to medium enterprises, which form a significant number in industrialising countries and thus contributing to the countries’ GDPs. However, policy-makers needed to recognise the technicians in order to remove the myth that they were less important than engineers or technologists. That myth could have been one of the reasons that motivated the transformations of polytechnics to universities. While the conversion of some of the technical colleges to fully fledged universities has been welcomed by many in Southern Africa, the number of universities are still significantly low compared to the industrialised world. Unfortunately, most countries in Southern Africa can ill-afford to establish more universities let alone polytechnics to replace those that were upgraded to universities, due to limitations in financial capacities. Additionally, even if the countries had the capacity, the limiting factor would be the low capacity utilisation at most of the companies such as the industry partners in this collaboration, creating another challenge of unemployment if the graduate numbers are not managed well. This would probably be one of the reasons to resuscitate polytechnics to churn out technicians to create employment in the small to medium enterprises. The resuscitation of polytechnics or creation of new ones to replace those that were upgraded to universities was an absolute must, and this should have been done in line with the recommended UN ratios of about one engineer to about five technicians and so should the enrolment figures be dictated. This should also have been done in line with the Washington, Sydney and Dublin Accords that govern and regulate the operations of engineers, technologists and technicians, respectively, in accordance with the Conceptualise, Design, Implement and Operate (CDIO) principles (Crawley et  al. 2014). Within Southern Africa, Mauritius authorities have successfully reconsidered the policy of transforming polytechnics to universities by reverting to their original status in 2015, the key drivers for this move being increased unemployment by graduate engineers and the shortage of technical skills, which had an adverse effect on their small to medium enterprises (Mohamedbhai 2017). Skills audits that have been carried out in Southern Africa, such as in Zimbabwe, have not only revealed but exposed the high skills deficit (over 90%) in science, engineering and technology (Government of Zimbabwe 2018). This prompted the need for all authorities to reconsider their policies in order to enhance and prioritise practical skills generated at polytechnics. This was one of the motivations for the grant awarded by the Royal Academy of Engineering under the HEP SSA project (2019–2021). In line with this motivation, regular skills audits also needed to be carried out to monitor and control the situation in order to improve the pool of skills.

32

2  Industrialisation and Technology Dynamics: Recent Research Trends

2.5.3  Double Degrees and Double Majors Another major change that has taken place in engineering education and training under the fourth Industrial Revolution was the introduction of double degrees and double majors. This was initiated at some British universities as a way of enhancing students’ options. Double degrees allowed students to pursue two degrees at the same time to enable them to graduate with different undergraduate qualifications, although these were more common at postgraduate or Master’s level. Double degrees increased options, flexibility and opportunities in this ever-increasing dynamic society and unemployment. Studies have shown that, as a result of the fourth Industrial Revolution, what universities were preparing students for employment may not be available after graduation, hence the need to broaden one’s options and opportunities (Gedye et  al. 2004). Double degrees also allowed students to develop expertise in different but interrelated areas such as Engineering and Business, Engineering and Economics, such that in the end, the student was awarded two degrees. Typically, double degrees can be pursued at different institutions under special arrangements. On the other hand, another common route that has been opened up by institutions in response to the fourth Industrial Revolution is that of double majors, which are related but strictly not the same as double degrees. Double majors primarily consist of two majors attached to a single degree that students can pursue as differentiated from two separate degrees. Essentially, a double major is where students earn one degree with two different specialisations such as Bachelor of Science in Engineering specialising in Electrical and Mechanical or Mining and Metallurgy, but all based in the same institution. Double majors also provided the graduate with some flexibility and options to specialise in after completing their studies. Naturally, the number of courses pursued and credit hours required in a double major would be less than those required for a double degree. These concepts are increasingly being accepted as the norm around the world. Previous studies and research carried have revealed that, although employers consider double majors or double degrees as an added advantage to applicants for employment, in terms of wider skills that could prove beneficial to other sections of the company, they were however more interested in the graduates’ skills and results, whether from single or double degrees (Fleming et  al. 2010). While engineering graduates were expected to focus and concentrate in their area of specialisation during training in the first 2–3 years of their employment, a double major or double degree, particularly in areas related to Engineering such as Business or Economics, could see the rapid progression to senior management or leadership positions of the employees with double degrees or majors. The concept of double degrees or double majors is still fairly new in Southern Africa, particularly where double majors can be offered by two different institutions. The network of institutions that was created from the HEP SSA project aimed at getting the partnering institutions to collaborate to the extent of offering double degrees. In line with the institutions collaborating for either double degrees or double majors in response to the demands by the fourth

2.5  Impact on Engineering Education and Policies

33

Industrial Revolution, one of the major effects and changes was the standardisation of engineering curricula. The standardisation was done in such a way that a student can accumulate credits in one institution and transfer these to another institution and that promoted mobility of students among the collaborating institutions. While this practice is common in industrialised countries that subscribe to the Washington, Sydney or Dublin Accords, the practice in Southern Africa is new. Based on information gathered from the collaborating institutions, the major challenge to achieve the mobility of students among the institutions has been the lack of standardised courses, assessments and length of programmes. While this is now acceptable international practice, the other reason for failure to be in sync with institutions from the industrialised world was the failure by regional institutions to accredit their courses internationally and in line with the 3 Accords. Internationalisation and accreditation of degrees by collaborating institutions in this research was one of the main thrusts to ensure that the skills developed among the institutions were not only relevant for the regional industry but were acceptable internationally, in such a way that promoted the mobility of both engineers and students.

2.5.4  Collaborations in Southern Africa With the advent and transition from the third to the fourth Industrial Revolution, there has been increased demand from industry for engineering academics and students to provide relevant solutions to industry problems. Through the collaboration of the 9 tertiary institutions and 14 industry partners, several students have been attached while at least one engineering academic was seconded to each of the companies. The student attachments enabled them exposure to engineering practice. The secondment of engineering academics facilitated access to modern equipment and technology that enabled them to dispatch their lectures confidently and also relevantly. The other two major achievements by both students and staff during the secondments were problem-based learning (PBL) and industry-based learning (IBL), key attributes and requirements for the fourth Industrial Revolution. The secondments and attachments were used as an opportunity to expose and teach students using real-life industry problems as the avenue to raise students’ understanding of theory. All the students attached were also required that they successfully generated their undergraduate projects from the attachments. Engineering academics who were seconded also developed industry-based projects for the other students who could not be accommodated, apart from creating consultancy opportunities with the companies that they were seconded to. All the universities in the collaboration now have a mandatory one-year industrial attachment for students before they write their final examinations. Some of the students were accommodated under the HEP SSA project in addition to the IBL that allowed them an opportunity to be paid an income from the attachment, apart from presenting an entire IBL project as part of their assessment for that year.

34

2  Industrialisation and Technology Dynamics: Recent Research Trends

2.6  Training Challenges and Possible Solutions 2.6.1  Complexities and Uncertainties The fourth Industrial Revolution and the inevitable transition to the fifth Industrial Revolution present several challenges particularly for industrialising countries that are grappling to cope with the rapid and dynamic changes of the earlier revolutions. While it is envisaged to improve or change for the better, the way people live and relate, the complexities required innovative ways in order to cope (Schwab 2016). Additionally, the complexities in these transformations came with a lot of uncertainties that required integrated and comprehensive approaches that also required the participation of all stakeholders, hence the systems thinking approach adopted in this book. Peters (2017) reiterated that, despite the excitement with the transformations in industry, some of the changes were also scary and unimaginative of the consequences, the major challenges being the availability of skills to cope with the changes, thus the need for a paradigm shift and the way engineers were trained to deal with these dynamics. While it was anticipated that incomes were expected to improve, the jobs that were available a few years ago will become extinct, thus requiring the professional engineer to continually be trained even on the job.

2.6.2  From AI to IA Quite a number of tasks that were previously performed by humans will be taken over by robots with the introduction of automation, artificial intelligence (AI) and automation. However, one way of dealing with this challenge will be to regard it as an opportunity for Intelligence Amplification (IA), thus devoting the available skills to development and leave the traditional chores to machines and robots in order to avoid eliminating jobs. However, even so, several jobs and people will be displaced by robotic systems and automation, thus aggravating the investments that would have been made for the training of professionals. The developers of systems should thus focus on creating opportunities and flexibilities to address the impending inequalities in the labour markets. In this regard, the most sought-after and valuable resource in these transformations would be the ability to cope with changes and management of the same. Innovation, entrepreneurship and new ideas will drive countries to the future more than the investment in ordinary training of engineers. The number of investors in new technology and the talent and innovations in engineers must be matched in order to remain in tandem with the dynamic changes (Brynjolfsson et al. 2014). The nurturing of talent and promotion of innovative ideas should be priority for leaders and policy-makers by providing them with the space and resources to incubate and develop the ideas to commercialisation and markets. Digitalisation, big data and internet of things should no longer be a luxury and preserve of researchers but a necessity for all countries to survive in this

2.6  Training Challenges and Possible Solutions

35

ever-­increasing global competitive market. Competition among employees with requisite skills for the fourth Industrial Revolution will be rife, thus requiring tertiary institutions to change their teaching and learning methods (Fomunyam 2019).

2.6.3  Promotion of Creativity and Innovation Apart from the need for highly innovative and talented engineering academics, tertiary institutions will need to be adequately funded to diversify and expand their scope to incubation of ideas and commercialisation of the most promising innovations. Although science and technology parks are predominant at/or in conjunction with tertiary institutions in industrialised countries, the concept has been adopted in Southern Africa with the emergence of innovation hubs and industrial parks at all science and technology universities in Zimbabwe and South Africa. This was a necessity to avoid disruptions in the labour market in such a way that after graduation some students may be ready to roll out their innovations as entrepreneurs. The challenging factor in this regard, especially for industrialising countries, was the capacity to establish the science and technology parks. However, one way would be to consider possibilities of employing the Build-Operate-Transfer phenomenon, whereby industry could invest in such ventures and in turn get research and development solutions provided for their operations through the parks. In addition, tertiary institutions, in collaboration with industry should focus on inculcating a culture of practical solutions and their students’ involvement in working with machine tools through problem and industry-based learning strategies in such a way that the students and academics should actually be able to develop and programme the intelligent machines rather than compete with them. Reformulating the curricula to respond to these demands could be another challenging task for tertiary institutions. The Zimbabwean government through the Ministry of Higher and Tertiary Education, Innovation, Science and Technology Development introduced the concept and thrust towards Education 5.0, which now included Innovation and Industrialisation as additional pillars to Teaching, Research and Community Service. The implementation of this strategy in line with the University of Zimbabwe strategic plan (2019–2025) has not been smooth, mostly because of the fear for change by some of the academics. Some of the fears are understandable challenges, especially with regards to the need for constant upgrades of curricula and risk resentment associated with the fear for loss of jobs. The increased interconnection of devices to daily routines and lives also pose a challenge of fear for cybersecurity. In 2020, there were even fears of the allegation of the connection between 5G networks and the corona virus, a fear that has fortunately been allayed by scientists (Warren 2020). Obviously, however, the increased connection of gadgets to other gadgets and everything else through the Internet of Things is a vulnerability risk for the networks and increases the possibilities of hacking and thus requiring additional training, as well as cost for securing the systems. This is probably why information

36

2  Industrialisation and Technology Dynamics: Recent Research Trends

technology and security of systems has been rated as one of the most wanted jobs for the future (Cicek et al. 2019). In an environment or organisation with such rapid changes and possibly resentment, cases of sabotage by disgruntled employees cannot be ruled out. In this regard, such transformations will need to place emphasis on security and trust in employees as such risks pose another challenge on costs. The ability to process data in this era of dynamic changes in technology and the rate at which it can be accomplished surpasses that of individuals unlike several years ago when mainframes could take several days to process data. In that regard, insuring the company systems from possible risks of invasion or hacking becomes a necessity but a challenge in terms of cost. Due to the changes brought on by the industrial revolutions, where the focus for the earlier ones was standard education, then diversifying to market driven and lately in the fourth Industrial Revolution, very broad skills that are technology driven are now a necessity as more and more of the professions integrate into a fusion of digital, physical and biological systems, creating some complexities in integrated curricula for tertiary institutions (Fomunyam 2019). While innovations were welcome and were the attributes and sought-after skills for the future, they were equally disruptive to engineering education and training as the norm and conventional education has to be redefined. With the emergence of automation, machine learning and genetic engineering, new thrusts and focus on ethics are also problematic for the professional bodies responsible for standardisation and accreditation of curricula. In addition, the robots or machines that are now increasingly becoming autonomous lack the ability and capacity for moral reasoning and ethical values, thus limiting them in making good and rational decision.

2.6.4  Online Learning Resources The fourth Industrial Revolution has also witnessed the emergence of online learning and online conferencing. While this has assisted greatly during the 2019–2020 outbreak of the corona virus world-wide due to restrictions in travel, as well as social distancing to avoid the spread of the virus, this has had the negative effect of the reduction in human interactions and contacts, as well as socialisation. More and more people now spend more time with their gadgets, be it mobile phones, computers, or iPads on social media networks and very little time to socialise even with the family. Gadgets have basically taken over the way people behave unlike a few years ago when socialisation was key. ‘I fear the day that technology will surpass our human interaction. The world will have a generation of idiots’. This is probably a well-known saying attributed to one of the finest scientists that ever lived, Albert Einstein. Whether this is correctly attributed or not, the rate at which people have reduced social interactions by paying more attention to gadgets is alarming and one can only imagine what could happen in the future where human-human interactions will be taken over by human-gadget interactions. Another challenge posed by online education particularly for engineers

2.7 Conclusion

37

is the inability to carry out practical laboratory sessions and actually getting the feel of how machines operate and relate to theory and equations, unlike other professions such as humanities where this can easily be accomplished. Direct contact and face-to-face education is a vital necessity for the science, engineering and technology fields to provide a deeper appreciation of practice, and hence the advocacy and thrusts for this book for problem-based learning, industry-based learning for engineering students and secondment to industry for engineering academics in order to bridge the gap between industry and academia.

2.7  Conclusion This chapter provided an overview of the various transformations that industry has gone through since the steam engine and how these transformations have impacted on the acquisition of skills at tertiary institutions and their applications in industry. The various transformations, especially from the third to the fourth Industrial Revolutions, saw the emergence and increase in integration and multidisciplinary ways of resolving challenges brought on by the rapid and dynamic changes in technology. The complexities in those changes also gave rise to complexities of the increasing interconnectedness of systems. The biggest challenge in this regard was the unavailability of skills to ensure that the systems continued to function. This required a new type of engineer and technician to appropriately respond to the demands of the fourth Industrial Revolution. Many changes have been introduced in the engineering education and training of engineers and technicians who are still required to conform to the CDIO principle under the Washington, Sydney or Dublin Accords. The multidisciplinary nature of the demands has seen the introduction of a new way of engineering education such as the emergence of double degrees or double majors including problem-based and industry-based learning. These changes were obviously costly and have affected the industrialising world due to lack of capacities to invest in both the new technologies or the new way of teaching and learning, thus requiring a holistic approach in which all stakeholders, particularly academia and industry, can work together in order to provide comprehensive solutions. One of the major changes in engineering education was the conversion of polytechnics to universities to increase the number of engineers and technologists. This was due to the general belief that the degreed professionals would readily adapt to and cope with the changes in the industrial revolutions. However, many countries that took this route did not put plans in place to establish more polytechnics to replace those that had been upgraded. This saw a significant reduction in the number of apprenticeships and ultimately the reduction in the number of technicians and thus affected output in production, which saw some companies scaling down. Many tasks that were previously carried out by humans have been taken over by the automation of systems and the use of robots and artificial intelligence.

38

2  Industrialisation and Technology Dynamics: Recent Research Trends

Focus for the future in engineering education systems should be to promote innovations and entrepreneurs, the strategy of which would be to have flexible professionals capable of critical thinking and equipped with creative skills. Academia can also achieve this through the establishment of innovation hubs for incubating ideas and science and industrial parks for commercialising the ideas. This can only be realised if industry and academia worked closely together through such avenues as problem-based and industry-based learning from where the creative and innovative skills can be nurtured by involving all stakeholders through engineering change management using systems thinking.

References Abu-Goukh, M. E., Ibraheem, G. M., & Goukh, H. M. E. A. (2013). Engineering education for sustainability and economic growth in developing countries (the Sudanese Case). Procedia – Social and Behavioral Sciences, 102(2013), 421–431. Adams, R. (2017). Former Polytechnics should lose University Status. Higher Education in The Guardian of 10 Oct 2017. Arnold, R.  D., & Wade, J.  P. (2015). A definition of systems thinking: A systems approach. Procedia Computer Science, 44(2015), 669–678. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: a survey. Computer Networks, 54(15), 2787–2805. Ayres, R. U. (1990). Technological trasformations and long waves. Technological Forecasting and Social Change, 37(1), 1–37. Bakrania, S., & Lucas, B. (2009). The impact of the financial crisis on conflict and state fragility in Sub-Saharan Africa. GSDRC Applied Knowledge Series. Available: http://www.gsdrc.org/go/ emerging-­issues#crisis. Accessed 24 Mar 2016. Basoglu, N., Daim, T., & Sofuoglu, E. (2009). A decision methodology for customizing software products. International Journal of Industrial and Systems Engineering, 4(5), 554–576. Belaud, J. P., Negny, S., Dupros, F., Micheá, D., & Vautrin, B. (2014). Collaborative simulation and scientific big data analysis: Illustration for sustainability in natural hazards management and chemical process engineering. Computers in Industry, 65(2014), 521–535. Boothroyd, G., Dewhurst, P., & Knight, W. A. (2011). Product design and for manufacture and assembly. Boca Raton: Taylor & Francis Group. ISBN: 13-978-1-4200-8928-8. Broadbent, O., & McCann, E. (2016). Effective industrial engagement in engineering education – A good practice guide, London: Royal Academy of Engineering. ISBN: 978-1-909327-14-6. Brynjolfsson, E., McAfee, A., & Spence, M. (2014). New world order: Labor, capital, and ideas in the power law economy. Foreign Affairs Weekly Newsletter. Accessed 6 May 2020. Available: https://www.foreignaffairs.com/articles/united-­states/2014-­06-­04/new-­world-­order Cicek, K., Akyuz, E., & Celik, M. (2019). Future skills requirements analysis in maritime industry. Procedia Computer Science, 158(2019), 270–274. Crawley, E., Malmqvist, J., Ostlund, S., Brodeur, D., & Edström, K. (2014). Chapter 8: Adapting and implementing a CDIO approach. In Rethining engineering education (pp. 181–207). Duignan, B. (2019). Indsutrial revolution. In Encyclopedia Brittanica. Accessed 6 April 2020. Available: https://www.britannica.com/event/Industrial-­Revolution El-Houssaine, A., Abdelhakim, K., & Le Tam, P. (2016). Optimizing production and imperfect preventive maintenance planning’s integration in failure-prone manufacturing systems. Reliability Engineering and System Safety, 145(2016), 190–198.

References

39

El‐Khasawneh, B. S. (2012). Challenges and remedies of manufacturing enterprises in developing countries: Jordan as a case study. Journal of Manufacturing Technology Management, 23(3), 328–350. Faure, D., & Joly, D. (2016). Chapter 2: Technological revolutions: Possibilities and limitations. In Insight on environmental genomics (pp. 21 – 25). Fleming, J., Iyer, R., Shortis, M., Vuthaluru, H., Xing, K., & Moulton, B. (2010). Employers’ perceptions regarding graduates of engineering dual degrees. World Transactions on Engineering and Technology Education, 8, 277–282. Fomunyam, K.  G. (2019). Education and the fourth industrial revolution: Challenges and possibilities for engineering education. International Journal of Mechanical Engineering and Technology (IJMET), 10(8), 271–284. Gandhi, M. M. (2014). Industry-academia collaboration in India: Recent initiatives, issues, challenges, opportunities and strategies. The Business & Management Review, 5(2), 45–67. Garg, A., & Deshmukh, S. G. (2010). Engineering support issues for flexibility in maintenance. Asia Pacific Journal of Marketing and Logistics, 22(2), 247–270. Gedye, S., Fender, E., & Chalkley, E. (2004). Students’ undergraduate expectations and post‐ graduation experiences of the value of a degree. Journal of Geography in Higher Education, 28(3), 381–396. Global Manufacturing. (2014). 6 Challenges facing the global manufacturing sector in 2015. Available: http://www.manufacturingglobal.com/leadership/6-­challenges-­facing-­global-­ manufacturing-­sector-­2015. Accessed 5 Feb 2015. Government of Zimbabwe. (2018). National Critical Skills Audit report. Harare: Government of Zimbabwe Printers. 2018. Available: https://safrap.files.wordpress.com/2018/12/2018-­ zimbabwe-­nationalcritical-­skills-­audit-­report.pdf. Accessed 22 Oct 2019. Ju, H. (2012). Design a training and maintenance system based on code identification. IERI Procedia, 1(2012), 155–159. Karlsson, M., Nilsson, T., & Pichler, S. (2013). The impact of the 1918 Spanish Flu epidemic on economic performance in Sweden. Working Paper Series 911. Research Institute of Industrial Economics. Available: http://ideas.repec.org/p/hhs/iuiwop/0911.html. Accessed 30 April 2020. Koc, T., & Teker, S. (2019). Industrial revolutions and its effects on quality of life. PressAcademia Procedia (PAP), 9, 304–311. Lwakabamba, S. (2011). Initiative to build capacity in research and postgraduate training. World Journal of Science, Technology and Sustainable Development, 8(2/3), 241–249. Marques, A. F., Alves, A. C., & Sousa, J. P. (2013). An approach for integrated design of flexible production systems. Procedia CIRP, 7(2013), 586–591. Martinez, V., Bastl, M., Kingston, J., & Evans, S. (2010). Challenges in transforming manufacturing organizations into product-service providers. Journal of Manufacturing Technology Management, 21(4), 449–469. Matthews, P., Ryan-Collins, L., Wells, J., Sillem, H., & Wright, H. (2012). Engineers for Africa: Identifying engineering capacity needs in Sub-Saharan Africa, analysis of stakeholder interviews. London: Royal Academy of Engineering. ISBN: 1-903496-91-8. Meybodi, M.  Z. (2013). The links between lean manufacturing practices and concurrent engineering method of new product development. Benchmarking: An International Journal, 20(3), 362–376. Mohajan, H. K. (2020). The second industrial revolution has brought modern social and economic developments. Journal of Social Sciences and Humanities, 6(1), 1–14. Mohamedbhai, G. (2017). The importance of polytechnics for Africa’s development. International Higher Education, 30, 30–31. Nguyen, D. Q., & Pudlowski, Z. J. (2007). Issues and challenges in engineering education and the future outlook of the engineering profession in Australia. Global Journal of Engineering Education, 11(2), 107–116. Nuvolari, A. (2019). Understanding successive industrial revolutions: A “development block” approach. Environmental Innovation and Societal Transitions, 32(2019), 33–44.

40

2  Industrialisation and Technology Dynamics: Recent Research Trends

OECD (Organisation for Economic Co-operation and Development). (2016). Evaluation systems in development co-operation: 2016 review. Paris: OECD Publishing. ISBN: 978-92-64-26205-8. Penprase, B.  E. (2018). Chapter 9: The fourth industrial revolution and higher education. In N.  W. Gleason (Ed.), Higher education in the era of the fourth industrial revolution (pp. 207–228). Singapore: Springer. Peters, M. A. (2017). Technological unemployment: Educating for the fourth industrial revolution. Journal of Self-Governance and Management Economics, 5(1), 25–33. Schwab, K. (2016). The fourth industrial revolution: What it means, how to respond. World Economic Forum 2016. Davos: WEF.  Available: https://www.weforum.org/agenda/2016/01/ the-­fourth-­industrial-­revolution-­what-­it-­means-­and-­how-­to-­respond/. Accessed 2 May 2020. UNESCO. (2010). Engineering: Issues, challenges and opportunities for development. Paris: UNESCO Publishing. ISBN: 978-92-3-104156-3. Vasanthi, S., & Basariya, S.  R. (2019). On the job training implementation and its benefits. International Journal of Research and Analytical Reviews, 6(1), 210–215. Warren, T. (2020). Why the 5G coronavirus conspiracy theories don’t make sense. The Verge. Available: https://www.theverge.com/2020/4/9/21214750/5g-­coronavirus-­conspiracy-­ theories-­radio-­waves-­virus-­internet. Accessed 6 May 2020. World Bank. (2020). COVID-19 Crisis: Through a migration lens. In Migration and development brief 32. Washington DC: World Bank Group. Zinyemba, R. (Ed.). (2010). Academia and the dynamics of transformative leadership: The experience of the University of Zimbabwe in the first decade after Zimbabwe’s Independence (1981-1992). Harare: University of Zimbabwe Publications. Zunino, C., Valenzano, A., Obermaisser, R., & Petersen, S. (2020). Factory communications at the dawn of the fourth industrial revolution. Computer Standards & Interfaces, 71(2020), 103433.

Chapter 3

Systems Thinking Research: Adapting for Engineering Change Management

Abstract  Systems thinking has been an effective approach to managing organisations going through changes as synthesis allowed the observation of how different entities interacted and influenced how an overall system operated. The rapid changes in technology due to the fourth Industrial Revolution demanded regular and corresponding changes in skills to cope with and manage the changes. This book is based on the systems thinking methodology to manage such changes, which have increasingly become complex and intertwined. Engineering change management is the holistic and systematic approach taken for documenting the changes and modelling the bridge between academia and industry, from identifying the required changes, modelling the elements and their relationships, to planning and implementation by connecting the sub-models, testing, verification and validation. This chapter outlines the principles of systems thinking and forms the foundation for the development of systems thinking sub-models that were later integrated to form the universal model to bridge the gap between industry and academia. Keywords  Analysis and synthesis · Balancing · Reinforcing and causal loops · Engineering change management · Feedback · Process and systems mapping · Interactions · Systems thinking

3.1  Introduction Due to the broad nature of application and use of systems thinking in resolving complexities, it has been defined and used for different applications such as diagnosis in health systems and analysis and prediction of behaviour in general systems. The systems thinking methodology employs the systems theory and systematic

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_3

41

42

3  Systems Thinking Research: Adapting for Engineering Change Management

approach to analyse how different parts of a system interrelate to produce a desirable objective function within the context of larger systems. Bartolomeo et  al. (2015) argued that ‘the whole was more than the sum of its parts’. Mathematically, this sounds like an impossibility. However, the fundamentals of interconnectedness and relationships between elements of a system and the systems themselves are not simply resolved by arithmetic additions but by other factors and how these impact on the elements and the systems. The philosophy is based on the principle of reductionism, the traditional approach used in modern science for describing complex phenomenon in terms of individual elements that make up a system. Elements within a system are interconnected and to understand their roles, the purpose and function of the system must be understood.

3.2  Systems Thinking Tools By virtue of their inclusion, components within systems play important roles although some are needed more than others and systems may also exist within subsystems (Behl and Ferreira 2014). While problems exist in these systems and subsystems in general, the dynamic approach for solving these problems using systems thinking require the scrutiny of individual components but more so and thereafter looking at the subsystems and eventually the entire universal system as components and their systems rarely work in isolation but depend on each other due to their interconnectedness. The interactions between elements of a system and the performance of the universal system are the key attributes required to shape the structure and determine how to adequately adjust in order to improve system performance. Systems thinking can be further refined to include interdependences between system components that are not necessarily technical but can be socially oriented, hence the suitability of the methodology for analysing multiple interactions in systems (Oliver et al. 2016). The skills and competencies required of system engineers lay in the ability to understand and interpret the relationships between interacting components of systems in order to map and adjust them for optimal system performance. The use of systems thinking for resolving organisational challenges can be achieved by first resolving ‘standalone’ problems and then further explored to collaborative systems where teams and expertise are drawn from different disciplines to offer specialised perspectives for multi-faceted challenges (Oliver et al. 2016). Systems, particularly those in science, technology and engineering, have evolved over time and in respect to the principles and techniques that are employed in the various disciplines but ultimately the interdisciplinary nature of such systems is the strength that systems thinking can offer to resolve challenges that are multi-faceted and particularly also due to the rapid and dynamic changes in technology, which required engineers to be multi-skilled and have an understanding of other aspects outside their disciplines (Gero 2017). The most widely used systems thinking software tools, Arena and STELLA, are very technical and sometimes ignore the human element for the requisite knowledge of the interconnections, interdependences and

3.2  Systems Thinking Tools

43

relationships between components of systems and their subsystems (Hong et  al. 2017). In such instances, the analysis of the systems through reductionism can be difficult to achieve in models and projects that are dynamic and human driven, often requiring the inevitable separation of the project model into smaller parts in order to synthesise them properly. In their research to manage the implementation of systems thinking to manage risk in public–private partnership projects, Loosemore and Cheung (2015) concluded that the separation of projects may have undesirable outcomes that may result in failure to manage the projects at interdisciplinary levels and in the process lose the capacity to adjust or understand why a system behaves the way it does. Unlike the traditional approaches of analytical problem solving, which are usually done in a straightforward and linear manner, systems thinking tends to be more useful for circular problems where the holistic picture of the system is considered to provide solutions even to symptoms of the problems instead of the traditional causes and effects. The systems thinking holistic approach places more emphasis on the system structures instead of humans and physical processes. Sometimes this invariably puts a barrier to innovations and long-term improvements and effectiveness of the systems (Chen 2016). Additionally, this tends to raise possibilities of creating turbulences in established policies, especially those that are required for professional development, performance management, monitoring and evaluation of personnel due to humans’ comfort with routine tasks and structured systems (Schiuma et al. 2012). This kind of rigidity is one of the key challenges encountered when trying to use systems thinking for engineering change management.

3.2.1  Analysis and Synthesis Although systems thinking involves both reductionism, that is, breaking down a system into its component parts and analysing them through the traditional analytical approach, the main focus is on synthesising and dissecting the complexities to understand the relationship between the components. Synthesis therefore goes beyond analysis to combining two or more elements to create a new system. Analysis on the other hand is more applicable to the more technical and reductionist angle where the system is viewed as parts. Despite this distinction, all systems are normally dynamic and complex in nature, hence the need for a holistic approach in order to decipher and understand the concept. Entities within an organisation are like parts of a machine required to perform an overall function when put together. Synthesis is therefore an appreciation of the whole and the parts that make up the system concurrently, together with the interconnections and interdependencies that make up the whole such as shown in Fig. 3.1. The more specific engineering systems thinking is a synthesis tool that allows engineers to perform tasks in an integrated manner in order to achieve the optimisation of operations or organisations from the systems point of view (Frank 2012). These cognitive competences and skills are initially acquired at tertiary institutions

44

3  Systems Thinking Research: Adapting for Engineering Change Management

Fig. 3.1  Interconnected system with nodes and feedback loops

and then nurtured and developed over time through experience and exposure to practice in industry and interactions with professionals from other disciplines. The management of operational systems in an engineering or manufacturing environment also requires attention on both the human and structural aspects which are generally regarded as complementary to the technical systems (Behl and Ferreira 2014). The ability to understand and decipher the interconnections and relationships between system elements, the implications and their functions with minimal constraints is the cornerstone of engineering systems thinking in operations that have certain levels of complexities. The application of systems thinking in science, engineering and technology has mainly been streamlined and focussed on engineering systems thinking, prompted by the demands to have graduates acquire such skills during training for them to have broader appreciation and ability to resolve complex operational and organisational issues of an interdisciplinary nature for sustainability. Both approaches of analysis and synthesis were applied in this book although the focus dwelt more on the latter, in the process of linking the acquisition of skills at tertiary institutions and application of the same in industry for engineering change management in the bridging of the gap between academia and industry.

3.2.2  Interconnectedness Unlike the traditional and linear way of resolving problems, systems thinking tends to be circular, the fundamental difference being that of the availability of reinforcing or balancing feedback loops. This difference, basically displaying and demonstrating the interconnectedness of systems, an attribute that is key and one of the many

3.2  Systems Thinking Tools

45

systems thinking tools. The notion of interconnectedness is that in real life, components of systems and subsystems rely on each other. Usually, failure in one subsystem that is connected to another one to form a universal system, most likely translates to failure in the other systems or at best, operations of the other systems may go on but with reduced capacity. As an example taken from the thrust of this book, industry relies on graduates from tertiary institutions to drive industry, the government that funds higher education relies on taxes derived from profits generated by industry, just to mention a few attributes that demonstrate a cyclic and circular nature of the relationships. In general, elements and subsystems of systems need each other for full functionality, often generating complex arrays to perform desirable functions. Physical systems such as a wooden door requires a tree to grow in order to provide the timber required to produce the door, a car requires fuel for it to be able to move etc. Interconnectedness of components from a systems thinking point of view is the fundamental principle of life for such systems. This is why systems thinking practitioners such as Meadows (2008) generally defined it as: ‘A system is a set of related components that work together in a particular environment to perform whatever functions are required to achieve the system’s objectives’. The sense of looking at systems shifts the mind-sets of professionals to view the universe and its systems from a linear and structured world to that which is dynamic and sometimes chaotic, consisting of numerous interconnected array of relationships, causal and feedback loops, some of which help to reinforce a function while some balance out to maintain a smooth performance.

3.2.3  Process and Systems Mapping Apart from feedback loops, knowledge of the connection of systems and the ability to analyse and synthesise, process flow and systems mapping are also tools for systems thinking. There are various ways in which these tools can be employed, from the conventional analogue cluster mapping to digital and computerised feedback and causal loop analysis. In general, however, the basic principles and practices of process flow and systems mapping are standard and universal. The identification and mapping of the components within a system, enables the understanding of interconnections and relationships in complex organisations and operations. Unique insights and revelations can then be derived and used to develop interventions, prioritisation of tasks and possibly change of policies that can significantly and positively impact on the performance of the organisation. Various analytical and computerised systems mapping tools are at the disposal of the systems thinker, ranging from graphs to analyse the behaviour of systems over time, general systems modelling to build and simulate systems, causal loop and feedback diagrams to understand how subsystems impact on each other and interconnectedness to understand the relationships of components or subsystems within systems and subsequently what the individual functions of the components and that of the combined system.

46

3  Systems Thinking Research: Adapting for Engineering Change Management

Fig. 3.2  Unconnected systems map for stakeholders in academia and industry

A systems map allows systems engineers to set out the components and boundary of a system and the components of the environment in which they reside at a particular point in time. This effectively makes the systems map, a list of components in the system or a graphical representation of the same. The main purpose for mapping systems is to be able to accurately structure a system and its boundaries to enable easier understanding of the interconnections for analysis and synthesis. A typical systems map is shown in Fig.  3.2 for the various boundaries used in this book, that is, Tertiary Institutions, Industry, Professional and Regulatory Bodies, Research Institutes, International Partners and Government but exclusive of the relationships between them, a subject for later chapters.

3.2.4  Emergence (Outcome of Systems Interactions) In general, outcomes from systems thinking models, whether positive or negative, emerge from the interactions of system components. These outcomes basically describe the global concept of how life is born out of individual biological elements from two parents in a natural but unique way. Emergence is therefore the outcome of the interaction and synergies of system components in a non-linearity and often self-organisation. The outcome of system interactions is the overall objective of carrying out a systems thinking analysis and synthesis to optimise operations or the business in an organisation. For the purposes and thrust for this book, the expected outcome of which are skilled engineers who will be able to drive industry in this era of rapid and dynamic changes in technology and the fourth Industrial Revolution. If the universities and industry work closely together, then the graduate engineers produced would be ideal to drive industry without any major additional training required. For government to realise maximum taxes from the profits generated by industry, then they must provide well-resourced learning institutions to produce

3.3  Systems Thinking Operations

47

well-trained graduate engineers. These are the emergences or the expected outcomes from such interactions and will be handled in more detail in latter chapters.

3.3  Systems Thinking Operations Systems thinking is an emerging paradigm within many areas from science, engineering, business management and many other areas, including social sciences. It presents an alternative to the traditional modelling and analytical methods of investigations and solution to complex problems by emphasising the need for a more holistic and conceptualised understanding of the system within which the problem resides. Systems thinking is often employed when the current paradigm or traditional analytical method has reached a limit and thus it gives a fresh perspective or alternative approach to resolving problems. Systems thinking is often regarded as the beginning of systems theory, which provides a whole suite of tools for analysing and modelling systems and their interaction dynamics as they evolve over time, broadly making it a way of describing systems in a more holistic manner based upon the model of its elements, relationships and functions (Behl and Ferreira 2014). The system can be anything ranging from a machine consisting of different parts performing a function and contributing the overall function of the machine. In essence, the machine itself could well be within another system, say a production factory where it is used as a workstation among a group of other workstations, thus forming another system of the production factory, which in fact can also be a system within the manufacturing company. The sequencing of systems goes on and on to the extent that even the most remote of possibilities will see some form of relationship. For example, the manufacturing company ultimately has to produce profit that can be used to pay employees at all levels and also provide taxes to the government in which the manufacturing company resides. Part of the profits can also be ploughed back to provide continuous training and skilling of professionals to ensure that the company remains competitive, generating enough profit to remain afloat. Traditionally, professional engineers made use of the analytical methods that are normally taught during their engineering education and training such as thermodynamics, fluid mechanics, dynamics, solid mechanics, strength of materials, and design for manufacture and assembly, as well as engineering design in general, in order to improve their products through product development and designs. These analytical methods are extremely useful, particularly for rebranding and improvement of product performance on the increasingly competitive global market. However, what many engineers are barely trained on is the ability to look beyond the product, what it is made of, how strong it is and its functions. The main focus for this book is to present engineers with an alternative way of assessing their products and services through a holistic and systems thinking approach that seeks to analyse beyond the functions of the products in a system and also how the same product or service is impacted on by other related factors such as the ability and skills to develop or modify the product or service.

48

3  Systems Thinking Research: Adapting for Engineering Change Management

3.3.1  System Dynamics and Complexities In many institutions and enterprises, the activities such as lectures, laboratory work, tutorials and workshops (acquisition of skills in academia) and product development and design, manufacturing and processing (application of the skills in industry) are composed of numerous entities that make up systems in daily life. In almost all of them, the systems are composed of three major sections: input variables, processing and parts interacting under certain conditions, desirable and undesirable outputs and outcomes. The purpose of systems thinking would be to decipher, understand and predict the behaviour of such systems in order to produce desirable results while side-lining the undesirable outputs. This can be achieved through some kind of looping and feedback control. As such, systems thinking is thus regarded as a system dynamics instrument that allows systems engineers and engineers in general to comprehend how the system would behave by way of analysing and identifying governing rules, patterns and bottlenecks and thus the ability to control and adjust future outcomes (Cadavid et al. 2010). The interconnectedness and relationships between system elements do not necessarily follow the logical route predicted by traditional analytical methods due to system dynamics in which an effect can be the future cause of other effects in a looping or cyclic domain. By and large, this explains why systems approach is required to analyse the secondary effects as it may not be detected in the analytical approach. The performance of a system depends on its elements and how they are connected and interact to produce a desirable function, hence the importance of the relationships and how they affect each other rather than how many elements are in the system or their properties. Reductionism is the detailed complexity and process of splitting up a system into its individual elements, thus enabling the analysis of the different elements of the system while synthesis is the dynamic complexity and the manner in which the elements are connected and related to each other in the system to produce a desirable function. When both the detailed and dynamic complexities have a high prevalence, probably due to the nature of connections and relationships, then the system is regarded as complex (Cadavid et al. 2010). Such high prevalence of interactions is in itself a warning signal that any tempering can have serious consequences on the outcomes and impacts, thus affecting the desirable outputs.

3.3.2  Feedback Loops and Control of System Performance The major purpose for analysing systems using the systems thinking methodology is for professionals or users to be able to study and understand system behaviour to enable them to predict future behaviour and also adjust and control system variables and parameters in order to obtain desirable outputs. The behaviour of such systems can be measured and controlled through feedback loops, periodically. Quite often, control and adjustments of system elements and other actions can influence and

3.3  Systems Thinking Operations

49

impact the system over time. The feedback loops can also be used to understand the behaviour of systems within systems (subsystems). Essentially, these loops represent the system’s response that may resuscitate in the form of a boost or generates information that may affect a future action or stage. For a system to be considered complete, there must be some feedback loops. There are two types of feedback loops that are generally used in systems thinking, that is, positive reinforcing and negative balancing loops (Cadavid et  al.  2010). When a modification or changes occurs throughout a system, it is regarded as positive, if the changes occur in the same direction, thus boosting the cause from where it would have originated. Positive reinforcing loops usually result in desirable or virtuous cycles but can also be equally detrimental, hence the need for critical thinkers in the use of this methodology. Negative balancing loops on the other hand provide a balancing act where modifications in the system naturally oppose the initial change with an eventual effect of dampening the process and desirable outcome, thus maintaining the stability of a system that would otherwise be distorted by the action of positive reinforcing feedback. Negative balancing feedbacks often guide the system to the desirable outcome until such a time that it weakens and system changes become gradual (Cadavid et al. 2010). Essentially, the effect of the negative feedback is to achieve the desirable outcome, while that of the positive feedback is to provide a constant progressive effect.

3.3.3  Causal Loop Flow Diagrams Most problems that are handled or set aside for solving using systems thinking are usually not linear but cyclic in nature, hence the emergence and use of feedback loops and sometimes contours (Palaima and Skarzauskiene 2010). Considering the setup of a production plant consisting of several workstations that are arranged to process parts in sequence from the first workstation to the next, particularly in a flexible manufacturing system where the workstations are controlled centrally, a change or breakdown in one workstation generates wave of changes in subsequent workstations, thus affecting the entire production plant. The change or breakdown in that workstation returns a signal to the starting point or control station and prompts the users to modify the change in the loop in order for production to continue. The feedback loops are therefore responses to the changes and resulting actions, thus making the feedback an integral attribute of a system. The most commonly employed graphical representation for systems thinking that are employed to study, understand and predict the behaviour of systems are the causal loop flow diagrams. Such diagrams are used to display internal system variables and parameters, external influences, delays in behaviour and reaction, as well as other system parameters and components in such a way as to enable the easy visualisation of the effects that these elements have on each other. Other unexpected or expected reactions may emerge, thus revealing different loops in that manner. The concepts of feedback and causal loop flow diagrams in

50

3  Systems Thinking Research: Adapting for Engineering Change Management

University Management B Policy (Government)

R

Acquisition of Skills (Academia)

B

B Application of Skills (Industry)

R

B Professional Support and CPDs B

Employee Productivity

Fig. 3.3  Academia–Industry causal loop flow diagram

systems thinking can be represented by the relationship between academia and industry, the thrust for this book, with the overall aim of bridging the gap between the two. Although there are several factors and attributes, at this stage, the four main aspects for consideration would be: Acquisition of Skills and Training at universities, University Management and Government for Policies, Application of Skills and Employee Productivity, as well as Support for Professional Skills (CPDs) in industry. Figure 3.3 shows the typical feedback loops for such arrangements where the Acquisition of Skills loop (Balancing – B) describes that when there is an increased demand for engineers in industry, such as the shortage and mismatch of skills in Southern Africa, the need for restructuring the training of engineers and curriculum development and review also increases. The positive University Management (Reinforcing – R) loop then probes for and pushes for quick management actions to be taken to implement changes in the training and acquisition of required skills and prioritisation of the same. The negative Application of Skills and Employee Productivity (Balancing – B) loop shows that if there is an urgent requirement for additional engineers with

3.4  Implementation of Systems Thinking

51

certain skills, responsible authorities at tertiary institutions need to work over and above the normal schedules and possibly introduce additional classes, increase the number of institutions or students to satisfy industry demands for sufficient and appropriate skills. The positive Support for Professional Skills loop (Reinforcing – R) and continuous professional development of engineers in academia and industry reveals the need for intervention by policy-makers and resource organisations such as both university management and industry in the provision of support services and policies for professional development support and maintenance that may require release of financial services for the additional training requirements to meet industry needs.

3.4  Implementation of Systems Thinking While systems thinking is a universal methodology employed in almost all spheres of life and thus defined by different users to mean different things, the technique for its use goes beyond just the tools and methods but has become a philosophy for solving and optimising complex scenarios (Palaima and Skarzauskiene 2010). The use of feedback and causal loop flow diagrams has become the in-thing for looking at systems holistically, but the methodology is also sensitive to the increasingly circular nature of economies around the world and thus a realisation of the strong rules governing systems of the world. This has enlightened many researchers to developing structures and the conditions that govern them and in some instances it has unveiled issues that systems engineers may not have been aware of and thus possible consequences that they may be oblivious to. Systems thinking has been successfully employed as a diagnostic tool for organisations going through distress and thus enlightened them to make appropriate decisions based on the predictions that the methodology offers. The study and understanding of the relationships and functions of elements within a system often requires collection of data and observing processes or flows in order to identify behavioural patterns back to underlying principles and structures that drive the systems. The ability to decipher and change system structures to provide solutions to challenges allows more alternatives to be availed for comprehensive long-term solutions to perennial problems such as the shortage and mismatch of engineering skills. The use of systems thinking therefore not only requires a critical thinking and inquiring mind but one with courage, curiosity and willingness to adopt change through visualising a situation more completely. This should also include recognition of the intertwining relationships of distant but related systems, as well as the knowledge that multiple solutions to challenges can exist and thus requires open minds to explore even ‘outside the box’. Compared to traditional and analytical modelling and design tools for engineers, systems thinking avails a wider variety of choices and options, thus expanding the possible solutions conceptualised and taken holistically. The emergence of several alternatives and solutions inevitably enable users to realise that there is no perfect

52

3  Systems Thinking Research: Adapting for Engineering Change Management

solution to a problem since the changes that may be effected on one system may also impact on other elements of the system or even other external systems. That enlightenment of the impact of other elements or systems helps to minimise severity and in some cases it can be used to the advantage of the organisation, thus allowing users to make well-informed decisions to avoid any damages that may be caused by the changes. The graphical use and representation of systems using feedback and causal flow loop diagrams are effective vehicles for identifying, analysing and relaying of information among increasingly interconnected groups such as academia and industry. Having foresight, critical thinking and right frame of mind are vital attributes and prerequisites for resolving problems using systems thinking and thus the process of using such methodology requires professionals to focus on issues that are usually ignored as these sometimes form the core for solutions under systems thinking. In addition, it is also vital to fully understand the sequence of flows and processes within the context of the feedback and causal flow loops to ensure that the right problem is identified in order to get the best solution, and this can be accomplished from structuring the problem(s) through events, processes, patterns, behaviour and the structure itself (Arnold and Wade 2015). In so doing, assumptions used in formulating the problem must be clearly stated and backed by authentic information by drawing from different and experienced professionals’ perspectives to ensure that all views are incorporated and that possible solutions are adoptable by all concerned. The systems thinking approach adopted in this book was to build the smaller subsystems and then connected these to make the sub-models, which were eventually integrated to the universal systems thinking model for bridging the gap between industry and academia. The bigger the system and the more the interconnections, then more feedback and causal loops will be required in order to clarify the causal interconnections that may arise. While it was vital to incorporate all relevant details to the system model, including external details that do not have variable parameters of those whose changes are irrelevant to the system may actually complicate the ultimate purpose and function of the model. Effective feedback and causal loops normally reveal those hidden relationships that may not have been obvious at the time of formulating the systems thinking model.

3.5  Successes and Failures in Systems Thinking The use and application of systems thinking has been spreading throughout the world but in different ways. Pana et  al. (2013) analysed and made comparisons between Chinese and Western approaches to the methodology and concluded that, although there were similarities, the Western (UK and USA) methodology emerged from reductionism (detailed analysis of system components) to holistic analysis of entire systems, whereas the Chinese approach was popularised in the opposite direction. Models developed in the West tended to be used for describing, analysing and verifying before solving problems, whereas the Chinese were more

3.5  Successes and Failures in Systems Thinking

53

goal-­oriented and relied more on human interpretation and intuition. Although significant work has been carried out using systems thinking, this has been concentrated mostly on social sciences, education and health. The application in science, engineering and technology has been for specific issues such as analysis and optimisation of manufacturing systems (Khayut et  al. 2014), cognitive competences required by systems engineers (Frank 2012) and engineering curricula (KoralKordova and Frank 2012). The focus for this book was premised on the hypothesis derived in Chap. 1, and the assumptions that if the problem of insufficiency and inappropriate skills cannot be resolved using the traditional and analytical means, then the solution may well lie in an integrated approach to sustain operations in a dynamic society (Oliver et al. 2016). Taking cognisance of the fact that the engineering skills required in the era of dynamic and rapid changes in technology are frequently conceptualised with uncertainty and that the use of traditional engineering education, which focusses on analytics, the complex and dynamic interactions in the fourth Industrial Revolution, required a multiplicity of skills and interdisciplinary approach to solving them. Based on the assumption and principle of the systems thinking methodology that a system comprises of more than just its elements but a cohesive and integrated set of variables and parameters and how they interact with each other to perform a required function, the approach was adopted to link and bring industry closer to academia. Arnold and Wade (2015) employed the methodology as a problem-solving approach that considered individual problems of an overall system, their consequences and events that resulted in unwanted outcomes. Systems thinking has also been employed to minimise risk in public, private partnerships where Loosemore and Cheung (2015) recommended that engineering education and training should be conducted in such a way as to visualise projects and risks in joined up (teams) rather than in deterministic ways. Ultimately, this implied the need for academics to take holistic approaches to student projects instead of separating them into mini-projects to avoid the disturbance of the relations of elements and their overall functions in a system. More and more group work projects have been encouraged and implemented, especially for undergraduate students, where such training is geared to prepare them for work as teams in industry. The work in this book combined aspects of engineering skills acquisition and mapped them with the requirements for application of those skills in industry, based on the available equipment and technologies. The integration of these subsystems enabled capacity building for self-sustenance and promotion of a culture of teamwork. Problems encountered in science, engineering and technology are not always of a technical nature but multi-faceted, the integrated approach. The development of products, inventions and innovations have increasingly become complex due to a number of issues including global competition and dynamic changes in technology. In addition to the technical know-how, this requires engineers to continually upgrade and broaden their skills to be able to tackle peripheral aspects such as the impact on the environment as well as other social issues. Williams et al. (2013) developed a value enhancement model for the linear friction welding for use in aircraft engines. This was done using systems thinking in such a way as to identify critical factors such as human and equipment.

54

3  Systems Thinking Research: Adapting for Engineering Change Management

The research resulted in a successful fault detection and isolation model which was tested and adopted by Rolls-Royce by a combination of the value enhancement models to an integrated one. Lucas et al. (2014) also considered and identified six engineering habits of the mind of which systems thinking was one of the top ones, an indication that critical thinking skills was among the top requirements for engineers in the future, to cope with rapid changes in technology. Although skills and competences are the most critical attributes required to adopt, implement or employ systems thinking to optimise operations, it can be done through a phased approach and in stages in order for personnel to gradually get acquainted and eventually using these for periodic analysis and synthesis of their systems (Behl and Ferreira 2014). Due to the strengths offered by a combination of reductionism in analysis, different levels of synthesis can be executed from the very basic to the more complex and dynamic activities of an entire system (Chen 2016). The ability to break down and analyse individual elements of a system enabled systems engineers to determine the cause and effects of operational challenges without the need for feedback or causal loop diagrams or their closed boundaries (Schiuma et al. 2012). Through studying and understanding the individual components broken down and derived from the system, a solution may actually unexpectedly emerge by way of visualising the system from a variety of perspectives (Chen 2016). Depending on the system structure, reductionism alone can also offer advantages of visualising the system as closed and thus allowing different elements to be analysed individually to be deterministic or predictable. Conceptual frameworks can also be employed in systems thinking by way of using different theories and methodologies such as the Soft Systems Methodology (SSM), which can create an entire and holistic overview for the purposes of the relationships of elements and functions of a system (Wang et al. 2015). Schiuma et al. (2012) determined that non-linear modelling can also be used in systems thinking to enable different components to be connected in recurring chains, thus making it easier to identify interactions among different parts for establishing a system’s behavioural patterns. The interactions between components, A, B and C can also be regarded as linear, where A affects B and in turn affects C in such a way that this can be traced to study the behaviour from where results on an operational rather than a wider system level can be obtained (Qiu et al. 2016). Systems thinking has also been employed successfully for isolating risks during scoping for project management. This was accomplished through examining the complex interconnections between project execution success against the environment in which the project was domiciled (Loosemore and Cheung 2015). Despite all these glowing advantages for using systems thinking for resolving complex and operational issues, it is not an end itself, as it requires years of experience and expertise otherwise what may seemingly be a viable alternative and solution to an operational challenge, may actually result in a worse situation than prior to changes. To realise the ultimate benefits of using systems thinking requires careful sequencing and a full appreciation of the operations before proffering possible alternatives through systems thinking. Although systems thinking has been employed to resolve complex issues such as facilities layout and inventory control (Van Horenbeek et al. 2013), production systems (Oliver et al. 2016), construction projects (Saurin 2016) and logistics (Kunze et al. 2016), these have been specific activities and not wholesome solutions in those areas.

References

55

3.6  Conclusion The application of systems thinking as a methodology for analysing and synthesising systems in organisations offers an alternative way of resolving operational challenges to the traditional and analytical methods that are often linear. This chapter introduced the methodology from the fundamentals and systems thinking tools through to how it is employed and implemented for optimising and enhancing efficiency in organisations and finally how it has been successfully applied elsewhere, coupled with possible failures and challenges that can be encountered in its use. Systems thinking involves the visualisation and understanding of how systems are constructed from the elements that are interconnected and how they are related through to what objective functions they are supposed to achieve. Several systems thinking tools are at the disposal of the analyst to fully appreciate, relate and adjust these for a desirable outcome. The use of reinforcing and balancing feedback and causal loop flow diagrams enables the analyst to break down and synthesise dynamic complexities encountered in systems from system mapping to appropriate adjustments of system parameters and variables for optimal operations. Due to the rapid and dynamic changes synonymous with industrial transformations, particularly the transition from the third to the fourth Industrial Revolutions, the need to continually change, adapt and cope with these transformations has been on the increase particularly for the science, engineering and technology sectors. Engineering change management in this regard requires a holistic and systematic approach for documenting the changes. The focus and main thrust for this book is to model these changes with a particular focus on the acquisition of skills at tertiary institutions and the application of these skills appropriately in order to drive industry. The book is premised on the assumptions and hypothesis that in order to bridge the gap between academia and industry and be able to respond adequately to the demands of the fourth Industrial Revolution, there is a need to carry out engineering change management by identifying gaps and the required adjustments, modelling the components and their relationships into subsystems and then planning and implementation by connecting the sub-models, testing and validating, culminating in the universal systems thinking model for bringing industry closer to academia, details of which are covered from Chap. 4 onwards.

References Arnold, R.  D., & Wade, J.  P. (2015). A definition of systems thinking: A systems approach. Procedia Computer Science, 44(2015), 669–678. Bartolomeo, P., Vuilleumier, P., & Behrmann, M. (2015). The whole is greater than the sum of the parts: Distributed circuits in visual cognition. Cortecx, 72(2015), 1–4. Behl, D. V., & Ferreira, S. (2014). Systems thinking: An analysis of key factors and relationships. Procedia Computer Science, 36(2014), 104–109. Cadavid L. R., Duque D. F., Garay J. A., & Caicedo P. F. (2010). Applying systems thinking and active learning strategies to a lean manufacturing program. Production and Operation Management Society (POMS) 2010 Conference, Vancouver, Canada.

56

3  Systems Thinking Research: Adapting for Engineering Change Management

Chen, H.  T. (2016). Interfacing theories of program with theories of evaluation for advancing evaluation practice: Reductionism, systems thinking, and pragmatic synthesis. Evaluation and Program Planning, 59(2016), 109–118. Frank, M. (2012). Engineering systems thinking: Cognitive competencies of successful systems engineers. Procedia Computer Science, 8(2012), 273–278. Gero, A. (2017). Students’ attitudes towards interdisciplinary education: A course on interdisciplinary aspects of science and engineering education. European Journal of Engineering Education, 42(3), 260–270. Hong, J., Yeom, S., Eoh, J. H., Lee, T. H., & Jeong, J. Y. (2017). Heat transfer performance test of PDHRS heat exchangers of PGSFR using STELLA-1 facility. Nuclear Engineering and Design, 313(2017), 73–83. Khayut, B., Fabri, L., & Avikhana, M. (2014). Modeling of intelligent system thinking in complex adaptive systems. Procedia Computer Science, 36(2014), 93–100. Koral-Kordova, S., & Frank, M. (2012). Improving capacity for engineering systems thinking (CEST) among industrial engineering students. In IEEE international conference on industrial engineering and engineering management (pp. 1378–1380). Hong Kong, Dec 2012. Kunze, O., Wulfhorst, G., & Minner, S. (2016). Applying systems thinking to city logistics: A qualitative (and quantitative) approach to model interdependencies of decisions by various stakeholders and their impact on city logistics. Transportation Research Procedia, 12(2016), 692–706. Loosemore, M., & Cheung, E. (2015). Implementing systems thinking to manage risk in public private partnership projects. International Journal of Project Management, 33(2015), 1325–1334. Lucas, B., Hanson, J., & Claxton, G. (2014). Thinking like an engineer: Implications for the education system. London, UK: Royal Academy of Engineering. ISBN: 978-1-909327-08-5. Meadows, D.  H. (2008). Thinking in systems. Chelsea Green Publishing, USA.  ISBN: 978-1-60358-055-7. Oliver, J., Vesty, G., & Brooks, A. (2016). Conceptualising integrated thinking in practice. Managerial Auditing Journal, 31(2), 228–248. Palaima, T., & Skarzauskiene, A. (2010). Systems thinking as a platform for leadership performance in a complex world. Baltic Journal of Management, 5(3), 330–355. Pana, X., Valerdi, R., & Kang, R. (2013). Systems thinking: A comparison between Chinese and western approaches. Procedia Computer Science, 16(2013), 1027–1035. Qiu, Y., He, Y. L., Wu, M., & Zheng, Z. J. (2016). A comprehensive model for optical and thermal characterization of a linear Fresnel solar reflector with a trapezoidal cavity receiver. Renewable Energy, 97(2016), 129–144. Saurin, T.  A. (2016). Safety inspections in construction sites: A systems thinking perspective. Accident Analysis & Prevention, 93(2016), 240–250. Schiuma, G., Sole, F., & Carlucci, D. (2012). Applying a systems thinking framework to assess knowledge assets dynamics for business performance improvement. Expert Systems with Applications, 39(9), 8044–8050. Van Horenbeek, A., Bure, J., Cattrysse, D., Pintelon, L., & Vansteenwegen, P. (2013). Joint maintenance and inventory optimization systems: A review. International Journal of Production Economics, 143(2013), 499–508. Wang, W., Liu, W., & Mingers, J. (2015). A systemic method for organisational stakeholder identification and analysis using Soft Systems Methodology (SSM). European Journal of Operational Research, 246(2), 562–574. Williams, D. T., Beasley, R., & Gibbons, P. M. (2013). Combining hard and soft system thinking: the development of a value improvement model for a complex linear friction welding repetitive process (lfw-VIM). Procedia Computer Science, 16(2013), 1007–1016.

Chapter 4

Academia and Industry Collaborations: A Research and Professional Perspective

Abstract While collaborations between polytechnics and industry existed and were well pronounced in the earlier revolutions where apprenticeship training was key to driving industry, the relationship between industry and universities was not well pronounced. The transformations in the engineering education sector, especially from the third to the fourth Industrial Revolution, saw the introduction of industrial attachments for both the traditional and technical universities. This was partly in response to the demands for appropriate skills due to the fourth Industrial Revolution and it was also meant to address the gap created by the conversion of polytechnics to universities. This chapter focusses on the collaborations between various tertiary institutions, both the traditional and technical universities, and industry partners in Southern Africa from 2011 to 2020, in order to establish effectiveness of such relationships and how this could be synthesised and modelled using systems thinking for repeatability and sustainability in capacity building in order to bridge the gap between academia and industry. Keywords  Academia–industry partnerships · Attachments · Attributes · Competences · Continuous professional development · Industrial secondments · International backstopping · Knowledge sharing · Resources and equipment · Technology transfer

4.1  Introduction The advent of the industrial transformations and, in particular, the fourth Industrial Revolution demanded the close collaboration of academia (acquisition of skills) and industry (application of those skills). More than ever before, industry required relevant skills to drive rapid changes in technology, particularly equipment and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_4

57

58

4  Academia and Industry Collaborations: A Research and Professional Perspective

methods in the ever-increasing integration of systems (Harrison 2012). The reduction in the number of polytechnics due to their upgrade to universities meant the various universities that trained engineers and technologists required to put aside time for these trainees to spend more time than before industry (Mohamedbhai 2017). Polytechnics that traditionally produced technicians normally had their students spending close to 50% of their time in industry on the job training. However, the conversions of some of the polytechnics were not matched with the establishment of new ones, hence the reduction of apprenticeship training. This inevitably meant that some of the engineers and technologists being trained at the traditional and new universities required to undertake training on the job in order to take over some of the tasks meant for technicians.

4.1.1  Importance of Academia–Industry Partnerships By nature, and practice, industry holds the financial capacity through their revenue generated in production while academia holds extensive knowledge and research capacity apart from being experts in their respective areas of specialisation. While cooperation and working together of the two has been successfully implemented in the industrialised world, the concept is still fairly new in the industrialising world. However, the collaborations thus far implemented in Southern Africa involving 9 tertiary institutions and 14 industry partners have proved the importance and various advantages of such collaborations. Undoubtedly, the academics’ secondment to industry enabled them access to modern equipment and technology in most cases where such equipment and technology would usually not be available at institutions of higher learning. Not only did this enhance their own skills but also prepared them to confidently deliver their lectures to future engineers, thus producing relevant and appropriate skills. Secondment to industry by academics also broadened their career opportunities, developed industry-based projects for students, created opportunities for consultancy in solving industry problems thus raising the much-needed funds for research. In the process, and in view of the rapid changes in technology and increased integration, academics were also kept in tandem with these changes for the sake of their students. On the other hand, one of the key deliverables and expectation from practising engineers was Continuous Professional Development (CPD). The engineering profession is very dynamic in such a way that what students learnt at inception may in fact be irrelevant at graduation. Therefore, for all engineers in industry, it was of vital importance to keep in tandem with the rapid changes in technology, particularly new machine tools and methods, hence the need to be continually trained by tertiary institutions. This has actually been enforced as a requirement by professional engineering institutions for licencing of engineers on an annual basis where they are required to accumulate a number of CPD points, 15  in the case of and according to the Zimbabwe Institution of Engineers (2015). For the practising engineers, the interactions with academia also allow them access to extended networks,

4.1 Introduction

59

scouting for new talent among students and above all, new information, methods and knowledge sharing. In view of the new requirement by almost all tertiary institutions for a mandatory 1-year industrial attachment for students before graduation, collaborations of this nature certainly created platforms to make this possible. While this has been achievable in the more stable economies in Southern Africa, such as Namibia, Botswana and Mozambique as well as the semi-industrialised South Africa, Zimbabwe faced a number of challenges mostly orchestrated by its unstable economy, and the conversion of about five technical colleges into degree awarding institutions without replacing them with more polytechnics. However, partnerships of this nature are beneficial for both academia and industry in the long run.

4.1.2  Building Robust and Successful Collaborations Gandhi (2014) suggested that in order to build cohesive interactions in a collaboration, it was vital and necessary to establish and acknowledge the aims and objectives of all stakeholders in the collaboration. Clearly, this translated to the systems thinking approach where stakeholders comprised the elements of the system, their relationship constituting the interconnections and the achievement of the aims and objectives being the impact/outcome or deliverable functions. Although there are many stakeholders required for bridging the gap between industry and academia, the key ones comprise academia and industry professionals. The main aim of academia was the acquisition and dissemination of the state-of-art research and education to future engineers to drive industry while industry’s main aim was to generate profit for shareholders using the acquired skills from academia. In this ever-­ increasing integration of systems and global competition, to achieve the industry objective, often innovations have now become commonplace and can be accomplished through the use of new talent and ideas from academia. These are the fundamental requirements for a successful collaboration between industry and academia. Having established the foundation, it was also important to operationalise the cooperation and of utmost importance in that regard was transparency and effective communication. Quite often, either students on attachment, academics on secondments or practising engineers undergoing training at tertiary institutions, encounter a lot of information, sometimes confidential. Before engaging in any of these activities, both academia and industry need clear agreements on confidentiality as well as any resulting product from the collaboration in order to protect each party’s intellectual property and rights. It was also necessary that any work undertaken by students and academics needed to be documented as per the company’s requirements and agreement, for instance, in terms of publishing the research findings. Documentation also helped in moving towards registering patents and intellectual property rights apart from producing something that was repeatable. This can also be sustained and monitored through regular review meetings, mutual adoption of goals as the collaboration progressed as well as updates, with a clear and mutual

60

4  Academia and Industry Collaborations: A Research and Professional Perspective

vision derived from the objectives. The success of the collaboration in this regard was hinged on the ability of the team (academia and industry) to work together for a common and beneficial goal. That way, it was helpful to learn from each other and from any mistakes that may be made in the process. As the industrial revolutions evolved, there was an even greater need for collaborations between industry and academia in general but in an interdisciplinary nature, hence the importance and need for teamwork among academics and industrialists before engaging each other. Collaborations within academia and beyond were a vital requirement to fulfil the adage ‘The whole was more than the sum of its parts’ (Bartolomeo et al. 2015).

4.2  Collaborations in Southern Africa The collaborations among tertiary institutions in Southern Africa date back to the time institutions were established from colleges of universities in Europe, but at that time, it was confined to bilateral arrangements, initially between the parent institution and the college and later between the various institutions in the region through conferences (Zinyemba 2010). When the colleges became full-fledged and independent universities, resources became scarce as most of the laboratory equipment left by the parent institutions could not be well maintained, leading to ageing, obsolescence and, in some cases, underutilised (Nyemba et al. 2017). This led to the establishment of the Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) by collaborating tertiary institutions offering engineering education in Eastern and Southern Africa, supported by the Swedish International Development Cooperation Agency/Swedish Agency for Research Cooperation (Sida/SAREC) of Sweden, followed by the Enriching Engineering Education Program (EEEP) and the Higher Education Partnerships for Sub-Saharan Africa (HEP SSA) funded by the Royal Academy of Engineering as articulated in Chap. 1. The emphasis on the latter interventions was meant to bring industry closer to academia through problem-based learning and industrial projects for both staff and students. Following the introduction of industrial attachments to undergraduate engineering studies as a mandatory requirement for the new curricula in most universities in Southern Africa, there was an increased demand for industry and academia to collaborate and work together.

4.2.1  Shortages and Mismatch of Skills in the Region As aforementioned in Chap. 1, the world faced a persistent shortage of engineers, technologists and technicians for various reasons depending on what part of the world, industrialised or industrialising. The large proportion of the Southern African Development Community (SADC) region is industrialising while a few countries like South Africa and Namibia are semi-industrialised. However, the general ratio

61

4.2  Collaborations in Southern Africa

Graduates

University of Zimbabwe Engineering Graduation Statistics 200 180 160 140 120 100 80 60 40 20 0

Civil

Electrical

Mechanical

Metallurgy

Mining

Geoinformatics

Departments

Fig. 4.1  University of Zimbabwe engineering graduation statistics. (Source: Nyemba (2018))

prevailing in the region was one engineer for a population of 10,000, way below that of industrialised countries at 50 engineers for the same number (UNESCO 2010). Even so, the benchmark figure of 50 was still low. In addition, the number of technicians had also significantly gone down following the upgrading of polytechnics to universities. The information obtained from collaborating institutions and industry partners in the region revealed that for every engineer or technologist, there were one or two technicians instead of the recommended 1:5 (Mohamedbhai 2017). As such, even though the number of engineers was still low, it was even more so for the technicians. The challenge in Southern Africa was also compounded by the mismatch of skills between those imparted to students and the skills that industry required, hence the need for the close collaboration between industry and academia. Figure 4.1 shows a graph of graduation statistics of one of the collaborating institutions, the University of Zimbabwe, from 1992 to 2017 showing an average of about 120 engineers graduating from all the 6 disciplines every year (Nyemba 2018). While the statistics revealed an average of 120 graduate engineers per year, this translated to 1 engineer for every 25,000 (assuming the same output for the 4 institutions offering engineering education in Zimbabwe) for a total population of 12 million people then, way below the expected ratio. The drop in the numbers between 2010 and 2014 was due to the recession in Zimbabwe as well as the global financial crisis of 2008 that saw a lot of potential engineers dropping out of university and settling elsewhere. To some extent, the state of laboratories and equipment therein at that time also contributed to the low numbers and drop outs as some students were demotivated. However, the number picked up from 2015 and has been on a steady rise but a lot still needed to be done to more than double the number of engineers. The crisis also resulted in the suspension of some of the programmes during the same period (UZ 2013). Another major contributing factor to the shortage of engineers in the SADC region and in Zimbabwe in particular, was the economic situation that caused a

62

4  Academia and Industry Collaborations: A Research and Professional Perspective

‘brain drain’ and migration of engineers to greener pastures within the region and beyond (Nyanga et al. 2012). Although the situation was expected to remain stable in the semi-industrialised South Africa, the numbers of expected engineers in that country remained low but comfortably closer to the expected ratio compared to the other countries in the region (Lawless 2017). Undoubtedly, the state of affairs during and after the period of recession also meant that the development of curricula could not be done in tandem with rapid changes in technology, hence partly contributing to the mismatch of skills between what tertiary institutions produced and what the industry required. These challenges were some of the main motivations for the interventions by Sida/SAREC and the Royal Academy of Engineering in supporting the institutions in Southern Africa through NUSESA, EEEP and HEP SSA as articulated in Chap. 1. Through the various initiatives, sharing and disseminating information was key to enhance best practices in the training of future engineers by a stimulation for raising the standards of engineering education within the region. The assessments of the impact of interactions between industry and academia were thus done through the outcomes of the secondments of academics to industry in terms of access to modern equipment and technology, effectiveness of the professional training by both technicians and academics as well as the levels of engagement and usefulness of the knowledge-sharing workshops. These aspects were drawn from the hypothetical conundrums and challenges established in the introductory sections and problem statement for this book. While these initiatives were noble and greatly assisted the several institutions, they could only be sustained during the period of support, purportedly due to lack of continuity plans and buy-ins from all stakeholders, hence the need for a holistic approach in order to sustain the activities and bringing industry closer to academia.

4.2.2  Knowledge-Sharing Workshops One of the key deliverables for initiatives such as NUSESA, EEEP and HEP SSA was for stakeholders to periodically meet and share experiences and knowledge in order to enhance the training and education for future engineering professionals. This was based on lessons drawn from partners in the industrialised world such as the University of Leicester, University College of London and Imperial College of London, on the philosophy, ‘knowledge shared is knowledge gained and multiplied’ as well as a ‘problem shared is a problem halved’ (Runhaar and Sanders 2015). One of the objectives for this book and indeed the work done in conjunction with the three initiatives was to analyse and establish the effectiveness of knowledge sharing, professional training and secondment of engineering academics to industry, in order to enhance the quality of engineering education in Southern Africa in terms of the university academics’ confidence in dispatching their duties as lecturers and technicians’ ability to adequately demonstrate and lead in students’ laboratory work. The workshops, seminars and conferences were held in conjunction with professional

4.2  Collaborations in Southern Africa

63

and regulatory bodies such as the Zimbabwe Institution of Engineers (ZIE) and the Engineering Council of Zimbabwe (ECZ). The participants were drawn from participating tertiary institutions, industry partners, policy-makers from the Government of Zimbabwe through the Ministry of Higher and Tertiary Education, Innovation, Science and Technology Development, industry partners, as well international partners which included donors and tertiary institutions from the United Kingdom. The ZIE played a key role for the link between academia and industry and some of the workshops were actually jointly organised and facilitated by them. Table 4.1 summarises the NUSESA, EEEP and HEP SSA workshops, seminars and conferences held from 2001 to 2020 effectively during different periods and excluding the expanded HEP SSA which was in progress at the time of writing this book. Table 4.1  Knowledge-sharing workshops and conference Dates Oct 2001

Details NUSESA

Venue Bagamoyo, Tanzania

Number of participants 175

Feb 2005

NUSESA

Jinja, Uganda

125

Mar 2005

NUSESA

Maputo, Mozambique

168

Jun 2005 Oct 2005 Sep 2013

NUSESA NUSESA EEEP & ZIE

Harare, Zimbabwe Cape Town, RSA Great Zimbabwe

130 5 200

Nov 2013

EEEP Workshop EEEP Workshop

CUT, Zimbabwe

54

UZ, Zimbabwe

62

UZ, Harare, Zimbabwe

63

Wild Geese, Harare

95

Harare, Zimbabwe

63

Vic Falls, Zimbabwe

220

Wild Geese, Harare

66

Mar 2014

Oct 2014 Nov 2014

Nov 2014 July 2015

Oct 2019

EEEP Seminar EEEP Workshop

EEEP Seminar EEEP Conference

HEPSSA Workshop

Participants UDSM, UEM, MU, UZ Engineering MU, UDSM, UEM, UZ Engineering UEM, UDSM, MU, UZ Engineering UZ Engineering Staff UDSM, UEM, MU, UZ UZ, CUT, Industry & ZIE members CUT, HIT, NUST, UZ & Industry UZ, HIT, NUST, CUT, UB, PON, UEM, UL, Industry and Govt. of Zimbabwe UZ Staff and Industry UZ, HIT, NUST, CUT, UB, PON, UEM, UL, Industry and Govt. of Zimbabwe UZ, UL and Captains of Industry All Participating HEIs from Eastern and Southern Africa, Industry and Govt. of Zimbabwe UZ, CUT, HIT, Industry

Key: UZ University of Zimbabwe, UL University of Leicester, UEM Universidade Eduardo Mondlane, UDSM University of Dar es Salaam, MU Makerere University, CUT Chinhoyi University of Technology, HIT Harare Institute of Technology, UB University of Botswana, PON Polytechnic of Namibia

64

4  Academia and Industry Collaborations: A Research and Professional Perspective

The earlier workshops conducted under the auspices of the Sida/SAREC-funded NUSESA were confined to only four tertiary institutions offering engineering education in Eastern and Southern Africa, that is, the University of Dar es Salaam (Tanzania), Universidade Eduardo Mondlane (Mozambique), Makerere University (Uganda) and the University of Zimbabwe. In addition, the collaboration of these institutions, based on the support from Sida, was focussed on Innovation Systems and Innovative Clusters in Africa, with little or no interactions with industry. The NUSESA initiative under the broad aspects of the Innovation Systems and Innovative Clusters focussed on the procurement, use, sharing and maintenance of laboratory and scientific equipment within the four collaborating universities. Unfortunately, the support from Sida for the clusters programme ended in 2006 and so did the NUSESA initiative, primarily due to lack of buy-in from local governments and industry to support the continuity of the programme. The Royal Academy of Engineering–funded EEEP was established after extensive consultations in Eastern and Southern Africa involving the same institutions but with additional ones that were split into two consortiums, one for Southern Africa comprising the University of Zimbabwe as the hub and spoke institutions, National University of Science and Technology, Zimbabwe (NUST Z), Chinhoyi University of Technology (CUT), Harare Institute of Technology (HIT), University of Botswana (UB), Polytechnic of Namibia (PON) and Universidade Eduardo Mondlane (UEM), while the Eastern Africa consortium comprised the University of Dar es Salaam as the hub and the spokes were Makerere University (MU) and the University of Nairobi. The major difference from NUSESA was that EEEP had industry partners. The several workshops and seminars held from 2013 to 2015 were aimed at sharing knowledge and dissemination of information to enrich the quality of engineering graduates as well as dispatching relevant skills, hence the inclusion of industry in the EEEP collaborations. Some of the discussions at these workshops revolved around collaborative and regional research, industry’s expectations from academia in terms of quality and skills of graduates as well as provision of solutions to industry challenges and operations. The workshops revealed that challenges such as procurement, use and maintenance of equipment was not unique to one institution but almost all faced the same challenges and thus the workshops became an excellent platform to craft solutions for these challenges in conjunction with industry. Apart of the high attrition rates for both engineering academics and practising engineers in the region as a whole, most of the tertiary institutions had inadequacies in laboratory equipment. The interactions with industry practitioners created a perfect opportunity to share resources between academia and industry.

4.2.3  Sharing of Resources Under Distress The global financial crisis of 2008 forced many professionals to flee their countries for greener pastures. This occurred within the region where they moved from low-­ income countries, such as Zimbabwe, Zambia and Malawi, to semi-industrialised or stable economies such as South Africa, Namibia and Botswana. There was also

4.2  Collaborations in Southern Africa

65

general movement of professional engineers from the region to industrialised countries such as Australia, UK and mainland Europe. While the movement within the region and abroad was encouraged for the mobility of engineers to acquire new experiences and insights, the real reason was monetary and this resulted in the depleted number of engineers within the region. Faced with such crisis as a region, the hardest hit were tertiary institutions who were left with either very young and inexperienced academics or very old and retired academics who would have been called back to cover the deficits. This forced some of the institutions to make use of fresh graduates with no experience in industry or academia, to train future engineers. This was surely not acceptable and hence one of the focus areas for the workshops was to establish the strengths of each participating institution with a view to draw up a database that would enable sharing of resources, both human and equipment. This became more pronounced in the expanded version of the HEP SSA scheme where the establishment of Centres of Excellence was added as a standalone objective, the idea being, even if the economic situation was normal, it would be ideal to share resources to avoid duplication and underutilisation of equipment. Excess resources, if available, could be channelled to other better uses like R & D, innovation hubs and technology parks. One of the key deliverables under the Centres of Excellence was Doctoral Training Centres in which HEIs use the facility to develop their academics to higher levels such as PhD. The seminars on the other hand were small groupings that were mainly held at particular institutions where the main objective for these was to receive feedback from engineering academics who would have been seconded to industry, on what they would have learnt, how it helped to improve their lecturing duties and what problem-based learning projects they established for their students. The enthusiasm at these seminars was quite evident that the academics benefitted a great deal and this was one of the motivations for the expanded HEP SSA scheme with more players, particularly those providing financial support. The other seminars involved practising engineers providing motivational presentations to both engineering academics and students, thus increasing the interactions between academia and industry. In the process, the University of Zimbabwe in collaboration with all local tertiary institutions offering engineering education, the government, parastatals, industry and the professional body, the ZIE developed the first ever documented 5-year research agenda (2014–2019) at one of the workshops held in 2014. One end- of- programme conference was held in Victoria Falls, Zimbabwe in July 2015. This drew participation from both hub and spoke tertiary institution consortiums from Eastern and Southern Africa, industry from both regions as well as professional and regulatory bodies and policy-makers from government. The conference, which also included cooperating partners from the United Kingdom, the University of Leicester and the Royal Academy of Engineering, was primarily to wrap up the EEEP projects in both regions whilst mapping the way forward for the future, in which the HEP SSA scheme emerged.

66

4  Academia and Industry Collaborations: A Research and Professional Perspective

4.2.4  Focus Areas of Discussion and Key Resolutions Although the workshops and seminars were meant for specific deliverables, knowledge sharing and secondment report backs, respectively, they also covered a diverse range of issues which were mainly drawn from different levels of participants and their experiences. Table  4.2 summarises some of the key issues covered against which it is shown which organisation played a key role in facilitating the debate. This was the beginning in formulating the required systems thinking elements for the models that were developed and discussed in latter chapters. The resource organisations in Fig. 4.2 constituted the key stakeholders for these models before the interconnections and objective functions were established. At this stage of the book, the links between the knowledge-sharing focus areas of discussion and the responsibilities in terms of the resource organisations as shown in Fig. 4.2 were still generalised as the systems thinking models started to emerge. As a matter of fact, almost all resource organisations in Fig. 4.2 had something to do with most of the focus areas of discussion but these have been left out or generalised to the organisation most likely to have the biggest influence in the focus area. This will be handled in greater detail with the intricate connections and objective functions in latter chapters containing the detailed systems thinking models. The systems thinking objective functions that were generated from the interconnections were derived from the focus areas of discussion. For the various models to operate sustainably without any interruptions, each of the resource organisations needed to be considered as a single cog in a gearwheel in such a way that if one of the cogs broke, the gear would not function properly and thus the machine would break down. The development of the models and indeed the interconnections between them should be sufficiently robust such that in the event of any of the cogs breaking, the system should still be capable of achieving the set objective functions,

Table 4.2  Key resolutions, purposes and stakeholders Key Resolutions Network of universities and industry Regional accreditation of programmes Regional standardisation of curricula Stakeholder engagements Regional staff and student exchange Sharing resources International links and collaborations

Purpose Collaboration and regional research Cooperation and standardisation Mobility of professional engineers Improvements in interactions Student and staff mobility in Network Cost reductions and specialisations Technology transfer and best practice

Stakeholders Universities and industry Universities, regulatory bodies, government Universities, regulatory bodies, professional institutions, government Universities, industry, governments, professional & research institutions Universities, industry, government Universities, industry Universities, cooperating partners, industry

67

4.2  Collaborations in Southern Africa

Focus Areas

Resource Organisations

Research for Development

Problem Based Learning &

Universities

Industry

Outcome Based Curricula Industrial Training &

Professional

Internships

Bodies

Continuous Professional Development

Funding and Support for Innovations

Regulatory Bodies

Policy-Makers

Accreditation of Engineering

Cooperating

Programs

Partners

Developments in Engineering Technology

Patenting and Intellectual Property Rights

Research Institutes African Regional & Intellectual Property Organisation

Fig. 4.2  Focus areas of discussion and responsibilities

albeit in a modified form. The major requirement was therefore to ensure that all the responsible resource organisations (stakeholders) bought into the system to take full ownership, albeit in different proportions. The workshops and seminars did not only identify key objective functions as outlined in Fig. 4.2 but went further to formulate key resolutions and drivers to ensure that the noble initiatives continued to operate. Some of these resolutions have been implemented by the various stakeholders, with phenomenal outcomes such as the Professorial Chairs and industrial liaison office. Table  4.2 formed the foundation of the models with key resolutions, purposes (objective functions) and stakeholders (elements).

4.2.5  Foundations for Systems Thinking Modelling The key resolutions, objective functions and stakeholders in Table 4.2 provided the broad perspective for the specific expectations from the various stakeholders. Essentially, the collaborations and workshops were meant to answer the following

68

4  Academia and Industry Collaborations: A Research and Professional Perspective

Table 4.3  Systems thinking elements, functions and purposes Stakeholder (element) Universities

Research institutions Industry Governments Regulatory bodies and professional institutions Cooperating partners (Donors)

Expectations (functions and purpose) Engineering academics to be appropriately trained and exposed to modern technology in order to impart relevant skills to students Employ graduates from universities tasked with solving problems from governments and industry Require well-trained graduates to run their companies in profitable and efficient ways Rely on taxes derived from profitable and well-functioning companies Regulate the training of engineers and accredit HEI programmes that are well designed and appropriate Provide financial support and facilitate collaborations with industrialised countries

questions which were then translated to the basic requirements of the elements and objective functions of the systems thinking models. • Role of universities in developing skills to match industry needs • Interventions by policy-makers for enabling environments to develop human resources • Industry’s contribution in supporting universities to develop the skills they require to drive industry • Professional bodies’ mediation to narrow the gap between industry and academia • Regulatory bodies’ Regional Qualification Frameworks for accreditation and mobility of engineers • Motivation and promotion of innovations by academics and students up to commercialisation • Lessons to be drawn from the industrialised world through international partners The models were developed on the premise and assumption of the more detailed objective functions and purposes as shown in Table 4.3, the base on which the models were developed, underpinned by their roles and relationships in the detailed interconnections that were developed.

4.3  Industrial Secondments Following the collaboration among the four institutions in Mozambique, Tanzania, Uganda and Zimbabwe under the broad Innovation Systems and Innovative Clusters through which the NUSESA scheme operated, there was a realisation by the institutions that it was important to bring industry on board as a key stakeholder, apart from spreading the collaboration to other institutions within the region. This was premised on the challenge that equipment used by tertiary institutions was obsolete, old or underutilised, thereby producing graduates who were qualified as engineers

4.3  Industrial Secondments

69

but unemployable. This was mainly due to the mismatch of skills between those produced by universities and those that industry required, brought on by the use of old and conventional equipment in the university workshops and laboratories. One way in which this problem was resolved was to create the facility for seconding engineering academics to industry, thereby exposing them to modern equipment and technology to enable them to impart appropriate skills onto future engineers. Through secondments, the engineering academics also created opportunities for problem-based learning for students, industrial-based projects as well as opportunities for consultancy work through resolving industry challenges. In addition, most universities in this collaboration introduced the 1-year industrial attachment for students, which also helped in getting the students to be more employable after graduation, based on the familiarisation that they went through. Apart from academic requirements for the attachment, a number of students under attachment were offered industry-based learning (on the job training) while earning some allowances. However, this was only in a few of the cases as most of the companies could not afford to pay the students. In conjunction with professional bodies such as the Zimbabwe Institution of Engineers and the broad theme of ‘Engineers addressing economic and engineering education recovery’, following the global economic recession of 2008, the work in this book utilised a strategy of seconding engineering academics and attachment of students to ‘lead them to where the technology was’ in order to expose them to modern practices and systems in industry, in preparation for their future employment as well as academics’ consultancy and research opportunities. For the students, a complete year of attachments was set aside for most of the collaborating universities and for the academics, the secondments were designed to use mid-­ semester breaks as well as sabbatical leaves. The major challenge, especially during the early parts of the initiatives, was to secure enough places for the students and academics. However, the roping in of more industry partners into the collaboration, created opportunities and facilitated placement of student and academics. This demonstrated the need for industry to work very closely with academia but more so, it was also based on the outcome and impact of the various projects carried out in industry by academics as detailed in Chap. 6. The EEEP involved a small selection of industry partners in Zimbabwe, who accommodated both students and academics. The spoke institutions within Zimbabwe and regionally were mainly involved in the workshops and seminars but did not have any students or staff on attachment or secondment. The companies were drawn from the various disciplines on offer at the University of Zimbabwe and these ranged from the traditional Civil, Electrical and Mechanical Engineering as well as the more recent additions of Mining, Metallurgy and Land Surveying. This was also based on lessons drawn from successful ventures such as in Malaysia (Ahmad and Rashid 2011) where it was important to second academics to suitable companies related to disciplines of speciality. At least one academic or technician was seconded to each of the companies to carry out projects and research to resolve the companies’ challenges while students on attachment assisted in collecting data for that purpose. Although the Malaysian case made use of a stipulated 2-month

70

4  Academia and Industry Collaborations: A Research and Professional Perspective

Table 4.4  Summary of secondments and attachments under EEEP Company Asea Brown Boveri Zimbabwe Platinum Mines City of Harare, Surveying. Craster Foundry & Engineers Zimbabwe National Water Authority Jeffares & Green Consulting Engineers, South Africa Zimbabwe Platinum Mines Deven Engineering Adam Bede Craster International Zimbabwe Platinum Mines Scanlink TOTAL

Period Jul – Aug 2013 Jul – Aug 2013

Duration/ days Academics Technicians 62 0 1 54 2 2

Students 0 0

Total 1 4

Jul – Aug 2014

40

0

1

0

1

Jul – Aug 2014

46

1

0

0

1

Jul – Aug 2014

40

0

3

0

3

Jul – Aug 2014

40

1

0

0

1

Jul – Aug 2014

46

2

1

0

3

Aug – Sep 2015 Aug – Sep 2015 Sep – Oct 2015

40 40 46

1 1 1

0 0 0

1 2 2

2 3 3

Oct – Nov 2015

40

1

0

3

4

Nov – Dec 2015 40 2013 – 2015 534

1 11

0 8

1 9

2 28

attachment, the approach adopted for the EEEP was based on logistics and availability of places and facilities for placement and the periods ranged from 6 to 10 weeks. Table 4.4 shows a summary of the companies involved, duration and number of academics, technicians and students involved. Although the EEEP had budgeted for and received support from the Royal Academy of Engineering to cater for approximately 6 academics and 5 technicians, the in-kind contributions by industry partners enabled the increase in the number of academics to 11 and technicians to 8 as well as 9 students who had not been catered for in the budget. The in-kind contributions included accommodation and meals particularly for companies that were outside Harare. The report back seminars and workshops as listed in Table 4.1 were enlightening and the enthusiasm displayed showed how academics and technicians had benefitted. In addition, student online evaluations at the University of Zimbabwe revealed that there was a marked improvement in the delivery of lectures particularly by those who were seconded to industry. While the EEEP had a few companies on board and was mainly localised in Zimbabwe, the HEP SSA scheme which was a revised version of EEEP brought in

4.3  Industrial Secondments

71

Table 4.5  Summary of secondments under the HEP SSA scheme Company SINET Africa

Location Harare, Zimbabwe

PPC Zimbabwe Harare, Zimbabwe Zimplats Selous, Zimbabwe Maputo, Maputo Thermal Power Mozambique Station Virgo Energy Windhoek, Investments Namibia Design Team Consultants Zimbabwe Fertiliser Company Chloride Batteries

Harare, Zimbabwe Harare, Zimbabwe Harare, Zimbabwe

Johannesburg, MikroDev Southern Africa South Africa Turnall Holdings Ltd

Bulawayo, Zimbabwe

Distributed Power Africa

Harare, Zimbabwe

Specialisation Renewable Energy

Period Jan-­ Mar 2020 Cement Jan-Feb Manufacturing 2020 Mineral Jan-Feb Processing 2020 Power Mar-­ Generation Apr 2020 Renewable Jan-­ Energy Mar 2020 Civil Engineering Jan-Feb Consulting 2020 Fertiliser Feb-­ Production Mar 2020 Battery Feb-­ Manufacturing Mar 2020 Industrial Jan-­ Automation Mar 2020 Asbestos Feb-­ Manufacture Mar 2020 Renewable JanEnergy Mar 2020

Academic’s Duration Institution 7 weeks University of Zimbabwe 6 weeks University of Zimbabwe 5 weeks University of Zimbabwe 8 weeks Universidade Eduardo Mondlane, Mozambique 7 weeks Namibia University of Science and Technology 8 weeks University of Zimbabwe 7 weeks Harare Institute of Technology, Zimbabwe 4 weeks Chinhoyi University of Technology, Zimbabwe 8 weeks University of Johannesburg 8 weeks National University of Technology, Zimbabwe 8 weeks University of Zimbabwe

more players in tertiary institutions from 6 to 9 and industry partners from 5 to 14 which were no longer localised in Zimbabwe but spread within the region as shown in Table  4.5 where one academic was seconded to each of the companies listed. However, some of the industry partners are not listed in that table as they had not yet taken academics on board. The secondments and results thereof were used as the attributes for the systems thinking sub-models as discussed in latter chapters. These were mainly the access to modern equipment and technology, the need to revitalise policies on smart procurement, use and maintenance as well as sharing of equipment between industry and academia, the need for standing policies on secondments and attachments in such a way that placements can be done with ease. Figure 4.3 summarises the outcomes and attributes of engineering academics following the engagements with industry, particularly after secondments and workshops. This comprised of the secondment area/activity linked to outcomes and attributes and eventually to skills acquired and

72

4  Academia and Industry Collaborations: A Research and Professional Perspective

Activity

Industrial Secondments

Outcome/Attribute

Exposure to Modern Equipment & Technology

Skills/Competencies

Appropriate Experience & Training of Future Engineers

Confidence in Lecturing Access to Modern Equipment

Networking with Engineers

Industry Based Projects PBL & IBL

Practical Research R&D Solutions

Consultancies and Contracts

Strengthening AcademiaIndustry Links

Appropriate Technology

Industrial Engagement

Practical Problem Solving

Artefacts & Prototypes Joint Research with Industry

Research and Scholarship Research Publications

Fig. 4.3  Connecting activities, attributes and competences

competences gained. These were derived mainly from the feedback seminars as well as reports that the seconded staff submitted, coupled with the end of semester evaluations by students.

4.4  Continuous Professional Development The rapid and dynamic changes in technology, particularly the transition from the third to the fourth Industrial Revolution demanded that professionals, especially in science, engineering and technology, were kept abreast and in tandem with the changes (Perez-Foguet et al. 2018). This included both engineering academics and practising engineers in industry. Professional institutions and regulatory bodies such as the Zimbabwe Institution of Engineers and Engineering Council of Zimbabwe have now made it mandatory for all engineers, technologists and technicians to accumulate a certain number of Continuous Professional Development (CPD) points annually in order to keep their practising licence active (Engineering Council of Zimbabwe 2012). In Zimbabwe, this regulation has actually been gazetted as a statutory instrument that requires engineers to accumulate a minimum

4.4 Continuous Professional Development

73

of 15 CPD points annually through various activities such as attendance or offering short CPD courses, lectures or publication of research. This has become typical practice for the other countries in the region. For the EEEP and HEP SSA scheme, this was a two-pronged process in which engineering academics needed access to modern equipment and technology while practising engineers in industry had the equipment but needed to be kept abreast with the current trends and developments through academics’ knowledge base. This required carefully crafted and innovative systems in which both parties can capitalise, hence the need to bring industry closer to academia to achieve these objectives. The financial support granted by the Royal Academy of Engineering included a budget and provision for continuously upskilling engineering academics in terms of CPDs particularly on refresher courses offered by practising engineers on specialised equipment. Although the grant did not cater for practising engineers in industry, provisions were included for engineering academics to offer refresher courses to this group of professionals, hence the two-pronged approach. Following the end of the NUSESA scheme under the blanket umbrella of the Innovation Systems and Innovative Clusters, an end of programme assessment revealed that most laboratory equipment at participating institutions from Eastern and Southern Africa were relatively old, obsolete, lacked maintenance and, in some cases, underutilised due to lack of expertise (Nyemba et al. 2017). When the engineering institutions were weaned off from being colleges of universities in Europe and they became independent, some managed to continue using and maintaining their laboratory equipment but the majority could not afford this due to low financial capacity and depleted grants from their governments. Although the University of Zimbabwe successfully procured state-of-the-art computer numerically controlled (CNC) machines for students’ workshops and laboratories, the major challenges were in the ability to make use of them, let alone maintain them, hence the need for training of academics and technicians who would in turn impart those skills to students in preparation for their future employment. To avoid underutilisation of such machines and also to ensure that they were not just ‘white elephants’ lying idle, the University of Zimbabwe in collaboration with one of the spoke institutions, the Harare Institute of Technology, arranged for comprehensive training of academics and technicians since HIT already had a full-­ fledged CNC laboratory and competent staff. In that regard, a total of four academics and six technicians underwent professional training and this has enabled the CNC machines procured at UZ to be fully utilised for training students. The capacity to source and procure equipment and the ability to use and repair the machines sustainably when necessary, together with the continuous development of personnel were the key parameters that were used in the development and formulation of the systems thinking sub-models in Chap. 12. The ultimate universal model to build capacity sustainably and in the process bridging the gap between industry and academia was subsequently derived from the sub-models.

74

4  Academia and Industry Collaborations: A Research and Professional Perspective

4.5  Project Resources and Equipment Due to the different economic environments in the region, SADC tertiary institutions had varying capacities in terms of their abilities to procure state-of-the-art equipment in terms of requirements and the response to the fourth Industrial Revolution vis-à-vis the rapid and dynamic changes in technology. While industrial partners had a fairly reasonable collection of such equipment for their operations, tertiary institutions generally lagged behind, thus creating a gap between industry and academia. During the course of NUSESA, EEEP and HEP SSA, partner institutions from countries such as the semi-industrialised South Africa, diamond-rich Botswana and the economically stable Namibia showed that they had a fairly good collection of modern equipment as well as the capacity to carry out industry-based projects and consultancies. However, the rest of the countries still employed conventional machine tools and traditional methods in the training of their students. Additionally, the equipment available at these institutions were not adequate to cater for the increasing number of students who enrolled in these programmes, in a bid to meet the demands to address the skills deficit. The other major challenge was to ensure that skills imparted to students were relevant and matched those that industry required. It was against this background that the initiatives focussed on sharing available resources, both equipment and personnel, such that those who had state-of-the-art and modern equipment would avail them to those that did not have, through student and staff exchanges. In response to the need for imparting appropriate skills to future engineers, the strategy adopted in the various schemes was to promote the mobility of engineering academics and students within the region through the network collaboration to ensure that the future engineers were employable within and beyond the region. In the case of a few situations that advanced machine tools required were not available regionally, collaborations with the UK partners made this possible through exchanges at companies such as The Welding Institute (TWI) in Leicester, United Kingdom for the more advanced aspects of welding. However, in general the regionally available resources were adequate to cater for such needs. It was in the same regard that the collaboration sought to establish Centres of Excellence where institutions with strengths in a particular field would focus and offer that to the other partners, both in terms of equipment and human resources. Besides access to modern equipment and technology at the various industry partners, engineering academics, technicians and students created opportunities for consultancies and community service through the familiarisation of the equipment and challenges in company operations. This was evident from the feedback seminars as well as the increased practical and industry-based projects by undergraduate students. It was also an opportunity for academics to supplement their low incomes and for students to raise income from the industry-based learning (IBL). Apart from the opportunities created through these collaborations for the sharing of equipment among tertiary institutions in the region, similar arrangements were also made between individual institutions and industry partners. This was done

4.6  International Backstopping

75

either through purely donated equipment from industry to academia or through public–private partnerships (PPP) or build-operate-transfer (BOT) phenomenon as detailed in Chap. 8. Sharing of such resources was not only economical to companies and institutions in a region that had just suffered the worst effects of the global financial crisis of 2008 but also allowed the sharing of costs for the upkeep of the equipment and to ensure that the equipment was not underutilised. Income generated from consultancies using the shared equipment could also be shared proportionately or simply reinvested to cover costs such as maintenance, spare parts or replenishments. The gap between academia and industry could also be narrowed significantly if ‘win-win’ contracts or coopetition agreements were formulated and operationalised as detailed in Chap. 9. Such arrangements have been carried out successfully in other parts of the world to ensure that equipment is fully utilised to pay itself back in the shortest possible time and to avoid obsolescence (Lwakabamba 2011; Paton et al. 2012).

4.6  International Backstopping Local and regional collaborations have been encouraged and are good for sharing of resources and joint research and publications. However, limiting these to being entirely local or regional may be regarded as shallow and in-breeding unless there was an international flavour for best practices. Because of the need for such broad interactions, many tertiary institutions have actually created dedicated portfolios and offices for internationalisation. To cope with the demands for the fourth Industrial Revolution and the future of technology, it has become increasingly important to keep in tandem with the rest of the world and to tap from the achievements and technologies of world giants, normally domiciled in the industrialised world, where most technology has been pioneered (Borrego and Bernhard 2011). ‘Rubbing shoulders’ with world renowned inventors, innovators and technologists would certainly benefit. The systems thinking sub-model and eventual universal model emphasised the need to develop links between tertiary institutions in Southern Africa and those from industrialised countries such as the United Kingdom. Both the EEEP and HEP SSA schemes funded by the Royal Academy of Engineering made it a strict requirement to access the available funds by first identifying a UK partner in the application, hence the University of Leicester in the HEP SSA scheme and indirectly, the University of London and the Imperial College of London in the EEEP. These institutions played a vital role by bringing on board advanced practices and systems that helped in formulating and appropriately adjusting those in the region. Backstopping is generally referred to as the mentoring and developmental training or operational advisory role by a more experienced expert to another. These can be facilitated locally and regionally. However, in the essence of this book, it referred to the international backstopping role played by the University of Leicester in providing guidance to successfully carrying out the EEEP and HEP SSA projects, ably

76

4  Academia and Industry Collaborations: A Research and Professional Perspective

facilitated by the Royal Academy of Engineering, in itself, a form of international backstopping as well. Apart from the advisory and mentoring role by the UK partner, tertiary institutions in the collaboration also benefitted from the stints at the University of Leicester and its industry partners in the United Kingdom, from where the concept of Centres of Excellence was derived from for implementation in the region. In return, the UK partner also benefitted from applying their skills to solve challenges faced by industry partners in the region while utilising principles and techniques derived from the industrialised world. The international links and partnerships are also beneficial for student and staff exchange where they can gain new skills, perspectives and even be motivated to align their research with that from the industrialised world (Brown et al. 2015). Apart from creating life-long cultural relationships, engineering academics at regional institutions have also been motivated to revitalise their course contents and professional conducts through these engagements. International backstopping in this work was also useful for the High Performance Computer (HPC) that was installed by the Government of Zimbabwe, to fully utilise it for a wide range of computing work such as computational fluid dynamics, finite element analysis and general programming. International assistance has been quite useful in the provision of expertise and requisite software to benefit the local and regional partners.

4.7  Academia Dialogue with Captains of Industry Apart from the usual interactions with practising engineers at the workshops and seminars or during secondments, engineering academics rarely had the opportunity to interact with engineers managing the companies, purportedly due to their busy schedules. As part of the EEEP and HEP SSA schemes, appropriate fora were organised to make such interactions possible with captains of industry. These sessions were aimed at dispelling certain myths about the engineering profession but above all they were meant to get the captains of industry to answer typical questions such as the following: • ‘Are engineers better at management than business professionals?’, • ‘If engineers drive the economies of the world, why are so many shunning the profession and preferring other sectors?’ • ‘What inspires an engineer to have job satisfaction and remain within the profession?’ These are clearly subjective but debatable questions. Some of the answers ranged from perceptions of low rewards (Harrison 2012) to self-actualisation (Jerome 2013). Apart from being purely motivational for the younger and inexperienced engineering academics, the interactions with captains of industry were formulated and developed around these key questions. Based on the disciplines available at most of the partnering institutions, one captain of industry representing each of the disciplines was carefully selected to make presentations regarding the pros and cons of

4.7  Academia Dialogue with Captains of Industry

77

Table 4.6  Dialogue with captains of industry (engineering experts)

Expert Expert 1 Expert 2 Expert 3 Expert 4 Expert 5

Basic qualification Engineering metallurgist Electrical engineer Civil and water engineer Mechanical engineer Mining engineer

Expert 6 Land surveyor

Current occupation Vice chancellor Chief executive officer Engineering consultant Technical director General manager Director (Former surveyor general)

Years in engineering service 35

Organisation Chinhoyi University of Technology Engineering Council of Zimbabwe Consultant

45

Delta Beverages

20

Buchwa Iron Mining Company Africa Surveys Zimbabwe

25

40

25

their particular disciplines, the dos and don’ts but ultimately focussing on encouraging the young engineers and academics not to shun and leave the region or leave the profession. These sessions were both formal and informal to ensure that the information extracted was totally representative of the various disciplines. Table  4.6 shows a summary profile of the six captains of industry for a typical dialogue that was held at the University of Zimbabwe in 2014. The expertise was drawn from Civil, Electrical, Mechanical, Metallurgical and Mining Engineering as well as Geoinformatics and Land Surveying. Clearly, the levels of expertise of the six selected captains of industry, in terms of their levels of appointment and number of years in engineering service provided some evidence of their faith in the ‘indispensable’ profession apart from demonstrating that engineers can equally run and manage businesses just like any other professional, in areas spanning from engineering, manufacturing, mining and mineral processing, academia, consultancy and other business sectors in influential decision-making positions. Their passionate presentations were evidently inspirational to the young and inexperienced engineering academics. In addition to the dialogues with experts, the EEEP and HEP SSA also facilitated the engagement of independent fellows to monitor, evaluate and offer expert guidance on the schemes. The first was an academic from the University of Leicester who doubled up as a consultant for Rolls Royce in England and the other was a General Manager for a Zimbabwean mining company, who also doubled up as a part-time academic at the University of Zimbabwe. They both used their wide industrial and academia experience to support the development of new and modern curricula and teaching methods in tandem with current industrial trends. The interactions between academia (students and staff) and the captains of industry as well as visiting fellows boosted the morale for students and engineering academics, evidenced by the number of industry-based innovative projects that have been presented annually since 2014 at the Zimbabwe Institution of Engineers

78

4  Academia and Industry Collaborations: A Research and Professional Perspective

national engineering student awards and competitions. The following key resolutions were derived from the presentations and interactions with captains of industry and visiting fellows and used as input to the development of systems thinking sub-­ models in Chap. 12. • Engagement with the Governments and Industry to scale up student industrial attachments • Bankable proposals for R&D and consultancies to enable generation of income from industry • Lobbying engineers in influential positions to support engineering education • Team building and entrepreneurship skills among students to source funding for projects • Enhancement of non-examinable courses and activities such as interactions with captains of industry • Strategies to enhance information dissemination to be encouraged through journals and conferences • Increased platforms for sharing information, knowledge and experiences • Improved engagement with industry for student career guidance and opportunities • Collaborations with other institutions for joint research and sharing of resources

4.8  Conclusion Through the EEEP and HEP SSA schemes, there were increased interactions between industry and academia which resulted in a number of achievements such as the awarding of a Professorial Chair for the University of Zimbabwe, fully funded by one of the mining and mineral processing companies. The University of Zimbabwe’s first ever research agenda was formulated and documented and the university employed a full-time Industrial Liaison Officer to provide a constant link between academia and industry. Several workshops and seminars were held during the course of the schemes and an end of the EEEP conference brought together participants from Eastern and Southern Africa in 2015. Professional training for the use of state-of-the-art machine tools was conducted for engineering academics and technicians in collaboration with one of the partner institutions that had such facilities. More secondments to industry were achieved above the budgeted ones due to in-kind contributions by industry partners. Formal and informal dialogues were also organised and held with engineering experts in influential positions in their organisations as well as with visiting fellows who were engaged to provide guidance and advice to the schemes. This chapter provided details of these activities and events but more importantly, the key resolutions that were formulated in the interactions and workshops to form the foundation for the systems thinking elements, objective functions and purposes for the systems thinking sub-models, the detailed interconnections of which will be handled in latter chapters of the book, with the ultimate objective of bridging the gap between academia and industry through engineering change management using systems thinking.

References

79

References Ahmad, M.  F. B., & Rashid, K.  A. A. (2011). Lecturers’ industrial attachment programme to increase lecturers’ soft skill and technological competencies for global stability and security. Journal of Sustainable Development, 4(1), 281–283. Bartolomeo, P., Vuilleumier, P., & Behrmann, M. (2015). The whole is greater than the sum of the parts: Distributed circuits in visual cognition. Cortecx, 72(2015), 1–4. Borrego, M., & Bernhard, J. (2011). The emergence of engineering education research as an internationally connected field of inquiry. Journal of Engineering Education, 100(1), 14–47. Brown, P. R., McCord, R. E., Matusovich, H. M., & Kajfez, R. L. (2015). The use of motivation theory in engineering education research: A systematic review of literature. European Journal of Engineering Education, 40(2), 186–205. Engineering Council of Zimbabwe. (2012). Statutory Instrument 153 and Engineering Council of Zimbabwe Act CAP 27:22. Harare: Government of Zimbabwe Printers. Gandhi, M. M. (2014). Industry-academia collaboration in India: Recent initiatives, issues, challenges, opportunities and strategies. The Business & Management Review, 5(2), 45–67. Harrison, M. (2012). Jobs and growth: The importance of engineering skills to the UK economy. London: Royal Academy of Engineering. ISBN: 1-903496-92-6, Available: http://www.raeng. org.uk/publications/reports/jobs-­and-­growth. Accessed: 18 July 2016. Jerome, N. (2013). Application of the Maslow’s hierarchy of need theory; impacts and implications on organizational culture, human resource and employee’s performance. International Journal of Business and Management Invention, 2(3), 39–45. Lawless, A., (2017). Numbers and needs in  local government: Where are we now? Civil Engineering, South African Institute of Civil Engineering (SAICE), 2016, 15–26. Lwakabamba, S. (2011). Initiative to build capacity in research and postgraduate training. World Journal of Science, Technology and Sustainable Development, 8(2/3), 241–249. Mohamedbhai, G. (2017). The importance of polytechnics for Africa’s development. International Higher Education, 30, 30–31. Nyanga, T., Mpala, C., & Chifamba, E. (2012). Brain drain: implications for sustainable development in Zimbabwe. Journal of Sustainable Development in Africa, 14(8), 141–153. Nyemba, W.  R. (2018). Modelling the integration of engineering design and manufacture for capacity building and sustainability. Doctor of Engineering (D.Eng.) Thesis (Mechanical Engineering), University of Johannesburg, Available on UJ Institutional Repository. https:// ujcontent.uj.ac.za/vital/access/manager/Repository/uj:31939 using the object handler: http:// hdl.handle.net/10210/293682 Nyemba, W. R., Mashamba, A., & Mbohwa, C. (2017). Equipment maintenance challenges and solutions for capacity building and sustainability in the training of engineers: the case for the University of Zimbabwe. Procedia Manufacturing, 7(2017), 303–308. Paton, R. A., Wagner, R., & MacIntosh, R. (2012). Engineering education and performance: The German machinery and equipment sector. International Journal of Operations & Production Management, 32(7), 796–828. Perez-Foguet, A., Lazzarini, B., Gine, R., Velo, E., Boni, A., Sierra, M., Zolezzi, G., & Trimingham, R. (2018). Promoting sustainable human development in engineering: Assessment of online courses within continuing professional development strategies. Journal of Cleaner Production, 172(2018), 4286–4302. Runhaar, P., & Sanders, K. (2015). Promoting teachers’ knowledge sharing. The fostering roles of occupational self-efficacy and human resources management. Educational Management Administration & Leadership, 44(5), 794–813. UNESCO. (2010). Engineering: Issues, challenges and opportunities for development. Paris: UNESCO Publishing. ISBN: 978-92-3-104156-3. UZ (University of Zimbabwe), (2013), University of Zimbabwe 2013 Annual Report. Harare: University of Zimbabwe Publications

80

4  Academia and Industry Collaborations: A Research and Professional Perspective

Zimbabwe Institution of Engineers. (2015). The Zimbabwe Engineer. Vol. 77, No. 1. Available: http://www.wfeo.org/wp-­content/uploads/stc-­anticorruption/The_Zimbabwe_Engineer_-­_ December_2015.pdf. Accessed 12 May 2020. Zinyemba, R. (Ed.). (2010). Academia and the dynamics of transformative leadership: The experience of the University of Zimbabwe in the first decade after Zimbabwe’s Independence (1981-1992). Harare: University of Zimbabwe Publications.

Chapter 5

Problem- and Industry-Based Learning: Research, Theory and Practice

Abstract  Unlike during the earlier industrial transformations, tertiary institutions have adopted a new pedagogy of problem-based learning (PBL) in which practical industry problems are used as case studies in lectures to quicken the students’ understanding of industrial operations. Industry-based learning (IBL) involves the professional placement of undergraduate students for paid work in industry, under the supervision of their lecturers and engineers in industry, in preparation for their eventual employment. The major challenge of this concept in Southern Africa has been the availability of sufficient industry placements to absorb the increased numbers of students from universities and polytechnics. This chapter outlines PBL and IBL as carried out in Southern Africa by academics and students to demonstrate their importance, impact and challenges on how engineers are expected to respond to the demands of the 4th Industrial Revolution. The chapter further outlines how systems thinking and the bridge between academia and industry can help to resolve the challenges faced in placements. Keywords  Critical thinking · Design thinking · Industrial design · Industry-based learning · Problem-based learning · Problem-solving capabilities · Secondments · Synchronisation of PBL and IBL

5.1  Introduction The transition from the 3rd to the 4th and preparedness for the 5th Industrial Revolution have revealed the need for multi-skilled professional and critical thinkers to cope with the rapid and dynamic changes in engineering and technology. To complement the concept of problem-based learning (PBL), tertiary institutions have

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_5

81

82

5  Problem- and Industry-Based Learning: Research, Theory and Practice

introduced mandatory industrial attachments for students for at least a year during the course of their undergraduate studies. At the end of the work-integrated learning, students are expected to submit a project report detailing the work they did and what they learnt, which is marked and contributes credits towards the overall degree aggregate. This idea is similar to the concept of apprenticeships traditionally offered by polytechnics and technical colleges. There has been an increased demand for engineering skills that are responsive to these changes, and this requires a paradigm shift from the traditional classroom teaching and theory to more practically oriented, problem- and industry-based learning (IBL) that inculcates a culture of industrial design thinking. This thrust promotes the development of critical thinking skills and problem-solving capabilities (Andersen et al. 2019).

5.2  Problem-Based Learning 5.2.1  Fundamentals of Problem-Based Learning ‘Dynamic changes and challenges require dynamic solutions’ is an adage synonymous with the rapid changes in science, engineering and technology that equally demand dynamic skills in the provision of solutions to cope with the fourth Industrial Revolution. Problem-based learning is a recent pedagogy adopted by tertiary institutions to model their curricula by placing students in active roles of problem-­ solving that respond to practical and real-world problems (Andersen et al. 2019). Although the practice of PBL differs in different parts of the world, depending on whether they are industrialised or industrialising, the fundamental principles are the same, but probably the difference depends on the level of industrialisation. Specialists and constructivists for early childhood development assert that children and eventually adults learn best when they are actively involved in the construction of their own understanding instead of the traditional approach of being ‘spoon-fed’ with information (Patil and Kudte 2017). This philosophy is supported by many other researchers in the field of human development who have also concluded that practical hands-on experiences in classroom activities are vital for motivation and learning as the students quickly grasp the concepts as opposed to the traditional approach (Gupta and Gupta 2017). The basic and key elements for PBL are: • • • • • •

Learning is more effective in small groups. Learning should be student centred. Lecturers and teachers should simply be facilitators and provide guidance. Use real-life problems as a stimulus for learning. Real-life problem-solving is the appropriate avenue for development. Information and knowledge acquisition is through self-directed learning.

5.2  Problem-Based Learning

83

The emergence and use of problem-based learning, particularly at tertiary institutions, should develop a culture of appreciation and ultimately drive towards multifaceted skills and critical thinking among students, opening the world to the various alternatives in problem-solving. Traditionally, students are directly taught in a group where the lecturer or teacher presents facts that the students are expected to master through practice tests, tutorials or laboratory exercises in order to blend theory and information gathered in class to understand real-world problems. However, with PBL, the approach is slightly different in that it is almost a front-to-back approach where the students, in small groups, are first guided in order to understand potential problems, say, in production or manufacturing and then back to what theory can be used to solve such problems. In approaching the challenges and solving them in that manner, normally students are encouraged to do it in small teams where they present their findings and solutions as a group. Such group design projects particularly in engineering training are now commonplace in tertiary institutions in Southern Africa where students are expected to present group design projects for resolving particular problems. This inculcates a culture of teamwork, reminiscent of what the students should expect to work in teams in industry after graduation. This approach also sharpens the student’s critical thinking, communication and research skills as well as problem-­ solving aptitudes and capabilities before they embark on a full-year industry-based learning project. Table 5.1 shows the fundamental differences of the two approaches of the traditional against PBL, demonstrating an almost back to front and vice versa pedagogies.

Table 5.1  Traditional versus problem-based learning pedagogies Traditional learning Individual centred Aim: Pass examinations Students instructed on what they must learn Students memorise theory in order to pass exam Laboratory exercises/tutorials to solve set problems Normal class sizes (100–200) Normal lecturing/teaching manpower Lecturer role: Linear and sequential pattern Product: Paper qualified professional

Problem-based learning Teamwork centred Aim: Life-long learning Assignment of problem where students also take part in defining Zero in on theory and knowledge required to solve the assigned problem Learn and apply the theory to solve the problem Small groups (10–20) [10–20 groups] More lecturing/teaching manpower Lecturer role: Facilitator Product: Critical thinker and practical problem solver

84

5  Problem- and Industry-Based Learning: Research, Theory and Practice

5.2.2  Designing Problem-Based Learning Pedagogy In coming up with an ideal pedagogy for problem-based learning, the entire curriculum in a course needs to be divided into small units from where the lecturer can decide on typical problems found in industry that students can use as case studies to solve in groups. In doing so, specific problems need to be zeroed in, either those that can be solved through different routes or those that arouse students’ interests. Various methods can be employed for effective communication and learning, such as modern presentation formats, group and individual submissions, research papers etc., that can then lead to appropriate grading of students’ contributions either through peer, self- or lecturer evaluations. The students need to be continuously reminded of the importance and rationale for any activities carried out under PBL. For sensible solutions, the students need to be adequately resourced in terms of computer hardware and software, machine tools where necessary and access to information from the internet. Instead of the usual schedules for classes, enough time must be set aside for group work even if it means allowing the students to do this out of class and then eventually presenting their findings. In order for the students to understand whether or not their solutions are good, feedback sessions to what each group would have submitted, in terms of quality and thoroughness, are important, and these ‘corrections’ actually make the students learn better. While the lecturer’s role in PBL is to provide guidance and facilitation, they are also expected to derive interesting, relevant or topical problems for each of the units in their course. The provision of solutions to problems defined at the end of each group project must demonstrate sufficiency and multifaceted approaches to the problems, enough to probe the students to have an inquiring mind, thus providing different solutions that can be evaluated and implemented. In addition, the problems that are assigned to the students must be broad enough and demanding in such a way that various angles can be explored, thus helping the students to develop more than just the engineering skills but social and environmental ones too. When the lecturer decides on a problem and presents it to the groups, it must be done in a very precise and brief way as possible, to allow the students to probe for any missing information and even get involved in formulating the problem as part of the provision of the solutions. Grouping the students can be done at random but if prior knowledge of their strengths and weaknesses is available; it is advisable to mix the groups in such a way that each group comprises of strong and weak students. That way all the groups will be strengthened and have diversity of skills. Another alternative would be to leave the groups to decide what roles students in a particular group will play, and usually the students know each other bettter, hence it will be easier for them to determine this allocation. In addition to facilitating and guiding, the lecturer would thus also provide a support role to increase the students’ appreciation and blend it with practice through the various stages leading to the eventual solution. The students equally play an important role in shaping PBL pedagogy, apart from the knowledge and skills they acquire in the process through collaborative

5.2  Problem-Based Learning

85

derivation of alternative solutions. The students can brainstorm and split the problem into various segments in order to obtain all the possible information about the group project. Another alternative would be to allow the students to formulate the assigned problem in their own description that would help them understand the challenge better through feedback and interactions with group members as well as guidance from the lecturers. Derived from appropriate thoughts based on experience or theory, the students can generate lists of possible ways to solve the problem using various tools such as the Binary Dominance Matrix (BDM), Pugh method etc. to rank the solutions from where the best or optimal solution can be obtained. BDM is a tool based on the importance of various and weighted objectives, such as ease of manufacture, maintainability etc., that can be ranked to obtain the best solution (Hemelrijk et al. 2005). The Pugh selection method, for instance, is widely employed in engineering design to make choices among competing alternatives where quantitative analysis to rank multifaceted or multidimensional possibilities of a given set of options is carried out. The Pugh method has also been widely used to make investment decisions in business, such as regarding suppliers or product options (Madke and Jaybhaye 2016). It should also be borne in mind that all ideas can be embraced as there is usually no correct or wrong  answer in solving multidimensional challenges, hence the inclusion of various concepts in coming up with decision matrices towards a solution. The final task for students in a PBL would be to generate a report which can be a combination of all the contributions from team members but with group recommendations and conclusion at the end. The report can be presented to the entire class by either one representative of the group or each member presenting what they contributed but ultimately demonstrating the solution to the entire problem. The general format for the report and presentation is usually; problem statement, literature search and background, research questions, process undertaken by the group and individuals, resources utilised, data collected, its relevance and analysis, conceptual designs and solutions obtained, selection of optimal/best solution and reasons, detailed design and analysis of the optimal/best solution, supporting documentation such as surveys and their results graphically displayed, general results, discussion, recommendations and conclusions. During presentations, all group members must be adequately prepared to answer any questions or accept criticisms from the other students. Critical thinking and acquisition of knowledge are important attributes for effective PBL as they enlighten the students on how to make appropriate questions in fine-tuning the problem that would have been set by the lecturer. Variations in individual and group thinking also has to be taken into account throughout the project execution. In addition to the provision of the required solution, the reports that are submitted by students should also demonstrate what they would have learnt and how they best feel the knowledge and skills they would have acquired can be applied in real practice in industry. That way, it will be easier and also possible to allocate marks for evaluating the implications and possible applications in other spheres external to the problem set.

86

5  Problem- and Industry-Based Learning: Research, Theory and Practice

5.2.3  Implementation of Problem-Based Learning Most tertiary institutions around the world, inclusive of the marginalised Southern Africa, which is still largely going through industrialisation, have made attempts to implement PBL. Shifting from traditional to problem-based learning requires the change of mindset where the role of the lecturer becomes more of a facilitator and guide as opposed to the linear and sequential patterns that students traditionally followed. One of the critical requirements to be fully compliant with PBL guidelines is that at the onset of lectures, students must be clearly made aware of why they are taking a particular course, where the course objectives and content are outlined in such a way that the students attend the lectures with an inquiring mind. Having knowledge of the aims and therefore industrial scenarios can be set right at the beginning, and as the lectures progress, the set problems become clearer and solvable rather than to set the problems at the end as was done traditionally. The implementation of PBL also requires different forms of assessments that are done continuously throughout the semester rather than one exam administered at the end. Typically, such PBL assessments include computer laboratory exercises; workshop practice for machining, welding, wiring and general fabrications; and guided tutorials in small groups. These assessments should also be set in line with a defined problem or project that all students must be clear about. The essential elements and expectations from PBL are: • • • • • • • •

Relevant curriculum and content with industry input Aims and objectives of courses set in conjunction with anticipated problems Students with inquiring minds and in-depth knowledge of typical problems Need for critical thinking and twenty-first century multi-skills beyond engineering Group design projects in small teams with solutions presented to all groups Reflection and revision of set problems as a group Students’ voices to be heard more than the facilitators All examinations to be based on real-life and industry scenarios

The starting point in PBL would be to establish the learning outcomes on what students really need to learn after completing the group design project by identifying a relevant real-world and practical or industry challenge by possibly giving the students an opportunity of proposing a task or problem that they may have encountered during their attachments at different companies. The advantage of opening this up to students is that they would normally tackle the challenge with a lot more vigour and passion and thus provide an all-encompassing solution to improve their understanding and blending of theory and practice. The lecturer’s main role would be to provide guidance to ensure that the students are applying the right principles to solve the problem, based on the lecturer’s foresight, experience and expertise. In order to maximise the benefits of PBL, the lecturers are encouraged to formulate small groups or teams which are assigned the same or different problems but the

5.2  Problem-Based Learning

87

most important being to ensure that each member of the group participated and contributed to the overall solution. This can be accomplished by assigning a specific task to each of the team members, such as different conceptual solutions, theory to solve the problem, application and implementation. Depending on the set problem and task, the students could also be assigned typical roles in industry, such as design engineer, production engineer, technical manager, general manager or chief executive officer, so that they provide a comprehensive solution handled from all the different angles and level in the organisation. Again, the role of the lecturer would be to provide guidelines on how organisations are structured and how they work, particularly in the case where some or all of the students would not have had the experience of industrial attachment to understand organisational structures and operations. Whichever route is adopted to solve a problem and complete a task, it is also important at the onset to establish and determine how the solutions provided by the different groups can be evaluated and assessed in fully addressing the challenge. There are several ways in which this can be accomplished, such as the lecturer setting the task with a known solution in which the submitted projects can be marked; self-assessments, where the students are given the opportunity to evaluate the outcome using software; or peer evaluations, where one group evaluates the solution of another group.

5.2.4  Challenges and Possible Solutions for PBL One of the major objectives for encouraging tertiary institutions to adopt problem-­ based learning as a new pedagogy and paradigm shift to traditional classroom form of instructions is to develop professionals who are not only critical thinkers but with skills that match those required by industry. A lot of research has been carried out and one of the biggest challenges in Southern Africa was the mismatch of skills between what industry required and what tertiary institutions were producing (Matthews et al. 2012). To adequately drive industry in this era of rapid and dynamic changes in technology, there is need for professionals with a broad range of skills and also the need to keep in tandem with the changes by continuously updating and upgrading those skills through continuous professional development. Working in groups, whether in industry or at tertiary institutions, helped in many ways to keep in tandem with technology changes as professionals also continually learn from each other’s experiences. Not only does this help to develop content and expertise for future reference but also developing professionals who are multi-skilled to enable them to manage and cope with the dynamic changes. The effects of the 2008 global economic crisis left Southern Africa as one of the worst affected regions in the world. This resulted in a number of companies in industry, witnessed by those in which case studies for this book were carried out, surviving from ‘hand to mouth’ and thus sometimes failing in areas such as professional development of their staff. As such, they needed graduates who were employable to immediately generate profits for their companies.

88

5  Problem- and Industry-Based Learning: Research, Theory and Practice

Some of the attributes defined and required by industry for the employment of graduate engineers include: multi-skilled and diverse engineers; self-understanding; ability to quickly adapt and learn from different resources; ability to work in a team; critical thinkers with the ability to grasp work ethics and values; and leaders with the ability to handle crisis, make decisions and prioritise allocation of resources and problem-solving. These attributes have been the major drive towards establishing the PBL pedagogy by consolidating teaching and learning approaches. However, there are criticisms and several challenges that come with problem-based learning, particularly when applied in industrialising regions such as Southern Africa. Firstly, due to the lack of previous experience, students often find it difficult to appreciate the importance of tackling a problem in a manner in which the lecturer would have guided. They have to rely on what the lecturer provides, but this can be improved by running practical videos on the operations in industry so that the students can deepen their understanding. The time required to cover material under the PBL pedagogy is obviously more than that required for traditional classroom teaching due to the demands for scrutiny under PBL. However, one way in which this can be solved would be to push such group design projects to semester breaks where students can make use of the time to meet in groups and then present their findings and results at the beginning of the following semester. In 1985, Thomas Sankara, the one-time president of Burkina Faso, once said, ‘You cannot carry out fundamental change without a certain amount of madness. In this case, it comes from non-conformity, the courage to turn your back on the old formulas, the courage to invent the future. It took the madmen of yesterday for us to be able to act with extreme clarity today. I want to be one of those madmen. We must dare to invent the future’. Most lecturers have been trained on the traditional approach to teaching and learning, and thus it can be very difficult to do away with this traditional role in order to adopt PBL, where their role is more of facilitation and guidance. A certain amount of ‘madness’ is required for them to adapt to the new pedagogy. To ensure that this is successful, institutions need to make bold decisions to make it mandatory and set aside enough resources for retraining of those traditional lecturers. Faced with the challenges of the global economic crisis, companies have also been shunning students on attachment and academics on secondment. This has presented some serious problems, particularly for tertiary institutions in Zimbabwe and Mozambique but slightly better for those in Namibia and South Africa, in terms of the availability of places for students and academics. This obviously presented the challenge where students may not be able to carry out their group design projects in conjunction with industry to be able to see the practical real-life operations. There are a number of ways in which this challenge can be resolved, firstly by entering into long-standing agreements with industry for organised attachments that can be spread throughout the academic year instead of cramming them all during semester breaks. Secondly, the development of innovation hubs, science and technology parks, as detailed in Chap. 10, can also be utilised to achieve the same exposure to modern equipment and technology.

5.3  Industry-Based Learning (IBL)

89

The resources at most institutions in Southern Africa, especially IT equipment, laboratory and workshop machine tools, are either inadequate or old and obsolete. This also presents challenges for students to adequately carry out their group projects at the tertiary institutions. Instead of attaching students in industry where they can be exposed to modern equipment and technology, smart procurement, use and maintenance of equipment, as detailed in Chap. 8, where the phenomenon of Build-­ Operate-­Transfer, such as in construction and other projects, can also be employed by tertiary institutions to acquire state-of-the-art machine tools for installation and use by students and academics in the laboratories and workshops. Apart from the limited expertise to implement PBL, the high engineering academics vacancy rates at almost all the tertiary institutions in Southern Africa, and in particular those who participated in NUSESA, EEEP and HEP SSA, virtually means splitting the classes into small groups would require more academics or overworking those available. One alternative way to resolve this challenge would be for tertiary institutions to enter into agreements with industry for the provision of practicing engineers to provide facilitation and guidance for PBL.

5.3  Industry-Based Learning (IBL) 5.3.1  Overview of Industry-Based Learning Industry-based learning (IBL) is a development out of which PBL emerged but with a rather specific purpose. Unlike PBL, which is a recent pedagogy, IBL has been there for some time under different terminology but maintaining the same principles. IBL is a philosophy that was developed for learning from an industry perspective. Such has been the case in the second and third Industrial Revolutions where technicians were trained on-the-job under apprenticeships and vocational training. The major difference between PBL and IBL is where it is done and for how long. While PBL is a new pedagogy of teaching and learning during students’ semesters at tertiary institutions, IBL is a dedicated time set aside for attachment in industry for periods of up to 12  months of on-the-job training, without interference with other courses at the institution. All case study institutions in this book, drawn from Southern Africa now, have a mandatory 1-year attachments for undergraduate engineering students normally carried out in their third year of study. During the course of IBL, students will not only be learning but are productive for the company, and hence there is usually a payment. However, this is not always the case, particularly for companies struggling from the effects of the global financial crisis. At the end of the attachment, students are then expected to produce the IBL report, which is assessed, graded and aggregated together with the rest of the undergraduate courses. IBL is a philosophy that was developed following extensive consultations and agreement with industry that the relevance and matching of skills can be enhanced when students spent at least a year appreciating what happens in industry before they graduate. Most institutions have also deliberately designed their curricula in

90

5  Problem- and Industry-Based Learning: Research, Theory and Practice

such a way that students proceed to the IBL attachment after grasping the basics of engineering, such as mechanics, electronics, thermodynamics etc., to apply these principles in industry in a somewhat complementary fashion to the principles of PBL. The students would then use the foundation principles in the context of application of the theoretical knowledge to product development and designs and industrial operations (Ilyas and Semiawan 2017). The tertiary institutions and industry partnerships case studies in this book under the HEP SSA initiative in Southern Africa involved all the major disciplines in engineering with their corresponding industry partners, as outlined in Chap. 4. While many of the companies could not provide for academics and students placed at their companies, the financial support from the Royal Academy of Engineering for both EEEP and HEP SSA catered for this requirement to ensure that there were no disruptions during the course of the IBL secondments and attachments. Tertiary institutions in this regard have also supported the scheme for academics by allowing them to be seconded for periods of up to 9 months while they are on sabbatical. In essence, IBL synchronises theory with practice in a manner that will be acceptable and assessable by the tertiary institution concerned. This is ideal and helpful for matching the skills that industry requires and those that tertiary institutions produce. IBL placements are also opportunities for students to decide in what area or division of their discipline they would want to focus on after graduation in order to maximise their potential. Although it has not happened because the IBL attachments are carried out towards the end of the students’ undergraduate studies, IBL can also be taken as an opportunity for a student to decide whether or not they really wish to pursue engineering or working in industry. The acquisition of skills at tertiary institutions through PBL and the complementary role of IBL in the application of the skills in industry using systems thinking resulted in the development of the strategy for Industrial Design Thinking (IDT), one of the thrusts and objectives for the HEP SSA initiative.

5.3.2  Objectives and Importance of Industry-Based Learning The link between academia and industry is the vital bridge for which this book is about and focusses on the acquisition of skills at tertiary institutions and how these are then appropriately applied in industry. As such, the investment in tertiary education by governments, industry and other supporting agencies is equally an investment in the productive sectors of economies around the world. Apart from the provision of required skills to drive industry, tertiary institutions also provide social values that can be used in selecting professionals for certain tasks in industry. Most positions in industry are normally streamlined and have career paths that allow individuals to professionally develop themselves, with the assistance of industry. Academic qualifications are merely a gateway to a whole world of opportunities

5.3  Industry-Based Learning (IBL)

91

where individuals can increase their worth through multi-skilling and diversification, which can be achieved through the component of IBL after graduation and employment. As detailed in earlier chapters, several aid agencies such as Sida/SAREC and the Royal Academy of Engineering have actively supported programs in Sub-Saharan Africa to enhance the quality of engineering education and the skilling of engineering academics through initiatives such as NUSESA, EEEP and HEP SSA. These followed on efforts by former colonial governments through development agencies such as the Overseas Development Authority (ODA) and the  Organisation for Economic Cooperation and Development (OECD). All these initiatives were mooted after the realisation of the inadequacies in engineering education which invariably translated to slumps in production and capacity utilisation in industry. These efforts were initially concentrated in sharing of resources, both in equipment and personnel among collaborating tertiary institutions until the realisation that it was important to include industry for the simple reason that they were the end users. The latter initiatives, such as EEEP included industry partners, some of whom have provided support such as Professorial Chairs, and HEP SSA also saw the increased participation of industry and academia with more focus on IBL for students and staff. According to the World Economic Forum, (2016), regardless of profession, the top core skills required for employment after graduation are: complex problem-­ solving, critical thinking, creativity and innovation, people management and ability to coordinate and work in teams. Clearly, these require professionals to go beyond their academic qualifications and seek to be multi-skilled and diverse, attributes that can only be acquired through an appropriate grounding, hence the need for both PBL and IBL. In recruitments, more and more employers have been looking beyond academic qualifications and focussing on soft and social skills, attitudes and motivations. This was revealed by industry partners during feedback seminars and dialogues with industry, as detailed in Chap. 4. In the same vein, employers have embraced the need for bringing industry closer to academia by supporting initiatives that allow trainee engineers to access typical facilities in industry through IBL. Although most technical colleges and polytechnics that were upgraded to universities were not replaced by the establishment of more polytechnics, the principle and theme for apprenticeship training remained the same and are the basis on which IBL was formulated. Faced with the challenges brought on by the global economic crisis of 2008, companies in Southern Africa preferred IBL to semester break attachments as students on IBL internships tend to be more productive than those on short-term attachments, hence the payments that most of them get. The advent of the fourth Industrial Revolution, particularly the transition from the third  to the fourth, has revealed the demand for productive and practically oriented professionals. The engagements carried out in Eastern and Southern Africa through the Africa– UK Partnership for Development revealed the need for incorporation of IBL in university education in order to enhance the quality and productivity of graduates upon employment (Matthews et al. 2012).

92

5  Problem- and Industry-Based Learning: Research, Theory and Practice

5.3.3  Formulation and Evaluation of IBL Projects IBL was formulated and founded in the learning pedagogy of constructivism where the learner was expected to be actively involved in the process of learning (Patil and Kudte 2017). Constructivism, a theory based on observation and scientific study, deals with how people construct their own understanding and knowledge through experience and reflecting on those experiences. Constructivism is closely related to Kolb’s experiential learning style theory, which advocates that knowledge is generated through the transformation of experience during the learning process (Kolb 1984). This has been transformed and perfected through various stages of the learning cycle, such as concrete experience (on-the-job practice), reflective observation (reviewing skills acquired), abstract conceptualisation (drawing lessons from practice) and active experimentation (applying theory to practice). As such, IBL is a pedagogy inclined to both constructivism and experiential learning style theories as they both require students to participate practically and constructively using critical thinking for complex problem-solving. The concept of IBL is now widespread throughout the world, although its formulation and implementation differ from country to country. In 2015, the University of Zimbabwe revised its curricula to include an additional year of mandatory attachment for students in industry. This model was based on the programs for the technical universities that were upgraded to universities such as the National University of Science and Technology in Bulawayo, Zimbabwe, Harare Institute of Technology and Chinhoyi University of Technology. The major motivation for the curriculum review and the formulation of the 1-year industrial attachment was due to the preference of graduates from universities with an IBL component (Government of Zimbabwe 2018). Although the University of Zimbabwe remained as the top university in Zimbabwe, the competition for jobs stiffened after the 2008 crisis while more universities came on board. Employers were thus forced to look for attributes that could quickly assist them to improve productivity, hence the preference for those with practical experience. Before adopting the new curriculum that incorporated a 1-year industrial attachment based on the IBL philosophy and demands, the University of Zimbabwe consulted widely with other institutions that had taken the same route within the country and region. In addition, the last workshop before implementation included players from industry who chipped in the formulation of the new curriculum. The mandatory attachment was designed in such a way as to allow students to be on IBL internships where they are exposed to typical operations of industry. For engineering students in particular, they are expected to spend more time (60%) in areas that are directly related to the student’s discipline or area of specialisation, such as production plant or engineering workshops, while the rest (40%) was expected to be spent in other areas indirectly related to the student’s area of specialisation, such as marketing and sales, maintenance etc. The idea for spreading the exposure was to ensure that the student had a feel of all the divisions of the company in order to appreciate, for example, how the product they would have designed was manufactured or where it ended up in terms of sales and marketing.

5.4  Implementation of IBL in Southern Africa

93

In order to realise the full benefits, the formulation and implementation of IBL in tertiary institutions required additional administrative and logistics management. Apart from the lack of adequate places for such internships, each student was expected to be periodically monitored by an academic supervisor, and they also needed to be regularly guided and monitored by an engineer at the place of internship. While the concept of IBL is beneficial, these logistical nightmares can be quite a challenge. However, all things being equal, during the course of the IBL, the student is jointly assessed and evaluated by the academic supervisor and industry mentor on a regular basis through short reports and meetings. At the end of the IBL, the student submits a project report which is evaluated and assessed by the tertiary institution for crediting and aggregation with other courses based on what the student learnt, problem(s) solved, creativity, innovations, recommendations made and any opportunities for furthering the project.

5.4  Implementation of IBL in Southern Africa 5.4.1  University of Johannesburg Although the main thrust is the same, collaborating institutions in Southern Africa have varying ways of implementation and evaluation of IBL projects. The University of Johannesburg was established in 2005 as a merger of four tertiary institutions that included a Technikon (Technical College). As such, they adopted and took over all the programs that the four institutions offered. However, over the years, the institution realised the difficulties of arranging for internships for the ever increasing numbers of students, hence the decision to do away with the 1-year mandatory internships. In 2019, the institution suspended the mandatory attachment but still incorporated aspects of IBL through PBL, which was done by way of short visits and attachments during semester breaks. This was also with the firm understanding and belief that long internships of this nature were better left for Technikons to execute. Besides, South Africa is a semi-industrialised country and does not experience the same challenges as the other Southern African institutions in terms of competition for employments, one of the reasons for IBL. As legislated nationally in South Africa, the last intake for the Bachelor of Technology program, which had the industrial internship component, was in January 2019, making the University of Johannesburg the first in South Africa to embark on this change (Source: Dr. D.M. Madyira: Senior Lecturer). The phasing out of the Bachelor of Technology with its internship requirement at the University of Johannesburg was in line with the Department of Higher Education and Training, Higher Education Qualification sub-framework and the Engineering Council of South Africa. In place of the phased-out program, the Faculty of Engineering and the Built Environment rolled out a new and accredited 3-year Bachelor of Engineering Technology  (BEngTech) and Bachelor of Engineering (BEng) degrees in conformity with the Washington, Sydney and Dublin accords and

94

5  Problem- and Industry-Based Learning: Research, Theory and Practice

in line with Conceptualise-Design-Implement-Operate (CDIO) principles (Crawley et al. 2014). Although the new program no longer has the component for industrial internships, it supports and promotes access, increased diversity and stronger relationships between academia and industry in accordance with the Engineering Council of South Africa thrust towards improved qualifications for postgraduate studies. The new programs are primarily industry oriented, providing the students with appropriate skills and a sound knowledge base for a particular discipline as well as the ability to apply their acquired skills to a particular career while equipping them with multidimensional approaches to dealing with complex problems. The new programs were also designed to build requisite knowledge, abilities and skills for further learning and continuous professional development in practice. Some of the expected attributes were: complex problem-solving, application of scientific and engineering knowledge and competent technical and professional communication (Fengu 2020).

5.4.2  Universidade Eduardo Mondlane Universidade Eduardo Mondlane in Mozambique, a former Portuguese colony, has different systems from most Southern African countries, most of which were former colonies of the United Kingdom. Over the years, the institution had a national requirement for all high school students to be attached to a company before enrolling into university. This was meant for students to have a feel of the working environment regardless of which profession students wished to pursue. This was helpful for most school leavers as it assisted them in career choice and what degree program to pursue. At inception, students were only required to choose between Science Technology Engineering and Mathematics (STEM) and social sciences/humanities, and they were accordingly distributed. Thereafter, on enrolment into university, they were oriented according to their abilities and wishes. Due to costs and logistical difficulties, the institution now only administers entrance exams to determine students’ abilities and suitability for particular programs. Following this disbandment, internships at Universidade Eduardo Mondlane are now optional and carried out in the last semester of study. The students who opt not to go on the internships, work in basic research on campus. Ultimately, both groups of students submit a final dissertation based on either the internship or the research carried out on campus, for assessment and aggregation before graduating. The other reason why Universidade Eduardo Mondlane abandoned the mandatory attachment in industry was that due to the increasing numbers of students, it was difficult to obtain places for internship, besides the fact that most companies in Mozambique that were state owned had now been privatised. Most privately owned companies prioritised productivity and profit over continuous professional development and training, especially in view of the 2008 financial crisis and global competition (Source: Professor AJ Tsamba: Former Dean of Engineering).

5.4  Implementation of IBL in Southern Africa

95

5.4.3  Harare Institute of Technology The Harare Institute of Technology (HIT) was accorded an upgrade and university status from a technical college in 2005. As a technical college, they trained technicians and thus have a wide variety of workshops and equipment on campus. Traditionally, the training of technicians through apprenticeships involved a lot of practical work and time in industry during their programs. When the institution was upgraded, it continued with the structures and program of industrial attachment, albeit they were now training technologists. The institution, sometimes referred to as a technoprenueral university, places a lot of emphasis on application of skills, and hence they have maintained the IBL component in all their programs. HIT has an elaborate way of evaluation which involves an agreed placement programme, log book, university and placement supervision and comprehensive write-up. (Source: Dr. P. Muredzi: Dean of Engineering). Despite challenges in securing places for internship, the institution believed IBL was an important aspect for their programs and even went to the extent of making use of internal placement in any of their production units or in-house companies for students who would have failed to secure a place for attachment. HIT’s engineering education focusses on application of sciences in industrial production, technopreneurship and design competencies in product development and innovation. All programs at the institution have mandatory technopreneurship courses that run every semester. Practical project courses emphasise on design and project development and include the 2nd year Team project, 3rd year Design and Innovation project and the 4th year Capstone Design project, which provide students with knowledge and skills on project management and experience in designing and developing prototypes and their verifications in conjunction with industry. All programmes at the institution have a mandatory internship or industrial attachment in line with IBL principles. This is normally carried out in the second semester of the third year at established industrial enterprises or the institution’s production units or in-house companies. Assessments and evaluations are carried out through regular visits as well as the written 3rd year Design and Innovation project (HIT 2020).

5.4.4  National University of Science and Technology The National University of Science and Technology was established in 1992 to complement programs offered at the University of Zimbabwe but with  a special focus on science and technology. All programs at the institution, have a 1-year mandatory and supervised industrial attachment in line with IBL principles and is carried out in the 4th year of study. The implementation, evaluation and assessment of the internships are governed by the university regulations, which required students to pass both the continuous assessments done twice during the internship through visits by the academic supervisor and evaluation by the industry supervisor. As part

96

5  Problem- and Industry-Based Learning: Research, Theory and Practice

of the IBL pedagogy, National University of Science and Technology students on attachment are required to complete daily log books, which are then submitted together with the attachment report at the end of the internship. The continuous assessment marks are then aggregated with that of the final dissertation report and credited to the student’s overall degree aggregate. The institution indicated a lot of difficulties in placing all the students on attachment, especially due to the increasing numbers. While the institution made all efforts possible to assist the students to secure internships, there have been a few cases where this failed, and the only way was to delay the student from proceeding or graduating until they had satisfactorily completed the internship. Each department has an attachment coordinator to assist, but also because of the location of the institution where there are few companies, places for attachment have been difficult (Source: Dr. W. Goriwondo – Dean of Engineering).

5.4.5  Chinhoyi University of Technology Following the upgrading of Chinhoyi Technical Teachers’ College in 2001 to that of a university, the School of Engineering Sciences and Technology was established in 2002, carrying forward some of the concepts and mode of learning that included industrial attachments to produce technologists in various areas, such as Mechatronics, Production, ICT and Electronics, Environmental Engineering, Fuels and Energy. These are all 5-year programs in which all students were expected to spent a mandatory 1-year industrial attachment in the 4th year. The formulation, implementation and evaluation of students on attachment were similar with the National University of Science and Technology, where the students were continuously assessed by both the academic and industry supervisors. The students submitted reports detailing what they would have gone through at the company as part of the assessable portion of the 4th year, which was aggregated together with the other years. Due to the location of the institution in a small town with very few industrial companies, most of their students were usually attached at companies in Harare, 100 km away. Even then, the institution faced many challenges in placing the ever increasing numbers of students. In a bid to maintain the IBL component in their programs, the difficulties faced in placing students forced the institution to forge long-standing links with organisations such as Zimbabwe Power Company, Almin Metal Industries and Big Wave Automation for training courses and placements in Programmable Logical Controlers (PLCs), Supervisory Control and Data Acquisition (SCADA) and Alternating Current (AC) drives. The institution prides itself on industry’s preference for their graduates because of the experiences and skills acquired during the internships, which ultimately make their graduates more employable. However, despite these collaborations with industry, some of their students still fail to get places for attachment (Munyoro et al. 2016).

5.4  Implementation of IBL in Southern Africa

97

Unfortunately, the institution has not attempted to relax the requirements that only those students who have completed and passed industrial attachments are allowed to proceed to the final level before graduating. Each department was responsible for ensuring that all students were attached, but the few who failed to do so were usually delayed in progressing to the next level. The institution established an innovation hub and industrial park which they hope, after equipping, might also play a part in absorbing some of the students for internships. The collaborations among engineering institutions within the country and region may also assist in ensuring the continuity of the IBL thrust through exchange of students and staff. Tertiary institutions that were well resourced may assist partner institutions and facilitate placements in industries in the countries where such requirements were not a challenge. However, it may not be sustainable to continue such exchanges unless there is financial support to cover travel and accommodation, hence the need to find ways to revive some of the industries in order to absorb more students (Source: Eng. E. Manyumbu: Dean).

5.4.6  Namibia University of Science and Technology Namibia University of Science and Technology was also one of those institutions that were upgraded from a polytechnic to a university in 2015. Originally, as the Polytechnic of Namibia, the institution offered various qualifications, including certificates, diplomas and degrees. As such, the transformation saw them carrying forward some of these trainings but gradually moved on to offer more degrees as a university. However, owing to the value of internships based on feedback from employers, the institution decided to continue with the IBL principles where their students were required to go through industry attachment. However, there was a slight variation from most of the regional institutions in that only their Bachelor of Technology students were required to undergo a 1-year industrial attachment in their 3rd year whereas the Bachelor of Engineering students undertook this during the semester breaks from their second year onwards. Each department has an academic responsible for ensuring that students were all placed. Purportedly due to the stability of the Namibian economy, most of their industries were operational, and placing students had not been much of a challenge. However, in the few unlikely cases where students failed to secure attachments, their progression to the next level was deferred as it was a strict requirement to complete the attachment first. Although this was minimal, there have been a few such cases where students’ graduation had been delayed. This challenge also required a holistic approach in which the effective narrowing of the gap between industry and academia could be useful in establishing long-standing arrangements where students enrolling at universities committed themselves with the knowledge that all will be secured and that the degree program would take the minimum possible time (Source: Professor S. John: Former Dean of Engineering).

98

5  Problem- and Industry-Based Learning: Research, Theory and Practice

5.4.7  University of Zimbabwe The University of Zimbabwe is the oldest institution in the country where the engineering programs and training started in 1974. The focus for these programs was on the production of engineering scientists rather than technologists. As such, the traditional training for many years did not have any mandatory industrial attachment but just an optional vocational attachment which was not assessed but simply acknowledged. The emergence of more universities in the country meant that the competition for jobs in a shrinking economy was high. Employers were more concerned about productivity and generation of profits to remain afloat instead of focussing on the detailed qualifications of applicants. As the technical colleges carried on with IBL principles, employers preferred such graduates who were productive on joining their companies. This forced the University of Zimbabwe to introduce one-­ year internships for all their programs starting in 2017, and thus too early to assess (Source: Dr. WR Nyemba: Former Dean of Engineering).

5.5  Industrial Secondments: UK Perspective There is a significant difference between the career progression of academics in the United Kingdom and universities in Sub-Saharan Africa. A typical career progression of an academic in the United Kingdom would be a BSc, immediately going on to a PhD in the chosen field of engineering. This would normally lead to a postdoctoral research appointment in the field and often a relatively short period in industry before taking up a lecturing post in an HEI. The links formed with industry enable the UK academic to apply for research funding from research councils that show good industrial links and support for the chosen project. An academic who does not form industry links during their early career often had problems in applying for research grants due to a lack of a track record in the field. This has a detrimental effect on the career progression of the academic and occasionally result in difficulties in retaining their university post. Secondments of academic staff to industry are relatively rare in the United Kingdom except to gain a better understanding of aspects of a topic that is required for a research project. In contrast, the experience in African universities is that, due to financial incapacities, after obtaining their first degree, potential academics need to seek employment. Often a PhD is obtained later when circumstances permit. Industrial experience can then be obtained by secondment to particular companies. Academics can therefore lack significant industrial experience at an advanced level, which reflect on their ability, or lack thereof, to teach students the latest industrial techniques which require equipment that can be unavailable within the university. Similarly, academics without Masters or Doctoral-level training can lack the knowledge, skills and track record to attract research projects from industry or for government infrastructure projects. There are many variations on these typical career paths, but it gives an idea of the type of career progression.

5.5  Industrial Secondments: UK Perspective

99

5.5.1  Criteria for Successful Secondments It should be recognized that companies in industry are not charities but have a duty to their shareholders to generate profit for the future prosperity of the company. Similarly, governments need to provide infrastructure projects for the improvement of life of the general population. Therefore, these organizations have no direct need to support HEIs. Thus, what can academics do to attract interest from industry and government that could lead to research funding and improved student teaching. Industry is not a teaching facility and does not wish to train students who will leave before they return the teaching investment by being able to carry out useful work to repay the teaching investment. However, industry has a vested interest in assuring that graduates from HEIs are fit for employment in their organisations. HEIs should therefore effectively become Centres of Excellence that industry and government can draw upon for: • Advanced academic knowledge in a particular field of engineering • Facilities not available to industry, such as High Performance Computer at the University of Zimbabwe • Other specialized equipment from successful research projects • Technical skills for operating specialised equipment

5.5.2  Establishing Academia Industry Secondments Secondments should be looked at as opportunities to develop a close relationship with the company concerned. This should allow the opportunity to investigate the possibilities for research projects in areas relevant to the company. It should be a priority to try to ensure that the company is satisfied with any secondment with useful work having been carried out for the company. This should lead to a sustainable relationship with the company. In addition, secondments also create opportunities to investigate if there are opportunities for student teaching placements within the company that satisfy the dual criteria of providing useful work for the company and also providing useful training in the latest equipment used in industry and the skills required to operate them. Obtaining secondments can be challenging for academic staff without existing industry contacts. A good strategy would be to review any existing contacts that might be available. Alternatively, a list of suitable target companies could be researched that have interests in the particular field of engineering required. This is ideally followed by identifying what target companies or government departments would be interested in and then match these requirements to the knowledge and skills available in the university. In this context, collaboration with other universities that have a track record in the chosen area of engineering might well improve the chances of a successful contact and subsequent relationship with a given company. Some of the contacts established for secondments carried out in this research were

100

5  Problem- and Industry-Based Learning: Research, Theory and Practice

a result of previous relationships, either from college or having worked together at some point. Once the secondments have been established, it should also be taken as an opportunity to cement contacts for the future. However, to contact or establish a relationship with a particular company or government department, it is prudent to identify the person at the correct level in the company. This would typically be the technical director or managing director of the company, introduced by an initial letter of contact, but more importantly the contact process demonstrates what the academic and university concerned can do for the company. This process of contact need to be thought out carefully as it is effectively a marketing brochure for consideration by the company. In this respect, a good track record in the field is a great help. All this pointed to the great need to maintain good relationships with colleagues or workmates throughout one’s career. Details on improvements in industrial operations, carried out as case studies in Chap. 6, were a good starting point for academics to market themselves.  Industry, government departments and grant awarding bodies in the UK generally have a set of criteria that they look for when developing university contacts and awarding grants. These criteria can be stated as follows: • Individual academics with expertise in the field of research that is evidenced by a track record including publications • Research proposals from academics associated with Doctoral Training Centres (DTC) that have the expertise and research facilities in a given field of engineering. The DTC will typically possess a team of postgraduates and academics who are available to study the topic and the required facilities to carry out that work. • Academics with interesting and/or novel proposals that can be shown to have a good chance of success. Some of the concerns that these proposals might look at are; solving particular known technical problems, opening novel methods of manufacture or analysis, methods of increasing the profitability of enterprises, analysis of government infrastructure projects.

5.6  Industrial Design and Design Thinking The whole purpose of formulating and implementing problem-based learning and industry-based learning pedagogy during the training of engineering students was to ensure that they were well equipped with skills to adapt to the rapid changes in technology and also to prepare them for the real world of industrial designs, creativity and critical thinking. Normally, industrial design referred to the process of designing for mass production as opposed to job production, which focussed on one product and usually took longer to complete (Coelho 2013). A fundamental aspect of the industrial design process was that the design was done in conjunction with manufacture. Although all processed and manufactured products came out of industrial design processes, the processes can be carried out in a variety of ways, such as through individuals or teams with different skills and expertise. Industrial design can be based on creativity or scientific decision-making or theory and is largely influenced by factors such as materials, manufacturing processes, appearance,

5.6 Industrial Design and Design Thinking

101

business strategy or social and economic situation of the company and environment. The process of industrial design frequently focussed particular attention on a combination of product outlook, end users and application, including marketing, branding, ergonomics and overall functions. Design thinking from an engineering perspective was an iterative process used by engineers to understand the end user of a product, formulation and reformulation of assumptions and problems in a bid to find possible and alternative strategies and solutions that may not be obvious at the onset. It revolved around the need to develop an interest and interaction with end users of products through developing an inquiring mind about potential problems, assumptions and implications of designing products in a particular way. Design thinking is often employed by industrial engineers for problem-solving using processes that begin with an appreciation of customer needs, which can be translated to the process of innovation, conceptualisation, product development and design, creativity, prototyping and experimentation. These processes are normally carried out with various experts from sales and marketing and those in charge of business strategies and development. The success of any business venture is dependent on how well products met customer specifications. Industrial design and design thinking provided the link between PBL, normally undertaken in conjunction with acquisition of skills at institutions of learning and IBL, undertaken as part of the application of skills in industry during internships. Under such scenarios, design thinking can be beneficial in solving problems that may not be adequately defined and formulated at the onset by modelling the problem in human-centric ways and brainstorming to provide a variety of alternatives and then using a practical hands-on approach in prototyping, experimentation, testing and validation. Almost all professions have evolved over the years to the extent that multi-skills, innovation, diversity of ideas and critical thinking will be the most sought-after to cope with the demands of the fourth Industrial Revolution and preparedness for the fifth Industrial Revolution (Digital Ecosystem) (Nahavandi 2019). Going forward, employers will most likely prefer professionals capable of complex problem-­ solving, people management and collaborations in an integrated or multifaceted manner. While many have regarded design thinking as a preserve for engineers, it is in fact a multifaceted tool that can be employed by all professionals to have a clear visualisation of the elements of systems (products), how they are interconnected and their expected functions, hence the systems thinking approach in this book. The use of design thinking to link PBL and IBL was the motivation in bringing the methodology to bridge the gap between academia and industry through solving the skills deficit and generating different options to cement the linkages. Taking cognisance of the variation of design thinking, its use in this book focussed on understanding operational problems in industry, insufficiencies in training at tertiary institutions, shortages and mismatch of skills, process mapping of industry requirements and academia outputs and in the process solving the engineering skills deficit to appropriately drive industry. The collaborations of tertiary institutions with industry partners, particularly under the EEEP and HEP SSA, have seen increased support from industry and interesting outcomes, as detailed in Chaps. 12 and 13.

102

5  Problem- and Industry-Based Learning: Research, Theory and Practice

5.7  Systems Thinking Synchronisation of PBL and IBL Evidently, the formulation and implementation of problem-based learning and industry-based learning at institutions in Southern Africa showed marked variations but with similarities in some of the areas. The PBL and IBL pedagogy has faced varied challenges throughout the world. Engineering change management was generally problematic, especially for professionals with traditional and analytical approaches to solving engineering problems. Although PBL was generally employed at tertiary institutions during the students’ course of studies, the pedagogy was best carried out with real-life challenges and engineering environments, which were often simulated even within the environs of the institutions. On the other hand, IBL pedagogy can only be fully realised when students are on some internships in industry. Ideally, PBL and IBL should be synchronised in such a way as to benefit both the acquisition of skills and their application and in the process cementing the links and narrowing the gap between academia and industry. Based on the same concepts derived from the foundations of systems thinking, as detailed in Chap. 3, and as a build-on towards modelling the bridge between industry and academia, Fig.  5.1 shows the causal loop feedback diagram of the flow and relationship between the two pillars of problem-based learning at tertiary institutions and industry-based learning in industry, supported by industrial design and design thinking.

Design Thinking

R

Problem Based Learning

Industry R Industry Based Learning

Academia R

Industrial Design

Fig. 5.1  Systems thinking causal loop feedback between PBL and IBL

5.8 Conclusion

103

The simple interpretation of the interconnections in the causal loop feedback is that as more students are exposed to PBL during their training and acquisition of skills at tertiary institutions, they will benefit more and their skills will enhance when they apply their PBL knowledge during the IBL internships. The relationship between PBL and IBL created a positive reinforcing loop in that their exposure through IBL encouraged the formulation and undertaking of PBL at tertiary institutions. Design thinking, as a tool for PBL, also created a positive reinforcing loop, likewise industrial design for IBL. Problem-based learning and industry-based learning are complementary almost in a similar manner to design thinking and industrial design. Focus for design thinking was at the conceptual stages of the design process where the problem was framed through rough concept development, whereas industrial design was the penultimate process carried out during product development and just before manufacture, focussing on the solution and possible challenges. While PBL and IBL were both student-centred pedagogies that promoted active learning and critical thinking through real-life problems and investigations, the major differences were in the levels of inquiry similar to those employed in high school education (Banchi and Bell 2008). The levels of inquiry included: • Confirmation: Students confirmed a principle derived from an activity where the outcome or result was known in advance • Structured: Involved investigating a problem set by a lecturer using a prescribed procedure • Guided: Investigation of a problem prescribed by the lecturer using a variety of procedures formulated by the students • Open: Investigation of questions formulated by students using selected procedures chosen by the students.

5.8  Conclusion The rapid and dynamic changes and challenges as a result of the fourth Industrial Revolution demanded multi-skilled engineers to cope with and manage the challenges and adequately prepare for the Digital Ecosystem (fifth Industrial Revolution). This can be achieved through appropriate training at the tertiary institutions, during acquisition of skills and in industry, for application of the skills in service. Most training institutions around the world have introduced new pedagogies to replace traditional classroom instructions, memorisation of information and passing of exams. Unfortunately, this has proven to create qualified but unemployable or unproductive graduate engineers who require additional and costly training after graduation. Problem-based learning was a recent philosophy that has been adopted by many institutions as a student-centred approach for active learning where students were guided rather than instructed, and they actively participated in formulation and solving of complex problems through exposure to real-life situations and

104

5  Problem- and Industry-Based Learning: Research, Theory and Practice

problems. Industry-based learning complemented this by getting students to be actively involved in industry through attachments or internships in a similar manner to apprenticeship training, albeit for fixed and limited periods. The two pedagogies of learning were complemented by the pillars of design thinking and industrial design, both of which were connected by positive reinforcing loops. Both pedagogies can be incorporated into any learning situation with an ultimate objective of creative problem solvers and critical thinkers. This chapter focussed on establishing the fundamentals, formulation, assessment and implementation of problem-based learning and industry-based learning. Case studies were drawn from seven tertiary institutions in Southern Africa and how they have adopted both pedagogies and what challenges they have faced. Evidently, all the institutions underscored the importance of problem- and industry-based learning methodologies in order to cope with the demands for the fourth Industrial Revolution in the provision of appropriately skilled engineers. The major challenges indicated by most of the institutions were the difficulties in securing industrial placements for students due to the rising numbers of students with no corresponding increases in industry operations. Some have entered into long-standing arrangements to address this issue, while others have gone to the extent of abandoning internships, thus in a way reducing interactions with industry. This book focuses on cementing links and bridging the gap between academia and industry. Abandoning internships would not be ideal in this era but instead and perhaps focussing on the establishment and maximum utilisation of innovation hubs and industrial parks as vehicles for industry-based learning. A systems thinking synchronisation of problem-­based learning at tertiary institutions with industry-based learning during internships was formulated to provide a feeder to the ultimate modelling of the bridge to narrow the gap between academia and industry.

References Andersen, A. L., Brunoe, T. D., & Nielsen, K. (2019). Engineering education in changeable and reconfigurable manufacturing: Using problem based learning in learning factory environment. Procedia CIRP, 81(2019), 7–12. Banchi, H., & Bell, R. (2008, Oct). The many levels of inquiry. Science and Children, 46(2), 26–29. Coelho, D. A. (2013). Advances in industrial design engineering. Croatia: InTech. Crawley, E., Malmqvist, J., Ostlund, S., Brodeur, D., & Edström, K. (2014). Chapter 8: Adapting and implementing a CDIO approach. In Rethining engineering education (pp. 181–207). Fengu, M. (2020). University students in a panic as UJ phases out course. City Press. Available: https://city-­p ress.news24.com/News/university-­s tudents-­i n-­a -­p anic-­a s-­u j-­p hases-­o ut-­ course-­20200203. Accessed 1 June 2020. Government of Zimbabwe. (2018). National Critical Skills Audit report. Harare: Government of Zimbabwe Printers. 2018. Available: https://safrap.files.wordpress.com/2018/12/2018-­ zimbabwe-­nationalcritical-­skills-­audit-­report.pdf. Accessed 22 Oct 2019. Gupta, R., & Gupta, V. (2017). Constructivist approach in teaching. International Journal of Humanities and Social Sciences, 6(5), 77–88.

References

105

Hemelrijk, C. K., Wantia, J., & Gygax, L. (2005). The construction of dominance order: Comparing performance of five methods using an individual-based model. Behaviour, 142, 1037–1058. HIT (Harare Institute of Technology). (2020). School of industrial sciences and technology. Available: https://www.hit.ac.zw/industrial-­sciences-­and-­technology.html. Accessed 1 June 2020. Ilyas, I.  P., & Semiawan, T. (2017). Industrial-Based Learning (IBL): Promoting excellence on polytechnics and vocational higher education. Journal Vokasi Indonesia, 5(1), 45–52. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development (Vol. I). Englewood Cliffs: Prentice-Hall. Madke, P. B., & Jaybhaye, M. D. (2016). Application of Pugh selection matrix for fuel level sensing technology selection. International Journal of Engineering Research, 5(2), 368–370. Matthews, P., Ryan-Collins, L., Wells, J., Sillem, H., & Wright, H. (2012). Engineers for Africa: Identifying engineering capacity needs in Sub-Saharan Africa, analysis of stakeholder interviews. London: Royal Academy of Engineering. ISBN: 1-903496-91-8. Munyoro, G., Nyandoro, Z. F., & Musekiwa, M. (2016). An evaluation of the student industrial attachment programme in Zimbabwe: A case study for Chinhoyi University of Technology. International Journal of Research in Business Management, 4(8), 1–16. Nahavandi, S. (2019). Industry 5.0 – A human centric solution. Sustainability, 11, 1–13. Patil, A. M., & Kudte, S. S. (2017). Teaching learning with constructivist approach. International Journal of Engineering Development and Research, 5(4), 308–312.

Chapter 6

Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

Abstract  The provision of solutions for industry in terms of modelling and simulations, ultimately leading to optimisation of manufacturing, mining or other engineering processes, is usually the preserve of production and process engineers. However, the shortage of such professionals often force companies to engage foreign expertise, which is usually quite costly. These optimisations can actually be carried out by academics and students at much reduced costs but still achieving reasonable results for the companies to remain competitive. As part of the engineering academics’ secondments and student internships under the EEEP and HEP SSA projects, a wide variety of projects were carried out. This chapter focusses on these projects as case studies and how the results were used as viable alternatives to provide solutions for industry problems through the improvement of capacity utilisation, productivity and efficiency as a demonstration of the capabilities and impact of utilising affordable engineering academics’ expertise, thus bridging the gap between academia and industry. Keywords  Capacity utilisation · Efficiency · Experimentation · Modelling · Machine distance matrices · Plant layouts · Process flows · Process mapping · Productivity · Optimisation · Simulation · Sustainable manufacturing

6.1  Introduction The ultimate purpose for any business enterprise is to generate income and maximise on profit and dividends for shareholders to keep the company afloat (Goldratt and Cox 2014). Due to the demands of the 4th Industrial Revolution and growing global competitions, these processes must be carried out using efficient and

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_6

107

108 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

effective methods, minimising waste and maximising capacity utilisation. Most business operations are characterised by many dynamic and complex factors which usually result from the unpredictable manner in which orders are received or processed. Technological companies in areas such as manufacturing and mineral processing have realised the need to invest in modern technology to cope with such demands. Engineers have devised several techniques ranging from modelling business operations to simulating them in order to predict performance or identify bottlenecks right through to optimisations in order to realise maximised benefits. However, these are largely pipedreams for industrialising countries such as those in Southern Africa, as they have evidently lagged behind, hence the need for streamlining operations in close collaboration between academia and industry.

6.2  Modelling Systems Modelling is a very broad word just like design which is used rather generally in real life. This can range from the display of fashion and style to the construction of scale models to represent real-life objects. Despite the differences in application, they all have one thing in common in that they are trying to represent something. The focus for modelling in this book is on engineering systems, the interdisciplinary study of representations to conceptualise and construct systems from real-life engineering scenarios in order to understand their behaviour, predict their performance and thus make decisions from the inferences drawn from them. There are various forms of systems modelling, such as the use of functional block diagrams; architectural modelling, which utilises systems architecture to conceptually model structures and their behaviour; and business process modelling, normally represented by graphs specifying business or manufacturing process flows. Models are created with the eventual intention of simulating them to provide realistic replications of the dynamic nature of process flows under investigation as opposed to the static analysis, often misleading in establishing good systems (Baldwin et al. 2010). The dynamism in process flows such as production schedules, nature and availability of materials handling equipment, variations in raw materials and product mixes as a result of varying orders from customers and random breakdown of machine tools creates varying loads on the system (Wang et  al. 2011). Noting, however, that both static and dynamic analysis can be utilised in evaluating the efficiency and predicting the performance of a plant and its flow processes, accurate and timely analysis can be derived from a combination of the two. Dynamic modelling and eventual simulation of systems provide a tool for identifying problems in a flexible and less costly manner than physical prototyping and experimentation since this does not require the physical plant and movement of parts in production, and it can be accomplished as some experimentations may take years whereas modelling and simulation aided by the computer can be done timely in a matter of minutes.

6.3  Simulation of Operations

109

This enhances planning and reduction of lead times, hence timely deliveries for customer orders. Historical data of product mixes and orders received can be used as input in modelling and simulation, thus assisting in production scheduling. Dynamic modelling and simulation depends on the proper identification of the problems to be solved, which translates to specifications of aims and objectives and the ultimate determination of the relevant controllable and uncontrollable variables (Harish and Kumar 2016). However, due to the nature and complexity of simulation in problem-solving, it should really be employed as a last resort after ascertaining that other analytical approaches such as queueing theory cannot be used.

6.3  Simulation of Operations The critical stage in dynamic modelling and simulation involves the determination of properties of the real system, which should be regarded as fixed parameters and which should be allowed to vary during the simulation run. Variables for system models can be specified by either empirical frequency distributions or standard mathematical distributions. Either way, these are determined by direct observations coupled with detailed analysis of records, although other scenarios can reasonably be assumed to closely approximate other standard mathematical distributions such as Poisson or Normal (Antwerpen and Curtis 2016). While the length and duration of simulation runs depended on the purpose of the simulation, the most commonly used approach was to execute the simulation for a set period, such as a month, to observe if the conditions at the end of that duration still appeared reasonable. However, errors may arise in the process, from mistakes in coding or logic (Yeh et al. 2012). The data required to model and eventually simulate a system is generally obtained from observations and recording work measurements such as process flows, distances traversed, plant configurations, materials handling and the time required to perform tasks in the production process. Simulations are carried out experimentally to predict the behaviour and performance of a real system with the ultimate intention of improving the performance in order to achieve a desired outcome, thus solving a particular problem. The values for controllable inputs can be selected and those for probabilistic inputs can be generated randomly while conducting simulation experiments to compute the values for the output (Rolón and Martínez 2012). Although simulation is commonly taken as optimisation, it is actually a tool that can lead to optimisation by predicting and thus adjusting how a system will operate under certain conditions for the controllable inputs and randomly generated probabilistic values (Negahban and Smith 2014). The values for controllable inputs are often obtained from quantitative analyses, and depending on the simulation results, the more runs are carried out during experimentation, the more ideal outcome can be obtained by changing and varying fixed parameters and variables, decisions governing the simulation, starting conditions and duration of the runs (Bloomfield et  al. 2012). A multiplicity of factors

110 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

influences the process flows in a production plant, mining or processing factory depending on the processes, raw materials handling and transportation from one workstation to another, layout of the workstations and individual and overall times required to process a part and the eventual product. Due to the interconnectedness of all these factors, the various stages and the dynamic nature of manufacturing and processing plants, modelling and simulating systems of this nature can be complex, thus requiring advanced techniques, including genetic algorithms or fuzzy logic, in analysing and predicting their performance (Negahban and Smith 2014). The various techniques for modelling and simulating systems have their own advantages and disadvantages, and thus certain techniques are more suitable than others for solving particular problems. While genetic algorithms and fuzzy logic are useful for optimisations and production control and monitoring, respectively, simulation was chosen for the work in this book, particularly for its suitability in process flows, systems thinking, interconnections and causal flow feedback loops. The various companies from where the case studies in this chapter were derived were drawn from Zimbabwe and part of the consortium of industry partners in both the EEEP and HEP SSA projects. The case studies were carried out during the period following the global economic recession of 2008 and were selected based on the diversity and differences in operations but representative of other companies in the country and region.

6.4  Process Mapping and Optimisation Process mapping, often employed in manufacturing plants, engineering or other business ventures, involved the creation of workflow diagrams with the aim of appreciating how processes or systems worked, their interconnections and functions (Rahani and Muhammad 2012). Usually, mapping of processes, modelling and simulation was followed by process optimisation for adjusting processes in order to make the best or most effective use of resources without disturbing or violating set constraints with the ultimate aim of minimising costs and maximising throughput, productivity, efficiency and capacity utilisation. These were necessary ingredients to cope with the increasing demands for the fourth Industrial Revolution and global competition (Schwab 2016). For instance, the positions of various workstations in a production factory influenced the lead time and throughput and therefore needed to be arranged in accordance with well-documented process flows that followed a uniform direction to avoid long distances traversed by parts in production and thus eliminating backtracking and criss-crossing of process paths. It is often difficult to visualise an entire system in a manufacturing environment due to the proximity and interconnection of individual and related processes. This required an appreciation of what a business does and how it does it through documenting the business’s inputs, outputs and resources. Process mapping is therefore an analysis of the entire system by distinguishing how tasks are actually carried out as opposed to how they are supposed to

6.4 Process Mapping and Optimisation

111

be done and what purpose and function the system should perform from how it is built to perform the functions. The relationships derived from the interconnections were grouped as a collection of elements to enable the visualisation of the entire operation to ultimately and conveniently allow the adjustments in order to optimise them. Process mapping also empowers manufacturers to quickly identify sequence of activities through process flows that cut across functional boundaries (Rybicka et al. 2015). The three fundamental stages followed in process mapping are: identifying sequence of activities, diagnosing and interpreting the activities for redundancies and bottlenecks and making decisions on the course of action, thus adjusting to enhance production throughput and efficiency (Okrent and Vokurka 2004). These enabled users to decide whether to replace one or more service components and how it can be accomplished. In one case study of Kraftmaid Cabinetry, a cabinet manufacturer from the United States, drawer parts would traverse a total distance of 208  miles backtracking and crisscrossing throughout the company’s 1.2  million square foot plant, prior to reorganisation of the plant and relocation of workstations (Inbound Logistics 2016). The total distance travelled was reduced by half following modelling and simulation, which led to reconfiguration of the plant. According to Smith and Balls (2012), process mapping was also employed for manufacturing optimisation where it allowed users to observe the ‘as-is’ scenario to benchmark for improvements in sustainable manufacturing through modelling materials, energy and waste flows. It enabled the capturing of materials and eventually waste from the manufacturing processes as a value stream mapping tool that enabled the manufacturer to eliminate waste, maintaining inventory control and product quality. The increase in global competition has also pushed manufacturers to reconsider their manufacturing systems in a bid to produce in the shortest possible time in efficient ways while coping with the demands of fluctuations in the market (Singh et al. 2006). The use of process mapping as a precursor to optimisation has also pushed engineers to redesign their systems, such as the value stream mapping for lean manufacturing where projected state maps were developed and overlapped with the current ones, leading to the design of a lean process flow through elimination of the causes for waste (Vinodh et al. 2010). However, this was limited to single product lines, whereas the case study companies in this chapter are multi-product manufacturing or processing companies, which makes modelling more involving and complex. A typical multi-product manufacturing plant was modelled and simulated, proving to be quite a useful tool for controlling and analysis of design and reorganisation of plants (Sagawa and Nagano 2015). Despite its usefulness, it did not have the capability of scheduling individual jobs as this required incorporation of parameters such as machine utilisation rates, setups, blocking and waiting times. The reorganisation of plants and location of workstations required an optimal facilities arrangement that included machine tools, materials handling and personnel in order to handle these facilities through product, process or fixed position layouts. Plant layouts are often altered periodically to satisfy production requirements depending on customer specifications, possibly product design changes and even as a result of acquisition of new machine tools. Thus, the layout of machine tools is not static but

112 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

dependent on a number of factors, such as the total distances travelled by parts, which can be reduced through optimisation and grouping of machines performing similar functions or arranging the machine tools in accordance with the steps for processing and/or assembling the products. In general, optimisation involved the determination of alternative means for production and processing with the most cost-effective, efficient and highest achievable performance under certain constraints, without compromising on product quality but maximising on desired outputs and minimising on the undesired ones. Optimisation was thus employed as a corollary to modelling and simulation where different alternatives can be experimented on by assessing and solving complex problems. Due to global competition, product complexities, market turbulences and demands for the fourth Industrial Revolution, industry adopted new techniques to cope with these demands and to remain in tandem with the rapid changes in technology to enable them to make quick decisions.

6.5  Case Studies The case studies in this section were carried out by engineering academics on secondment in industry assisted by students on attachment, led by this book’s authors. All of them utilised modelling and simulation as the foundation technique to demonstrate the usefulness of the solutions provided by academics in industry, justifying the need to bridge the gap between academia and industry. The case studies employed various software tools such as Arena and Limn Flowsheet Processor as well as novel techniques such as machine distance matrices, flexible manufacturing and group technology for businesses that included furniture manufacturing, foundry, general engineering, mining and mineral processing. The projects focussed on both quantitative and qualitative analysis by experimenting on physical locations of machine tools and workstations, transportation distances among interacting workstations, minimisation of waste, maximising throughput and productivity, materials handling and capacity utilisation.

6.5.1  Plant Reorganisation Using Machine Distance Matrices The data, results and recommendations in this section are a summarised version of a paper that was presented at the 14th Global Conference on Sustainable Manufacturing in Stellenbosch, South Africa in October 2016 and subsequently published in the journal Procedia Manufacturing in 2017 as follows, from where more details can be obtained: Nyemba W.R. and Mbohwa C., (2017), “Process mapping and optimization of the process flows of a furniture manufacturing company in Zimbabwe using machine distance matrices,” Procedia Manufacturing, 8(2017), pp. 447 – 454, Elsevier.

6.5  Case Studies

113

The appropriate arrangement and organisation of machine tools and workstations in a business operation can have a positive outcome on the performance of a business. The case study was carried out at a furniture manufacturing company following revelations that parts traversed long distances in production before the final product was completed due to the layout of workstations and crisscrossing of process paths. The research looked at how the plant layout was reorganised by mapping process flows and regrouping of the workstations according to their functions and products using machine distance matrices. The problems identified during the work study related to the plant layout, process paths and flows, materials handling and transportation, including assembly flows and procedures. The case study focussed on modelling and simulation of the furniture manufacturing plant’s wide range of products, their processing and assembling, with the objective of appropriately scheduling production by utilising the correct product mixes and process paths depending on current orders and historical order patterns. This was accomplished through optimisation of the movement of parts and reduction of distances traversed by grouping the workstations according to their functions in order to accomplish timely product deliveries in a sustainable way. 6.5.1.1  Research Methodology The research methodology was based on the work study and ‘As-Is-Analysis’ of the furniture manufacturing plant to establish the operational setup, workstations available, range of products, their popularity and frequency of production, process paths and sequences followed by parts in production for the different products, documentation available and skills and expertise available in each division of the plant. This was coupled by interactive interviews with operators and management and observations and data collected during the secondments. The proper understanding of a business process and why it is carried out in a particular way was the foundation for establishing the base for the optimisation process to enable elimination of non-value added work during production (Okrent and Vokurka 2004). Figure 6.1 shows the furniture manufacturing plant layout as it was at the beginning of the work study, showing the production process flows for one of the company’s popular products, the bunk bed. The numbers represent the various workstations performing different functions, as shown in Table 6.1. Having documented the company’s operations, a number of challenges were noted, such as obsolete machines that frequently broke down, contributing to delays in meeting customer orders and often substandard products. The next stage involved the development of product assembly trees for the company’s main products, such as the one for the bunk bed in Fig. 6.2 showing the number of parts, using the front to back approach to build the product’s bill of materials and process paths. A model was constructed to incorporate relative positions of all machines in the plant. Distances and process paths through which each part or sub-assembly traversed were measured and traced using the product assembly trees.

114 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

Fig. 6.1  Furniture manufacturing plant layout and process flow for bunk beds

Table 6.1  Machinery and functions for the furniture manufacturing plant Machine number Machine name Machine functions 1, 2 & 9 Ripsaw Ripping 3&7 Surfacer Edging/planing/surfacing 4 Thicknesser Thicknessing/planing/ 5, 12, 23, 39, 41, 43, 50, Cross cut saw Cutting/Sizing 65 & 71 6 4 cutter Planning/t&g/f-joins 8 Precision saw/cross cut saw Ripping/cutting/shaping 10, 64 & 70 Radial arm saw Bevelling/cutting/trenching 11 Multiborer Boring 13, 14, 15 & 29 Spindle moulder Rounding/rebating/tenon cutting/ trenching 16, 40 & 55 Bendsaw Cutting/Shaping 17 & 59 Router Mortising 18 Doweling machine Dowelling 19, 35 & 36 Drum sander Sanding 20 Tenoner Tenon cutting 21, 42, 62 & 66 Drilling machine Drilling 22 Cross cut saw(small) Cutting 24 Disc sander Sanding 25 Sewing machine Upholstery 26 Dowel moulder Doweling 27 Grinder Grinding 28 Press table Joining/pressing (continued)

6.5  Case Studies

115

Table 6.1 (continued) Machine number 30, 49, 52, 60 & 68 31 32

Machine name Ripsaw/precision saw Dimension saw 6 cutter

33 34 37 38 & 74 44 45 46, 54 & 58 47 & 53 48 & 73 51 56 57 & 63 61 67 69 72 75 & 76

5 cutter Dust extractor Mortiser Centre Lathe Planer/Thicknesser Surfacer Belt sander Surfacer/Thicknesser Press machine Web saw Mortiser Spindle Louvre machine Press Laminating machine Multi cutter Ingersol rand compressor & Standby compressor

Machine functions Ripping/cuttin/shaping Cutting Planing/surfacing/thicknessing/ ripping/t&g/f-joins Planing/surfacing/thicknessing Extraction of dust Mortising Shaping/turning Cutting Planing/thicknessing Planing/surfacing Sanding Press Fitting Cutting/bevelling Mortising Moulding Shaping Press Fitting Laminating Planning Provision of compressed air

bunk bed top {1} long rails {14}

short rails {4}

cleats {4}

ladder {1} slates {14}

legs {4}

steps {4}

bottom {1} legs {2}

long rails {2}

short rails {4}

cleats {2}

slates {14}

legs {4}

short dowels {4}

Fig. 6.2  Product assembly tree for the bunk bed showing quantities of parts

Bottlenecks were identified at workstations, such as the multi-borer (11) and drum sander, (35) due to the demand for the two workstations, an indication of insufficiencies in their numbers. Transportation distances between interacting workstations were identified as the major setback that required to be reduced through mapping, grouping and reorganisation of the factory. The various tasks were broken down into sub-tasks to enable visualisation and scrutiny of each workstation. Depending on the bulkiness of parts, the main modes of transportation were forklifts or trolleys as well as manual handling in the assembly areas. Figure 6.3 shows the production flow processes for the bunk bed.

116 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

Fig. 6.3  Production flow processes for the bunk bed

6.5.1.2  Reorganisation and Optimisation Group technology was employed to arrange machines with similar functions or those that required processing to be done close to each other, resulting in the reduction of movement of parts, enabling parts to be moved from one workstation to another without having to wait for a full trolley or busy forklift. The transportation distances between interacting workstations for the production of bunk beds were recorded in a machine distance matrix, as shown in Table 6.2, after the reorganisation and regrouping of the workstations. Depending on the transportation distances and frequency of interaction among particular workstations, the factory was reorganised using machine functions and positions. Machines such as the spindle moulder (13) and multi-borer (11), which were mainly used for secondary processing, were relocated close to each other to form the core of the factory, while cross cutters (5, 12, 23 etc.) were also grouped as these were mainly used for the production of pallets. Storage areas for boards were centrally located close to the assembly of domestic furniture for easy accessibility with minimal traverse distances. The cross cut saw (41) and multi-cutter (6) were relocated close to the timber yard, where raw materials were stored as this was where all the necessary cutting were carried out without having to move the raw timber. To allow for the free movement of trolleys, the multi-cutter (72) was relocated parallel to the other multi-cutters (6, 32 and 33). Following these relocations and reorganisation of the plant, transportation distances were recomputed and compared to the original matrix, as shown in Table 6.3, for the bunk beds, showing an average reduction of transportation distances for all the parts and sub-assemblies of 42.8%. Figure 6.4 shows a schematic of the reorganised plant showing the functional and product line groups from industrial products such as pallets and moulds, commercial furniture, domestic furniture to coffins, following sequencing of two important parameters of grouping products and relocating workstations with similar functions in a unidirectional approach to avoid crisscrossing of process paths.

13.2 15.8 5.8

7.9

2.6

1 11.01

11.1 29.6 29.4 19.0

T.Y.

14.6

34.9

18.5

7 19.01 3.2 4.2

2.6

3.5 15.8

9

58.2

7.9

19.5

23.2

9.5

12.1

6.3

30.6 31.7 42.2 22.8

12

9.5 13.2

6.9

11

7.4

22.1

56.5

18.5

2.6 3.2 6.9 3.2 7.9 8.5 7.9

13

7.4

17.8

14

9

13.2 4.22

16

5.3

5.3 6.9

22.7

20

37

26

2.6

6.9

29

18.5 18.5

5.3 5.3

14.3 12.1 2.6

30.1 13.2

31 35

40.7

5.3

16.9 5.3 5.3

46

13 5.3

53

23.8

11.6 6.9

53.9

55

2.6 5.3 5.3

6.9

60

Key: T.Y. Timber Yard, H.S.Hand Sanding, C.B. Cross Buttons, L Lamination, F.F. Final Fitting, W.T. Water Treatment, W.S.A. Workstation or Area

W.S.A. T.Y. 1 4 6 7 8 10 11 12 15 17 18 21 35 38 41 46 53 55 65 H.S. F.F. W.T. C.B. F.A.

Table 6.2  Machine distance matrix among interacting workstations – bunk beds

6.9

63

6.5  Case Studies 117

118 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Table 6.3  Comparison of component travel distances (m) for bunk beds Top 253.3 125.2 50.6

Bottom 220.3 130.4 40.8

Ladder 50.7 26.4 47.9

Slates 57.0 25.9 54.5

Rails 92.4 63.4 31.4

DISPATCH

(Pallets & Moulds)

PRIMARY PROCESSING ZONE (PPZ)

SECONDARY PROCESSING ZONE (SPZ)

SPRAY SHOP

TERTIARY PROCESSING ZONE (TPZ)

INDUSTRIAL

FINISHING & ASSEMBLY

FINAL FITTING

DISPATCH

Legs 85.0 58.1 31.7

COMMERCIAL (Furniture)

DOMESTIC (Furniture)

TIMBERYARD and TIMBER STORES

Component Original layout New layout % reduction

COFFINS

Fig. 6.4  Schematic of the reorganised furniture manufacturing plant

6.5.1.3  Achievements and Conclusion The relocation of various workstations and regrouping of products into four categories resulted in a continuous production flow and minimal crisscrossing of process paths. The recommended disposal of obsolete and redundant equipment cleared the gangways and reduced interference to allow for free movements of parts and sub-­ assemblies and a safe working environment, thus improving throughput and reducing lead times. In-line quality control was also adopted in accordance with product categories and similar functional workstations, which enhanced quality of products and anticipated reduction in assembling times. Where necessary, additional trolleys or the incorporation of an automated conveyor system along each product line were recommended to enhance the movement of parts and sub-assemblies within the factory. The reorganised and adopted layout was inclined to the product layout approach where parts were cut in one area, machined in another and assembled in yet another before final dispatch for sales. Using machine distance matrices between interacting workstations, transportation distances were reduced by 42.8% in the manufacture of bunk beds, derived from comparisons of the original layout to the reorganised one. Similar comparisons were carried out for the company’s main products, realising an overall reduction in transportation distances of 40%, translating to increased productivity and throughput and timely product deliveries to customers.

6.5  Case Studies

119

6.5.2  Optimisation for a Multi-product Assembling Plant The data, results and recommendations in this section are a summarised version of a paper that was presented at the 2016 World Congress on Engineering, subtheme on International Conference for Manufacturing Engineering and Engineering Management, at Imperial College London in June 2016. It was awarded a certificate of merit and recommended for an extended version, which was subsequently published by World Scientific Publishers in 2018 as a book chapter as follows, from where more details can be obtained: Nyemba W.R., Mbohwa C. and Nyemba L.E.N., (2018), “Process Mapping, Modelling and Optimization of Plant Layouts and Materials Handling in Manufacturing”, in Ao S., Gelman L., Kim H.K., Amouzegar M.A. (Eds), IAENG Transactions on Engineering Sciences: Special Issue for International Association of Engineers Conferences 2016, Vol. II, pp. 132 – 145, ISBN: 978-981-3230-76-7, World Scientific Publishers, Singapore.

A multiplicity of factors affected the movement of parts within a manufacturing environment, and this was quite complex for a company manufacturing a wide range of products, such as the furniture manufacturing plant in Zimbabwe, the same company covered in the previous section, except that this time, two of their main products were chosen for analysis. Analysing the factors for a multi-product manufacturing plant can be equally complex, hence the choice of modelling and simulation for optimisation of the plant. This case study focussed on the company’s two main products, the industrial pallets and domestic baby tenders, by modelling and simulating the process flows to develop an efficient system that realised timely product deliveries at minimal cost. 6.5.2.1  Research Methodology The furniture manufacturing company specialised in mid-volume or batch production of domestic, commercial and industrial furniture. In selecting the industrial pallets and baby tenders for this case study, consideration was taken into account for those products that went through most of the available workstations, as representative of the company’s main operations. Figure 6.5 shows the five-stage material flow for industrial pallets, while Fig.  6.6 shows the ten-stage materials flow for the domestic baby tenders. Simulation models based on the two products and derived from the process flows in Figs. 6.5 and 6.6 but generic to the company’s other products were developed and constructed using Arena simulation software. Measurements were recorded for the four time parameters as follows: ta tb tc t d

Material movement time from previous workstation to active workstation Waiting (Idle) time before processing at the active workstation Product processing time at the active workstation Waiting (Idle) time after processing before moving to the next workstation

120 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Timber Yard

Raw Timber Selection

(WS1) Cross-Cutter

79.5m

Cross-Cutting

(WS2)

11m

Parts

Rip Saw (WS3)

Ripping

9m

Moulding

Multi-Cutter (WS4) 26m

Pallet Assembly (WS5)

Assembling

Fig. 6.5  Five-stage process flows for industrial pallets Timber Yard(WS1)

Raw Timber Selection Surfacer

54m

14m

(WS2/5)

3m

Planing

Lamination

Laminating

(WS3) 13m

Thicknesser

Parts

Sizing

(WS4) Rip Saw (WS6) CrossCutter(WS7) Spindle Moulder (WS8)

Sub-assembly

Drum

10m Cross-Cutting

4.5m Moulding

28m

Sander

Sanding

(WS9) Nursery Assembly (WS10)

43.5m Assembly and Final Fitting

Fig. 6.6  Ten-stage process flows for domestic baby tenders

The size of a part or sub-assembly was an important consideration for the assembly line analysis and design just as the number of products that can be processed at each workstation affected worker performance. Therefore, the number of products (n) or sub-assemblies entering the assembly line should not exceed a particular value; thus, (n) became one of the controllable inputs to the simulation model while the other were the number of workstations (w). The probabilistic inputs to the materials flow simulation model were the 4 durations, ta, tb, tc and td derived from data collection and analysis. The output consisted of various operating characteristics, such as average queueing time, hourly output and the total time spent in the assembly line, as shown in Fig. 6.7 along with Eqs. (6.1) and (6.2), for the computation of total time spent at a workstation, tw and in the system ts. n



t w    t a  tb  tc  t d  x x 1



(6.1)

6.5  Case Studies

121

Fig. 6.7  Mathematical and simulation model for an s-stage process flows

s



t s  t w w 1



(6.2)

Following the development of the generic mathematical and simulation model outlining the probabilistic and controllable inputs, the materials flow charts which defined the sequence of the mathematical and logical operations required to simulate the materials flow for industrial pallets and domestic baby tenders were extrapolated and developed, taking note of the relevant, processing, waiting and movement times. As was necessary for any simulation experimentation and due to the complexity of real production processes, a number of assumptions were made before developing the generic simulation models to provide a representation of the operations and outcomes. It was assumed that the company ran two continuous 8-h shifts daily with minimal or no breakdowns and that machines would run uninterrupted without the need for maintenance, which can actually be carried out during the off-shift periods. However, in reality this may not be possible as machines can break down, hence requiring some kind of buffing factor to allow for repairs during the shift periods. It was also assumed that orders received from customers followed a uniform and normally distributed pattern based on historical data. However, due to the limited data, more experiments were necessary to validate the outcomes. The standard features for the generic simulation models were the workstations, process and assembly lines. For each workstation, there were two resources, a machine to process a task and a storage for parts prior to processing. Four possible states were assigned to each machine, namely starved (waiting), busy (processing), blocked (storage full) and failed (machine broken down). The latter was dependent on the company’s maintenance strategy, while the storage capacity for each

122 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Table 6.4  Parameters, variables and probability distribution for industrial pallets Parameter Work Machine station capacity WS1 1 WS2 1 WS3 1 WS4 1 WS5 1

Variables and probability distributions Uptime % 100 75 75 80 100

Downtime % 0 25 25 20 00

Workstation capacity 24 24 24 24 8

ta – ε{23.03} ε{14.95} ε{114.15} β{2,0.8}

tb – Β{3,1.5} γ{3,1} γ{3,1} γ{3,1}

tc γ{3,1} γ{3,1} γ{3,1} β{3,1.5} ε{271.8}

td β{0.0,8} β{2,0.8} β{1.5,3} γ{3.1} γ{3,1}

workstation was assigned three possible states: empty, partially full or full. On arrival at a workstation, parts would be delayed by a duration of time specified by a standard mathematical distribution equivalent to the idle time before processing and similarly delayed after processing before transportation to the next workstation. The parameters that were employed in both simulation models were workstation capacity (number of parts that can be handled at a time), storage capacity, number of workstations as well as machine uptime and downtime percentages, as shown in Tables 6.4 and 6.5, derived from the measurements and data collected in preparation for the simulation runs in Arena. The variables for the simulation models were custom-built probability distributions of the various time periods that characterised materials flow for the industrial pallets and domestic baby tenders and as defined by the mathematical model. The probability distributions with their shape parameters for the Gamma (γ), Beta (β), Normal (η) and Uniform (μ) distributions and the mean for the Exponential (ε) distribution {in braces} for these durations are shown on the right of both Tables 6.4 and 6.5. 6.5.2.2  Results, Verification and Validation In order to ascertain that the two generic simulation models were valid representations of the process flows, verifications and validations were carried out as part of the simulation processes. Errors in coding were encountered and this presented challenges in running the Arena programs. However, this was resolved by splitting the programs into small segments, followed by checking the validity of each segment. Results obtained quantitatively from the models were taken through a series of comparisons with the raw data that was collected at the plant to verify the validity of each model. The work study carried out at the onset during the ‘As-Is-Analysis’ and the interactive interviews with experienced personnel particularly artisans, contributed significantly in the validation process. Probability distributions were obtained from the company’s main products, including the bunk beds that were handled in the previous section. These results were used as input to the generic simulation models, as a way of validating the usefulness of the generic models for products other than just the industrial pallets and

Work station WS1 WS2 WS3 WS4 WS5 WS6 WS7 WS8 WS9 WS10

Parameter

Machine capacity 1 1 1 1 1 1 1 1 1 1

Uptime % 100 75 100 70 75 80 65 70 60 100

Downtime % 0 25 0 30 25 20 35 30 40 0

Workstation capacity 16 12 12 8 12 10 10 18 14 8

Table 6.5  Parameters, variables and probability distribution for baby tenders

ta – γ{3,1} β{3,1.5} γ{3,1} β{2,0.8} γ{3,1} β{3,1.5} η{52.8,1.5} γ{3,1} γ{3,1} tb – β{1,2} β{3,1.5} γ{2,1} ε{213.88} β{1.5,3} β{3,1.5} γ{3,1} β{1,1} γ{3,1}

tc γ{3,1} γ{2,1} γ{3,1} β{3,1.5} β{1.5,3} γ{2,1} γ{3,1} γ{3,1} γ{3,1} β{3,1.5}

Variables and probability distributions td γ{2,1} γ{2,1} β{2,2} β{3,1.5} ε{262.329} γ{3,1} β{3,1.5} μ{16.5313.2} β{3,1.5} β{3,1.5}

6.5  Case Studies 123

124 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

domestic baby tenders. For each workstation and for both products, the sample sizes were initially an average of 25 readings in an hour, and this figure increased to 37 per hour after implementing recommendations on product mixes, derived from historical orders and the projected monthly orders during the time that the research was carried out. The validity of the model results gave the company  management an appreciable level of confidence in implementing the recommendations. Qualitative results included direct observations of material flows during the simulation runs and experimentation of both generic models, from where bottlenecks, starved and busy machines, frequent breakdowns or those with large queues were identified. The observations were useful to recommend preventive maintenance on machines that frequently broke down or additional machines for those constantly with large queues. The output from the simulation models formed the foundation for the quantitative results which revealed the average times spent by products or sub-assemblies in the system, the hourly throughput and other characteristics such as busy, starved or blocked machines. These results, shown in Table 6.6, as extracted from the Arena simulation runs, also revealed the average times spent during production with storage space being empty, partially full or full. These tallied fairly well with the qualitative observations for both models.

Table 6.6  Average queue times for (a) industrial pallets and (b) domestic baby tenders (a) Industrial pallets Work station Average queue time (sec) WS1 4245.6 WS2 2624.6 WS3 2635.6 WS4 2005.5 WS5 2648.8 (b) Domestic baby tenders Work Station Average queue time (sec) WS1 1136.9 WS2 2243 WS3 1686.9 WS4 1675.7 WS5 65.294 WS6 4.909 WS7 15.7 WS8 12.306 WS9 20.059 WS10 0.0518

Minimum value (sec) 3754.2 404.3 484.59 1765.3 485

Maximum value (sec) 19,529 6396.76 6422 8904.6 6453.1

Minimum value (sec) 259.89 893.51 509.06 499.59 0 0 0 0 0 0

Maximum value (sec) 2767.2 3557.2 3557.2 3566.9 1286.9 179.36 213.77 209.39 358.05 6.6705

6.5  Case Studies

125

6.5.2.3  Achievements and Conclusion Two fairly flexible and generic simulation models were developed for the furniture manufacturing company’s two main products, industrial pallets and domestic baby tenders. Data was collected for the two products through interactive observations, interviews and direct measurement of the times that parts and sub-assemblies spent idle, being processed and transported from one workstation to another. This formed the foundation for the controllable and probabilistic inputs for the simulation model, coupled with the developed mathematical model. Simulation runs were conducted using Arena, based on the collected data where a number of revelations were made and thus formed the recommendations for advice to company management, in terms of optimisation of efficient operations. Some of the recommendations included the introduction of parallel machine blocks particularly for those workstations that were always busy or frequently broken down, in order to ease and reduce queues requiring these machines. Additional storage space was also necessary to avoid congestion prior to processing to enhance the flow of materials. Most of the recommendations were adopted by management as they did not require capital investment but simply reorganisation of systems. Lead times and backlogs were reduced as the company managed to meet customer orders.

6.5.3  Process Flows and Layout for a Foundry The data, results and recommendations in this section are a summarised version of a paper that was presented at the 2017 International Conference on Industrial Engineering and Operations Management in Bristol, United Kingdom in July 2017. It was awarded the best paper in the modelling and simulation track and was subsequently published by IEEE as follows, from where more details can be obtained: Nyemba W.R., Mhlanga R., Chinguwa S. and Mbohwa C., (2017), “Process Flow Modelling and Optimization of a Foundry Layout in Zimbabwe using Simulation”, Proceedings of the 2017 International Conference on Industrial Engineering and Operations Management (IEOM), Bristol, UK, July 24-25, pp. 292 – 303, IEEE.

One of the most common engineering operations that spans across various disciplines such as mechanical, electrical, metallurgical and systems engineering is the foundry industry where technologies have evolved over the years largely due to rapid changes in technologies. The flow of materials in foundries pass through various stages, synonymous with the various disciplines involved, and a multitude of factors ranging from preparation of charges, materials handling and conveyancing, production scheduling, furnaces and metallurgical testing influence the process flows, hence the need for careful planning and sequencing for efficient production. The complex interconnections of the various stages required modelling and simulation to optimise the production processes of which this case study focussed on with

126 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

the aim of optimising and reorganising the foundry layout in order to reduce production costs, improve productivity and enhance efficiency. The case study was carried out at a foundry and general engineering company in Zimbabwe which specialises in the casting and machining of grinding media such as ball mills, grinding balls, valves and numerous spares for the local and regional mining and industrial sectors. The company had also been capitalising on the opportunity for import substitution through designing and developing pumps, stokers for tobacco curing, automotive and rolling stock spares for the railway industry. At the time of carrying out this case study, it was the company’s intention to incorporate a state-of-the-art continuous casting machine to expand on their business activities that included well-equipped, albeit conventional, foundry furnaces, metallurgical lab, pattern shop and machine shop, hence the request to reorganise the entire plant using modelling and simulation tools. This was motivated by the global financial crisis of 2008 and competition from cheaper and more affordable imported media, thus the need for efficient production processes in order to reduce costs. The company wished to ensure that their diversification into a wide variety of products and their investment in new machine tools, such as the continuous casting machine, realised some benefits that could help grow the company and remain competitive with an appreciable share of the market. 6.5.3.1  Research Methodology The case study and research which was carried out in 2015 for a period of 6 months initially focussed on an ‘As-Is-Analysis’ by documenting the process flows of the original setup, in parallel with the collection of data such as processes, processing times, process paths and means of conveying materials. The data was analysed and deciphered into suitable categories, largely bundled as controllable and probabilistic inputs in preparation for modelling and simulating the plant using Arena. The drawings and model of the original entire plant were done using AutoCAD 2012, superimposed and derived to generate inputs for the Arena simulation models which were done in segments and then eventually merged. Simulation experiments were carried out live and in parallel with the real production in progress to eventually derive the optimal layout based on the simulation results. For batch production of items such as grinding balls, the company’s raw materials were largely scrap metal supplied by dealers and merchants and also frequently from the mines. However, the supplied raw materials were usually not in standard form or already segregated as per metal content, which required the company to carefully segregate these before smelting. For job production and general engineering machining and repairs, the materials were usually the parts supplied by customers. Due to the wide variety of products and the limited time spent at the foundry, focus for the case study was on the foundry section, as it was central to all the other operations and divisions of the company. In addition, the data that was collected was mainly the process flow distances from one workstation to another, especially those interacting ones where parts were processed in one and then transported to the next

6.5  Case Studies Table 6.7  Stages and time for a typical batch of the 80 mm grinding balls

127 Time/mins 10 5 45 10 10 3 5 1 10 220 20 2 10 40 5 120 60 10 110 1080 110 10 60

Activity Baling Waiting Loading – truck Transportation – foundry Offloading Loading – crane Transportation – furnace Offloading Charging into furnace Processing (smelting) Lab testing & Inspection Offloading into ladle Transportation – casting Pouring into die Waiting for solidification Waiting for cooling Loading – truck Transportation – fettling Offloading Fettling Loading – dispatch Transportation – dispatch Offloading in dispatch

processing workstation. The data also included the duration for processing, waiting (before and after processing) and the transportation time. Although this was done for a number of products, the case study reported in this section covered the 80 mm grinding balls, a typical batch shown in Table 6.7, showing the various stages and average times taken by the balls. The movement of materials between interacting workstations was recorded, and the average number of movements in a day for the 80 mm grinding balls are shown in Table  6.8, and the distances between those interacting workstations were also recorded and are shown in Table 6.9. Having established the processes and data collection of times and distances between interacting workstations over a period of 6 months, the Arena model was developed by extracting and inputting the controllable variables as the number of machines at each workstation and the number of 80 mm grinding balls produced at a time while the probabilistic inputs were the four time parameters: processing, transportation and idle (before and after processing). The machines were scheduled for a seize-delay-release action, which implied that the machines would receive the batch (seizing), process it (delay) and then release it after processing for storage or transportation to the next workstation. The priorities in the Arena model were set as

128 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Table 6.8  Number of movements per day in the production of 80mm grinding balls Workstation Scrap yard Furnace Casting Fettling Lab Weighbridge Machine shop

Scrap yard Furnace 5 6 8 0 1 20 15 3 0

Table 6.9  Distances between interacting workstations

Casting Fettling Lab 5 0 3 7 1 1 5 2 10 2 5 12 2 2 3 2 3 0 From Scrap yard Weighbridge Induction furnaces Induction furnace Fettling

Weighbridge 5 3 0 5 3

Machine shop 0 0 4 3 4 3

1

To Weighbridge Induction furnaces Laboratory Casting/fettling Stores

Distance (m) 25 237.7 18 31.7 205

high, medium or low depending on the priority for each process and whether or not it was value or non-value adding. In addition, the times were utilised for the model as triangular delay type, meaning that besides the processing time, the maximum as well as minimum times were also inputted to the model. 6.5.3.2  Results and Optimisation of the Foundry A detailed analysis of the processes in the smelting, casting and fettling of the 80  mm grinding balls was carried out throughout the different stages. Using the original setup and model of the foundry, simulation of the processing of the balls was carried out and modelled in Arena. The results obtained provided an overview of the process flows in the system. Valuable times per entity were derived from the Arena simulation at the various stages together with non-valuable time per entity for the weighing process. Processing and waiting times at the various stages for each entity were recorded, from where the accumulated value added time was for the production process after 20 replications. The accumulated non-value added time for weighing was also recorded to give the number of entities which entered and left the different processes to obtain the queueing and waiting times at each stage of the production process. This enabled the determination of scheduled usage of resources for the individual processes and the quantities seized at each of the workstations. Based on the initial analysis, which revealed that process paths were either backtracking or unnecessarily long, the first step to realise an optimal layout was to rearrange the routes through which the materials and parts followed but with minimal changes to the workstations as some of these, such as the furnaces, were huge and fixed. However, those that were flexible and small were relocated adjacent to each other in

129

6.5  Case Studies Table 6.10  Distances and times between workstations before and after rerouting Workstations Scrap yard – weighbridge Weighbridge – furnaces Fettling - stores

Distance before/m 25

Distance after/m 15

Transportation time before/mins 1

Transportation time after/mins 0.6

237.7

33.3

11

1.54

205

150

10

7.32

accordance with the interactions between them in order to reduce the distances travelled by materials and parts during processing. However, due to space it was necessary to relocate the weighbridge to be as close to the scrap yard as possible in such a way that immediately after baling, charges were weighed and transported straight to the furnaces. A more direct route was also introduced between fettling and storage. The space was also enhanced for free movement of materials by relocating and in some cases getting rid of obsolete equipment. A summary of the rerouting is shown in Table 6.10. The long queueing times observed at some of the workstations prompted the need for additional machines, particularly for baling and fettling. The two-tonne induction furnaces were normally utilised only when the demand for 80 mm grinding balls was high. These were both located adjacent to the hand-moulding section where a crane was used to transport molten material from the furnaces to the casting areas. However, due to the limitations in the movement of the crane fixed to the roof, rails were introduced across the two induction furnaces linking to the die casting section. The simulation results and data collected during the case study, especially the average time spent by parts on specific processes and the idle time, were the key parameters that were used to design the optimal layout. Undesirable scrap that entered the production system was also observed to queue on baling, weighing, smelting and fettling, thus contributing unnecessarily to delays in production. During experimentation, an additional machine was incorporated in each of the two processes, which resulted in a significant reduction in waiting times, as shown in Fig. 6.8. 6.5.3.3  Achievements and Conclusion Appropriate arrangement of equipment in an engineering setup, such as a foundry with a multitude of stages, is critical for efficient production. Through the analysis of this case study and the results derived from modelling and simulation, a number of recommendations were made, chief among them being reorganisation of the foundry by moving smaller and flexible machines and workstations to be adjacent to those that they frequently interacted with in order to reduce unnecessary long distances that parts or molten metal moved during production. The addition of

130 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Process Times

WAITING TIME PER PROCESS

Average waiting time before(mins) Average waiting time after (mins)

41.022 48.456

0 14.304

0 0

0 0

0 0

1147.23 895.542

1078.518 0 0

in to la So dl e lid ifi fa ct io n St W or ei ag gh e tin g( NV A)

g

di e o

in g

Po ur

Po ur

in g

in t

ng

M el tin

g

tli Fe t

Co ol in

Ba lin

g

44.208 8.7

3563.124

1400 1200 1000 800 600 400 200 0

Average Time before (mins)

Average Time after (mins)

Fig. 6.8  Process and waiting times before and after optimisation

machines to busy workstations eased queues in the system. The reorganised foundry layout realised decreases in processing, idle and transportation times, while the rerouted process paths accumulated distance in the production of 80 mm grinding balls decreased from 467.7  m to 198.3  m, translating to reduction in production costs and improvements in productivity. The manufacturing throughput time correspondingly decreased by 58%. The case study assisted the company in reorganisation of the plant in an affordable manner through the engineering academics’ interventions and recommendations.

6.5.4  Casting Technology for Sustainable Manufacture The data, results and recommendations in this section are a summarised version of a paper that was presented at the 15th Global Conference on Sustainable Manufacturing in Haifa, Israel in October 2017 and subsequently published in the journal Procedia Manufacturing in 2018 as follows, from where more details can be obtained: Nyemba W.R., Moyo R.T. and Mbohwa C., (2018), “Optimization of the casting technology and sustainable manufacture of 100mm grinding balls for the mining Sector in Zimbabwe”, Procedia Manufacturing, 21(2018), pp. 68–75, Elsevier.

Foundry die casting processes usually result in excessive waste due to the number of processes that the production goes through, such as bailing, charging, smelting, fettling and metallurgical testing. However, the major governing factors for these processes were in the design of the runners and gates, inclusive of the sizes, operation and heat and pressure during casting (Nimbulkar and Dalu 2016). Gating systems, runners and handling of molten metal in die casting play a critical role in the efficiency and productivity of foundry businesses. This case study was carried out at the same foundry in Zimbabwe as the one covered in the previous section, and this was motivated by the company’s desire to reduce production and ultimate

6.5  Case Studies

131

product costs in order to remain competitive and to respond to the demands of the fourth Industrial Revolution and rapid changes in technology. The research focussed on the reduction of excess waste and the long hours spent in manual fettling experienced in the production of 100  mm grinding balls for the mining sector through optimisation of the casting technology. 6.5.4.1  Research Methodology In conjunction with the previous case study, a number of challenges were identified at the inception, which constituted the candidates for resolving in order to meet the company’s desire to be competitive and reduce excess waste. Apart from the long distances traversed by parts and molten materials in production, as resolved and presented in the previous section, excess waste was also a contributory factor, even though it was recycled. In the long run, it contributed to the operational and production costs, thus affecting the general efficiency and productivity of the company. The company relied mostly on the induction furnaces for smelting, and due to lack of capacity and appropriate equipment, other forms of casting such as shell moulding and investment casting, mostly meant for ornamental trinkets in gold and silver as well as other complex shapes (Rao et  al. 2014), were not in use. Due to the absence of automated machinery for fettling, this stage also took a considerable amount of time, apart from the excessive waste generated in the section. Although, other products were considered, focus for the optimisation of the casting technologies employed by the company was on 100 mm grinding balls. The case study was conducted over a period of 6 months in 2015, initially documenting processes and operations of the die casting section in the production of 100 mm grinding balls. The data collected in the casting and fettling section comprised mainly of the times for pouring, solidification, offloading and fettling before the grinding balls were ferried for storage and eventual dispatch to customers in the mining sector. The gating system employed by the company for the 100 mm grinding balls consisted of a cylindrical down-gate, sprue base, runners and the mould where sand with binders was used as a release agent. The challenges observed included difficulties in directing molten metal from the ladle into the mould resulting in splashing and loss of molten metal. In addition, a considerable amount of waste also solidified in the runners and gates, apart from the evident turbulence and vortex formation in the flow of molten metal due to the uniform diameter of the cylindrical down-gate, often resulting in distortions and defects in the grinding balls. As part of the way to resolve these challenges in order to optimise the casting technology, three possible concepts of the gating system were considered, as shown in Fig. 6.9, modelled using Solid Works software. Molten metal can be easily directed and poured using the conical funnel in Concept (a) in order to reduce splashes. The tapered down-gate also reduced the chances for vortex formation and turbulence owing to the constricted opening. According to Bernoulli’s principle of fluid dynamics, this would also increase the

132 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Molten Metal Flow

Pouring Chamber

(a)

Sprue

(b)

(c)

Mould Cavities

Fig. 6.9  Gating system concepts

Rating Weight

Concept

Concept

Total Score

Maintenance

Weight

Manufacture

Life Span

Productivity

Quality

Cost

Function

Efficiency

Criteria

Table 6.11  Binary dominance matrix for selection of optimal gating system

Weight

6

6

5

4

4

4

3

2

2

(a)

8

7

9

6

5

7

8

7

8

(b)

6

4

5

8

6

5

7

6

5

(c)

7

5

6

7

7

8

5

6

8

(a)

48

42

45

24

20

28

24

14

16

261

(b)

36

24

25

32

24

20

21

12

10

204

(c)

42

30

30

28

28

32

15

12

16

233

speed of flow. The overflow bores on the side of the chamber would be useful to indicate that the mould cavities were full. Although the second concept (b) was almost similar to the first, it had a wide offset pouring basin which directed molten metal into the sprue to avoid the ladle coming close or in contact with the sprue. Nevertheless, this concept required more materials to develop the gating system and the chances of waste through spillage were high. Concept (c) was almost similar to that which the company originally used, which was cheaper to make in terms of materials and labour. However, the uniform cylindrical down-gate caused a lot of turbulence and vortex formation, while the speed for pouring was also slow, thus resulting in solidification before the pouring was complete. Using a combination of factors such as efficiency, cost, weight, ease of manufacture, life span etc. based on the multidimensional aspects of the designs, the binary dominancy matrix was used to select the optimal concept for detailed design and adoption. Binary dominance matrices are often employed in engineering design to decide on the most optimal solution from a wide variety of alternatives (Hemelrijk et  al. 2005). From various factors, such as those shown in Table  6.11, and set

6.5  Case Studies

133

criteria, as well as the relative importance of each factor, scores were allocated on a relative scale derived from comparing the different concepts, multiplied by the weighting (importance) and then summed up to select the most optimal concept, which in this case was Concept (a). This technique also allowed subjective opinions of concepts to be turned into objective ones. Although the conical pouring chamber for the selected Concept (a) meant additional waste due to the molten metal that may solidify in the chamber, it was estimated to be less than the spillages encountered when pouring direct into the sprue. The design was however adjusted to create a compromise between the large opening to permit pouring without spillages but small enough to avoid excess waste that solidified in the chamber by incorporating overflow bores for directing any spillages for recycling. A sprue base was also added to allow for the settling of molten material before it was uniformly distributed through the runners and gates into the mould cavities. 6.5.4.2  Results and Optimisation of the Gating System As part of the redesign and optimisation of the gating system, data in the form of time for pouring and mass of the cast 100  mm grinding balls were recorded, as shown in Tables 6.12 (a) and (b), respectively. These consisted of the average pouring times for two samples, which were drawn from six dies and the mass of four balls, including the waste from the runners and gates before they were separated and fettled. Analysing Table 6.12 (b), it showed that 37% of the original molten metal Table 6.12  (a) Average pouring time, (b) average mass of balls before and after fettling (a) Die 1 Die 2 Die 3 Die 4 Die 5 Die 6 Average pouring time (seconds) (b) Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Average mass

Sample 1 5.20 7.50 6.30 6.60 5.70 6.00 6.22 6.15 4 balls before fettling (kg) 19.80 20.50 19.70 21.00 20.60 21.50 20.52

Sample 2 6.40 4.70 7.10 6.20 5.60 6.50 6.08 1 ball after fettling (kg) 3.40 2.80 3.50 3.70 2.90 3.10 3.23

134 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

was lost in the runners, hence giving a yield of only 63%. The optimisation of the casting technology and redesign of the gating system were based on these results. Apart from the adjustments to the chamber, there were four other major improvements to redesign, and these are graphically illustrated in Fig. 6.10. Two overflow bores were incorporated to avoid spillages, but if  any overflow  occurred, it was quickly captured and recycled. The tapered sprue down-gate also allowed an increase in the flow velocity, thus reducing vortex formation and turbulence. A critical parameter in the design of gating systems is the choke, the cross-sectional area at the lower end of the sprue down-gate (Nimbulkar and Dalu 2016). The choke determined the mould-filling time depending on its location and cross-sectional area. Iterations and adjustments of the choke area improved the rate of filling to avoid solidification before pouring was complete. The choke was based on Bernoulli’s theorem and derived from established formulae from casting technology. 6.5.4.3  Achievements and Conclusion The use of conventional tools in sand and die casting, which is often unsystematic, produced excessive waste, which contributed to increased production costs. Analysis of the gating and runner systems at a foundry in Zimbabwe revealed a number of challenges, such as excess waste averaging 37% of molten metal raw materials, some of which were due to spillages and solidification in the runners, apart from the manual methods employed in fettling. Despite the recycling of the excess waste, it still contributed to operational and product costs, as it was time-consuming in terms of energy consumption. The gating system was optimised using computational fluid dynamics and a redesign of the system for the production of 100 mm grinding balls by incorporating a conical pouring chamber with overflow bores, tapered sprue down-gate and as a uniform sprue base, which resulted in marginal improvements and reduction of the waste to 24% of molten metal, translating to reductions in operational costs. The optimised casting technology also reduced the chances for defects and recycling of defective balls. Recommendations were also made for further improvements and reduction in costs of the grinding balls by automating the fettling section, which required capital and thus could not be implemented during the time the case study was carried out.

6.5.5  C  omminution and Flotation Circuits in Mineral Processing The data, results and recommendations in this section are a summarised version of a paper that was presented at the 16th Global Conference on Sustainable Manufacturing in Kentucky, USA in October 2018. It was deemed one of the best papers for the conference and recommended for an extended version, which was

6.5  Case Studies

135

subsequently published in the International Journal of Sustainable Manufacturing in 2020 as follows, from where more details can be obtained: Nyemba, W.R., Kapumha, Z.B., Mushiri, T. and Mbohwa, C., (2020), “Modelling, simulation and optimisation of the comminution and flotation circuits of platinum for sustainable mineral processing”, International Journal of Sustainable Manufacturing, Vol. 4, Nos. 2/3/4, pp. 300–318, Inderscience Publishers.

One of the critical objectives in mining and mineral processing is value addition to the ore extracted from underground. Generally, the amount of valuable minerals that can be extracted is very small compared to the waste that is discarded from the ore, hence the need for efficient extraction methods and thus the necessity for optimisation of the process flows through modelling and simulation. The case study was carried out at platinum mining and metallurgical processing plants in Zimbabwe. Although the major processes in the platinum mining and processing cycle are mining, comminution, flotation and smelting, focus for the research was on the comminution and flotation as these two were capital intensive and thus contributed significantly to the production of platinum. The case study was aimed at identifying bottlenecks and recovery hampering factors within the comminution and flotation circuits of the company’s concentrator plant. Modelling and simulation of the process flows of these two major sections were carried out using Arena and Limn Flowsheet Processor to optimise the production processes for improved throughput, maximum mineral recovery and enhanced productivity and efficiency. Processing of platinum involves complex and multifarious stages for extraction in an efficient and sustainable manner, hence the need for cost-efficient designs in order to maximise mineral extraction by simplifying the multipart processes of the process flows and materials handling. The ‘As-Is-Analysis’ carried out at the inception of the case study established that the company exported their ore in concentrate form for further refining in South Africa due to the lack of capacity for beneficiation. This obviously translated to loss of revenue that could be realised if the company had a precious metal refinery. However, even so, the bulk of the work in platinum processing resided in the concentrator where comminution and flotation processes were carried out. The value of the concentrate that was exported in raw form can be enhanced by improving the operations of these two major sections. 6.5.5.1  Research Methodology The quantity and quality of minerals extracted from ore generally depended on the technologies that were employed in mineral processing (Mwanga et al. 2017). Due to the excessive waste that is discarded from ore in mineral extraction, the equipment and processes employed must be efficient enough to justify the investment, thus requiring the appropriate optimisation of the various multifarious stages. For the purposes of this case study, these stages were broadly classified as comminution, that is crushing by the semi-autogenous grinding (SAG) and ball mills from ores as large as 300 mm boulders to 75μm for the flotation cells, thickeners and clarifiers.

136 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

In all these processes, the numerous workstations that were connected in series were critical to ensure that they continued to run uninterrupted, otherwise a breakdown in an upstream machine meant loss of production in downstream processes and thus minimised throughput. The other challenges revealed were that the production throughput of the plant was below the designed capacity, and there were also reductions in tonnage milled and platinum output based on comparisons with previous reports, coupled with queues observed at the smelter. Following the data collection, coupled with observations and interactive interviews with operators and management, it was imperative to consider alternative configurations for the comminution and flotation circuits, the basis on which the optimisation was carried out using modelling and simulation. The alternative configurations included: use of High Pressure Grinding Rolls (HPGR) in the SAG and ball mills, pre-crushing of the ore before feeding it into mills, different combinations of milling and flotation, use of cleaner scavenger cells in flotation and increasing rougher cells residence time and volume. To maintain a continuous flotation process, Yianatos et al. (2012) Eq. 6.3 was employed, where R was the recovery at time t, R∞ was the maximum recovery at infinite time, k was the kinetic rate constant for all sub-processes, F(k) was the constant distribution function for mineral types with different flotation rates and E(t) was the residence time distribution for continuous flotation, dependent on the hydrodynamic state, a function of the flotation cell design and circuit configuration. 



R    1  e  kt F  k  E  t  dkdt R 0





(6.3)

Several other factors influenced the processing of platinum from the Run-of-­ Mine (RoM) through the multifarious stages which were highly mechanised and technology intensive (Steyn and Brooks 2017). The assay values of the concentrate c and the feed f coupled with the tailings ta can also be used to determine mineral recovery using Eq. 6.4 (Asbjörnsson 2013). R

c  f  ta  100 f  c  ta 

(6.4)

Depending on the grinding media employed, the comminution circuit accounted for the highest operating costs due to the energy consumed (Carrasco et al. 2017). The platinum company processed 275 tons of RoM per hour, which was fed through a single SAG mill and single ball mill for each of the company’s two concentrator plants. The ball mill was operated in line with eight hydro-cyclones that were used to classify mill discharge in order to produce an overflow of 75μm concentrate for the flotation circuit. Figure 6.10 shows a model of the concentrator plant’s comminution and flotation circuits, extracted from the plant model that was developed during the case study. Tables 6.13 and 6.14 show some of the data collected for the SAG mill and cone crusher feeds. The company’s two concentrators had the capacity to process 2.2 million tons of ore per year.

6.5  Case Studies

137

Fig. 6.10  The platinum company’s comminution and flotation circuits Table 6.13  Sample SAG mill feed

Screen size (mm) 300 212 150 95 75 53 38 27 19 13 9.5 Total

Mass distribution (kg) 0.0 0.0 12.2 15.7 10.5 14.6 9.3 5.7 4.8 4.2 30.0 106.9

Percentage distribution (%) 0.0 0.0 11.4 14.6 9.8 13.7 8.7 5.3 4.5 3.9 28.1 100.0

Cumulative percentage retained (%) 0.0 0.0 11.4 26.1 35.9 49.5 58.2 63.5 68.0 71.9 100.0

Cumulative percentage passing (%) 100.0 100.0 88.6 73.9 64.1 50.5 41.8 36.5 32.0 28.1 0.0

Targeted particle size distribution (PSD) 100.0 96.5 72.4 53.7 45.2 36.6 30.1 25.8 22.4 19.2

6.5.5.2  Simulation and Experimentation This research utilised data which was recorded during the work study in 2015 and that which was obtained from the company manuals and documentation for their equipment operating capacities and processes. This was used as input to the various

138 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results Table 6.14  Sample cone crusher feed Screen size (mm) 75 53 38 27 19 13 6 Total

Mass retained kg 2.00 18.800 17.600 15.800 13.600 2.900 0.800 71.50

% 2.8 26.3 24.6 22.1 19.0 4.1 1.1

Cumulative % passing 97.2 73.7 49.1 27.0 8.0 3.9 2.8

alternative configurations that were considered in the process of simulation and optimisation of the processes. Arena Simulation Software was used for the discrete and continuous simulation modelling, while Limn Flowsheet Processor was used for establishing connectivity of process units and paths, the combination of which was used to establish performance, identify recovery hampering factors and bottlenecks. As is expected and as per norm for simulation experiments, a number of assumptions were made for the Arena simulation models which included: • Assign module in Arena was used to ascribe the size of the RoM ore from 300  mm boulders down to 75μm throughout the stages of the comminution. However, for consistence in the simulation results, delivery of the RoM to the bunkers was assumed to arrive at a constant rate of about 105 tons in 15 min. • Discrete event simulation was assumed for the modelling of the processes with reasonable delays or nominal residence times that were uniform or followed a particular mathematical distribution. • Process modules to be value adding during the seize-delay-release stages of the comminution circuit. • Entity value of 1 in the Arena simulation model was used to represent 100 tons in the plant due to the volumes of the RoM that were handled periodically. Model assumptions for the Limn Flowsheet Processor simulations were as follows; • Data structures and processes in the models to be based on one-dimensional data layout, while the data layout for the comminution circuit was size based. • The standard two rate per mineral flotation bank model could not be developed due to the limited data, which could not provide for distinct fast and slow floating mineral recoveries. • Tails for granulated matte comprising the 4Es (Platinum, Palladium, Gold and Rhodium) determined the residence times derived from predetermined formulae. • The mathematical models that were referred to in the Limn simulations and for specific workstations were based on the following: –– RoM silo: Simple mixer model (Tengende et al. 2014) –– Cone crusher: Generic crusher model (Johansson 2009)

6.5  Case Studies

139

–– SAG mill and ball mill: Austin model (de Oliveira and Tavares 2018) –– Cyclones and trommel screen: Whitten efficiency model (Narasimha et al. 2014) –– Flotation banks: Modified Kelsall model without entrainment (Bu et al. 2017) 6.5.5.3  Results and Optimisation The results that were derived from the Arena and Limn simulations provided an indication of the performance of the plant after a number of experiments and replications. Two hundred replications with a 95% confidence interval for the cycle time analysis were conducted for the comminution circuit where model outlays the half-­ width value at an average output of 70 across all replications. On the other hand, 1000 replications were conducted for the same confidence interval for flotation. The actual output versus design output of the plant was measured by resource utilisation and queues for the comminution and flotation circuits, from where Figs. 6.11a, b were derived. The two figures compared the utilisation of comminution and flotation equipment against their availability, respectively. For the comminution circuit, the SAG and ball mills had the highest scheduled utilisation with machines seized at 73.3% and 79.6% of the time, respectively; thus, its availability, efficiency and productivity provided a reasonable measure for the availability of equipment in the concentrator. However, the two machines also exhibited the highest waiting time, which culminated in queues of 19.55 and 9.35 tons per hour, respectively, meaning that the SAG mill was the bottleneck in the comminution circuit and thus affected the utilisation of the concentrator. The simulation results also implied that for different levels of equipment utilisation, the overall throughput was affected, as measured by the queueing time. The flotation circuit was designed to recover minerals from high-grade or fast-flowing elements through the roughers and maximum recovery by cleaners and recleaners, column and energy cells. In the flotation circuit, rougher cells had the highest scheduled utilisation and queueing time. Thus, the bottleneck for the flotation circuit were the six 28m3

Fig. 6.11 (a) Comminution resource utilisation, (b) flotation resource utilisation

140 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

roughers, which were the primary high-grade recovery equipment. Reduction of accumulation of ore at the SAG mill became the most critical target to achieve efficiency of the concentrator. Resource utilisation for the flotation circuit was generally low, rerouting of the tailings to several flotation columns. Value addition for the comminution and flotation circuits constituted total productive time of 71.2% and 68.6%, respectively, while work in process contributed between 8.7% and 15.1% of the total time, thus representing the recirculating loads in different stages. The cumulative total of the work in process and non-value added times provided an indication of the process efficiency. The Limn Flowsheet Processor simulation results revealed that the SAG mill consumed 4475kW, whereas the modelled configuration with variable parameters required 3477 kW. If the alternative High Pressure Grinding Rolls were used in place of the SAG mill, 2240 kW would be consumed while maintaining 300 tons per hour, thus realising a 49% saving in energy. The simulation results also revealed that the use of the pre-crusher alternative, the SAG mill, would consume 3158 kW, a 29% saving in energy. All these results needed to be validated and verified as possible errors could have been encountered in coding and experimentation. The RUN tool in Arena was used to debug such errors, enabling the models to be verified and programs edited in stages from one module to another. This also allowed the break-on-module and highlight-module with animations to visualise how entities progressed along the system while observing any abnormal behaviour, which was corrected through logical movements. Event validity was also utilised to verify the model by way of comparing model results to the real plant system, using a 95% confidence interval. Eq. 6.5 was used to obtain half-widths values for the (1-α) confidence level, where α = 0.05, s was the standard deviation and n were the number of replications (Liotta et al. 2016).



H  t n 1,1 / 2

s n

(6.5)

For the flotation circuit, simulation runs were conducted for cell volumes ranging from 28m3 to 50m3, where it was observed that as the cell volumes increased, there was a gradual decrease in throughput. Of the four main platinum group metals, platinum and palladium recovery improved with increases in cell volumes, but the opposite was observed for gold and rhodium. The optimum peak for the recovery was observed at 48m3, where the recovery gain averaged 81% to 83,97% with rhodium recording 91.36%, platinum 82.37%, gold 82.3% and palladium 79.83%. The use of cleaner scavenger cells in the cleaning circuit increased the residence time, thus allowing slow-floating PGMs to be captured before disposal to the tailings dam. Mineral recoveries following the introduction of cleaner scavengers showed rhodium at 86.93%, palladium 84.87%, platinum,81.8% and gold 72.99%. However, the throughput dropped from 125 to 119.41 tons per hour due to the circulating load and nominal residence times. Although it may have been ideal to incorporate a pre-­ crusher before the SAG mill in order to influence the feed size distribution for the SAG, this was capital intensive and also required more routine maintenance and was power intensive compared to the HPGR.

6.6 Conclusion

141

6.5.5.4  Achievements and Conclusion Platinum mining and processing are capital intensive due to the need for appropriate equipment for its multifarious and complex stages, dominated by comminution and flotation. Platinum mining in Zimbabwe is one of the major contributors to the gross domestic product, despite the fact that unrefined ore was exported in raw form for further processing. Nevertheless, the processing of the concentrate matte that was eventually exported needed to be done in an efficient manner in order to realise maximum mineral recovery and throughput. The case study was carried out  at a platinum mining and processing company in Zimbabwe, with focus on the comminution and flotation circuits of the company’s two concentrator plants. Data collected in these two sections were used in modelling and simulation of alternative configurations using Arena and Limn Flowsheet Processor. The use of high pressure grinding rolls in comminution was the preferred option as it was energy efficient and also required less maintenance. The use of bigger rougher cells of capacity 48m3 and increase in rougher bank residence time was recommended to maximise the throughput to 275 tons per hour. The final grade of the concentrate matte increased from 132 to 136 grams per ton. Energy consumed by the HPGR circuit was 8 kW per ton, down from 16.3 kW per ton, thus reducing the overall cost structure for sustainable platinum production.

6.6  Conclusion In response to the increasing demands for the 4th Industrial Revolution and complexities of modern equipment and technology, practising engineers have adopted tools such as modelling and simulation in order to optimise their processes and plants in order to remain competitive. The major challenge in implementing and making use of these tools in Southern Africa was the availability of appropriate expertise due to the increased flight of skilled engineers to other parts of the world, thus creating a shortage of such skills to drive industry. Companies in the region have been forced to import such skills, but the costs were prohibitive, hence the need to bridge the gap between local industry and local tertiary institutions in order to tap on locally available and affordable skills. This chapter focussed on five of the many case studies carried out by academics on secondment in  local industries. The case studies which were carried out at a furniture manufacturing plant, foundry and mineral processing companies demonstrated the provision of solutions by academics for the local industry. The results obtained, which have been adopted and implemented, ranged from reorganisation of the plants using simulation, group technology and machine distance matrices, reduction and elimination of waste, capacity utilisation and improving productivity and throughput for maximum mineral recovery, thus justifying the need for industry to work closely with academia.

142 6  Modelling, Simulation and Optimisation: Case Studies, Research Methods and Results

References Antwerpen, C., & Curtis, N. J. (2016). A data collection and presentation methodology for decision support: A case study of hand-held mine detection devices. European Journal of Operational Research, 251(2016), 237–251. Asbjörnsson, G. (2013). Modelling and simulation of dynamic behaviour in crushing plants. Master’s thesis. Göteborg: Chalmers University of Technology. Baldwin, J. S., Allen, P. M., & Ridgway, K. (2010). An evolutionary complex systems decision support tool for the management of operations. International Journal of Operations & Production Management, 30(7), 700–720. Bloomfield, R., Mazhari, E., Hawkins, J., & Son, Y.  J. (2012). Interoperability of manufacturing applications using the Core Manufacturing Simulation Data (CMSD) standard information model. Journal of Computers & Industrial Engineering, 62(2012), 1065–1079. Bu, X., Xie, G., Peng, Y., Ge, L., & Ni, C. (2017). Kinetics of flotation. Order of process, rate constant distributionand ultimate recovery. Physicochemical Problems of Mineral Processing, 53(1), 342–365. Carrasco, C., Keeney, L., Napier-Munn, T.  J., & Bode, P. (2017). Unlocking additional value by optimizing comminution strategies to process Grade Engineering streams. Minerals Engineering, 103–104, 2–10. de Oliveira, A.  L. R., & Tavares, L.  M. (2018). Modelling and simulation of continuous open circuit dry grinding in a pilot-scale ball mill using Austin’s and Nomura’s models. Powder Technology, 340, 77–87. Goldratt, E. M., & Cox, J. (2014). The goal: A process of ongoing improvement (4th revised ed.). North River Press. ISBN-13: 9781622313945. Harish, V. S. K. V., & Kumar, A. (2016). A review on modeling and simulation of building energy systems. Journal of Renewable and Sustainable Energy Reviews, 56(2016), 1272–1292. Hemelrijk, C. K., Wantia, J., & Gygax, L. (2005). The construction of dominance order: Comparing performance of five methods using an individual-based model. Behaviour, 142, 1037–1058. Inbound Logistics. (2016). Consumer products logistics: Driving shoppers to the mall. Available: http://www.inboundlogistics.com/cms/article/consumer-­products-­logistics-­driving-­shoppers-­ to-­the-­mall/. Accessed 25 Mar 2016. Johansson, A. (2009). Modelling and simulation of cone crushers. In 2009 IFAC Mining, Minerals and Metal Processing (IFAC MMM) conference, IFAC proceedings volumes (Vol. 42, No. 23, pp. 13–18). Liotta, G., Kaihara, T., & Stecca, G. (2016). Optimization and simulation of collaborative networks for sustainable production and transportation. IEEE Transactions on Industrial Informatics, 12(1), 417–424. Mwanga, A., Parian, M., Lamberg, P., & Rosenkranz, J. (2017). Comminution modelling using mineralogical properties of iron ores. Minerals Engineering, 111, 182–197. Narasimha, M., Mainza, A.  N., Holtham, P.  N., Powell, M.  S., & Brennan, M.  S. (2014). A semi-mechanistic model of hydrocyclones – Developed from industrial data and inputs from CFD. International Journal of Mineral Processing, 133, 1–12. Negahban, A., & Smith, J. S. (2014). Simulation for manufacturing system design and operation: Literature review and analysis. Journal of Manufacturing Systems, 33(2014), 241–261. Nimbulkar, S. L., & Dalu, R. S. (2016). Design optimization of gating and feeding system through simulation technique for sand casting of wear plate. Perspectives in Science, 8(2016), 39–42. Okrent, M.  D., & Vokurka, R.  J. (2004). Process mapping in successful ERP implementations. Journal of Industrial Management & Data Systems, 104(8), 637–643. Rahani, A. R., & Muhammad, A. A. (2012). Production flow analysis through value stream mapping: A lean manufacturing process case study. Procedia Engineering, 41, 1727–1734. Rao, R. V., Kalyankar, V. D., & Waghmare, G. (2014). Parameters optimization of selected casting processes using teaching–learning-based optimization algorithm. Applied Mathematical Modelling, 38(2014), 5592–5608.

References

143

Rolón, M., & Martínez, E. (2012). Agent-based modeling and simulation of an autonomic manufacturing execution system. Journal of Computers in Industry, 63(2012), 53–78. Rybicka, J., Tiwari, A., Campo, P. A. D., & Howarth, J. (2015). Capturing composites manufacturing waste flows through process mapping. Journal of Cleaner Production, 91(2015), 251–261. Sagawa, J. K., & Nagano, M. S. (2015). Modelling the dynamics of a multi-product manufacturing system: A real case application. European Journal of Operational Research, 244(2015), 624–636. Schwab, K. (2016). The fourth industrial revolution: What it means, how to respond. World Economic Forum 2016. Davos: WEF.  Available: https://www.weforum.org/agenda/2016/01/ the-­fourth-­industrial-­revolution-­what-­it-­means-­and-­how-­to-­respond/. Accessed 2 May 2020. Singh, R. K., Choudhury, A. K., Tiwari, M. K., & Maull, R. S. (2006). An integrated fuzzy-based decision support system for the selection of lean tools: a case study from the steel industry. Proceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture, 220(10), 1735–1749. Steyn, C. W., & Brooks, K. S. (2017). De-bottlenecking of the Anglo platinum converting process utilizing advanced process control. IFAC-Papers Online, 50–2, 1–6. Tengende, K., Mushiri, T., & Garikayi, T. (2014). Finite element analysis of the RoM Silo subjected to 5000 tons monotonic loads at an anonymous mine in Zimbabwe. In Proceedings of the International conference on challenges in IT, Engineering and Technology (ICCIET’2014), July 17–18, Phuket, Thailand, pp. 79–84. Vinodh, S., Arvind, K.  R., & Somanaathan, M. (2010). Application of value stream mapping in an Indian camshaft manufacturing organization. Journal of Manufacturing Technology Management, 21(7), 888–900. Wang, J., Chang, Q., Xiao, G., Wang, N., & Li, S. (2011). Data driven production modelling and simulation of complex automobile general assembly plant. Computers in Industry, 62(2011), 765–775. Yeh, C.  W., Li, D.  D., & Zhang, Y.  R. (2012). Estimation of a data-collection maturity model to detect manufacturing change. Journal of Expert Systems with Applications, 39(2012), 7093–7101. Yianatos, J., Carrasco, C., Bergh, L., Vinnett, L., & Torres, C. (2012). Modelling and simulation of rougher flotation circuits. International Journal of Mineral Processing, 112–113, 63–70.

Chapter 7

Capacity Building and Sustainability: Research Findings and Recommendations

Abstract  There are several underlying factors that are sometimes ignored while diagnosing companies with low capacity utilisation such as sustainability strategies for continuity and holistic approaches to engineering change management in this era of dynamism in technology. This chapter focusses on establishing the failures that contributed to low capacity utilisation through the various industry partners where engineering academics were seconded. Apart from the apparent observation of the use of conventional equipment, traditional and analytical methods of manufacturing and processing, most of the companies lacked the capital and expertise necessary to boost capacity utilisation, resulting in depressed throughputs and productivity. The data derived from the surveys, observations and interactive interviews complemented the information gathered and documented in Chap. 6, with the aim of demonstrating the sustainable building of capacity for both academia and industry to respond to engineering change management and bridging the gap between industry and academia. Keywords  Adjunct appointments · Appropriate skills · Centres of excellence · Capacity building · Doctoral training centres · Engineering education · Capacity utilisation · Continuity · Systems thinking integration · Self-sustenance · Sustainability

7.1  Introduction In spite of the plethora of natural resources such as minerals and the abundant exposure to solar radiation throughout the year, Southern Africa has not taken full advantage to exploit these opportunities, largely due to lack of expertise, skills and equipment to extract and beneficiate such minerals or tap the abundant solar for © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_7

145

146

7  Capacity Building and Sustainability: Research Findings and Recommendations

sustainable renewable energy purposes (Mohammed et al. 2013). The same challenges have also been encountered in manufacturing where capacity utilisation in the region has perennially remained subdued due to lack of appropriate skills and expertise to drive industry efficiently. Arguably, the region has adequate resources to provide the required raw materials for industry to avoid the import of skills and spares. Almost all countries in Southern Africa were at one time colonies of European countries, most of which have companies dominating operations of the industries in the region. Having inherited functional industries at the time of independence, this was followed by a systematic decline in operations, attributed to several reasons, including political instability and mismanagement, leading to failure to balance imports and exports (Hove 2012).

7.2  Sustainability Planning and Implementation In conjunction with five industry partners directly and several others indirectly, the research on sustainability planning and implementation was carried out mostly by engineering academics from the University of Zimbabwe. The five industry partners were carefully selected from the diverse portfolios of foundry and machine shop, platinum mining and mineral processing, boilermaking and coach building, heavy vehicle maintenance and service and furniture manufacturing. The other companies that were indirectly engaged in the research are listed in Tables 4.4 and 4.5 in Chap. 4. The reason why different and diverse companies were selected was to obtain comprehensive information about the different sectors and not to compare the performance of each of the companies against each other. The results derived from the companies were meant to draw synergies in operations vis-à-vis the challenges encountered in sustainability planning, systems thinking and how these impacted capacity building, efficiency, productivity and capacity utilisation with a view to establish models for self-sustenance. The research carried out by engineering academics at these five companies revolved around observations during the secondments, questionnaire and structured interviews involving engineering and operations managers, engineers and operators such as artisans and shop floor staff. The surveys were guided by the six standard steps proposed and as set out by Creswell (2014). These were summarised as follows: objective of the survey, which was meant to establish general challenges; existence of sustainability planning, or lack thereof, and levels of adoption; involvement of staff; and challenges in implementation. Based on the information and data collected, the focus was to determine and establish the companies’ technologies and equipment used in production, processing, mining or fabrications, the companies’ policies towards continuous professional development, capacity building and utilisation. All personnel at the different levels of the companies were equally briefed on the importance of the survey, the objectives and relevance of collating such information, where it would be used and, more importantly, the emphasis that the results of the survey were not meant for appraising the staff vis-à-vis their performance.

7.3  Capacity Utilisation in Industry

147

Emphasis was placed on the broad objective of improving the company performance through effectiveness of methods, enhanced throughput, efficiencies and increased capacity utilisation. A sample of the survey questionnaire is provided in Appendix A7.1, mostly designed to provide multiple choice answers. The analysis of the feedback from the participants was multifaceted and focussed on content, particularly those that did not provide definite responses. This was meant to synthesise and synchronise them based on the additional comments that respondents made. Interactive interviews and observations were also made at workstations to validate the information gathered through the survey and in synch with the knowledge sharing workshops. The interviews were structured in the same way that the questionnaire was designed and completed by the same groups of respondents, mainly meant to synchronise and verify the answers obtained from the survey. The secondments by engineering academics also involved spending time in different technical sections while collecting data such as processing times, process flows and operations for simulation and optimisation, the information which was used to simulate and optimise processes, as outlined in Chap. 6. Some of the challenges identified from the questionnaire verified the results obtained from the simulation and optimisation of process flows and technologies. In general, the results from the survey showed a general lack of capacity and expertise to formulate sustainability plans and lack of knowledge on what sustainability and systems thinking meant. This was coupled with the absence of policies or budgets for research and development and minimal interventions by the companies for professionally developing or motivating staff through rewards for innovations and performance. With the exception of the platinum mining and processing company, the other four companies faced the same challenges, such as inadequate infrastructure; conventional machine tools that often broke down, thus delaying production; traditional methods of processing and manufacturing that were not supported or computer assisted and thus often slow and inefficient. Among the five companies, the platinum mining and processing was the only one that was ISO certified and had well implemented Safety, Health, Environment and Quality (SHEQ) standards in place, with the rest of the companies operating under unsafe working environments. Interactive observations were generally regarded as effective ways for qualitative research by experiencing first-hand account of the operations for sustainability planning and management in an industrialising country (Saadatian et al. 2010).

7.3  Capacity Utilisation in Industry In general, the challenges faced by the companies, such as waste management, long travel distances in production, backtracking of process flows, conventional machine tools and traditional methods of manufacture, as articulated in Chap. 6 and also derived from the surveys, negatively affected productivity and capacity utilisation. The number of respondents at each company depended on the staffing levels in the

148

7  Capacity Building and Sustainability: Research Findings and Recommendations

production and engineering departments. For the boilermaking and fabrications business, a Government of Zimbabwe subsidiary, the number of respondents were very low because the company had suspended operations due to recession and failure by major shareholders to invest more to revive the business. The skeleton staff they had on the ground at the time of carrying out the research were just a few people monitoring the departments in anticipation of injection of funds to resuscitate operations. Most of the engineers and artisans had been retrenched, but some were offered the option to utilise the company’s available machine tools to run their own operations. Thus, the results obtained from the boilermaking company, which was also involved in coach building, did not provide much significance in terms of the responses provided in the survey. However, the work that was carried out to model the proposed plant for the manufacture of Yutong F11 buses was done in conjunction with the six available personnel who also responded to the survey. The six comprised the managing director, who also happened to be an engineer; three artisans; one accountant; and a marketing officer. The respondents from the other companies were evenly spread as each of the other four companies were in full operation albeit at very reduced capacity utilisation, which was experienced by most companies in Zimbabwe at that time. To a large extent, the numbers also depended on the size of the company and operations. Table 7.1 summarises the results derived from the questionnaire in conjunction with recordings on machine utilisations, transportation distances and wastage during the secondments. Waste was derived from the amount of materials that were removed from the original raw materials using a multi-criteria strategy for sustainability evaluation (Kluczek 2017), particularly for the manufacturing and processing companies. For the heavy vehicle maintenance and boilermaking businesses, the low figures were indicative of the service provision, derived from sundries used in the business, with very low wastage. The number of resources available, both human and machine Table 7.1  Factors affecting sustainability planning and operational strategies Industry

Furniture manufacturing Boilermaking Foundry & Machineshop Heavy vehicle maintenance Platinum mining and processing

Number of respondents 54

Factors affecting sustainability and operational strategies Average Capacity Estimated Plant/factory transportation distances utilisation waste area 36% 23,000 m2 ± 300 m 64%

6 61

10% 39%

26,000 m2 24,000 m2

± 400 m ± 600 m

10% 58%

39

7%

22,000 m2

± 200 m

76%

83

86%

Mining – 10 km2 Processing – 4 km2

± 70 km between mines and processing plants

90%

7.3  Capacity Utilisation in Industry

149

tools, downtimes due to breakdowns and usages, and the machine capacities derived from the survey provided the base for estimating capacity utilisation. The transportation distances were averages derived from the production of selected products as covered in Chap. 6. The results from the survey showed a clear absence of adequate documentation and procedures, the operations of which were often observed to be unplanned, except for the platinum mining and processing company, which was ISO certified and therefore had well-documented procedures and a well-implemented business management system (BMS) and SHEQ standards. Most of their processing plant was fully operational and automated, running on three shifts per day. The slight shortfall of 10% below full capacity utilisation was attributed to the company’s failure to completely refine platinum, although a base metal refinery was being installed at the time of the secondments. The high figure for waste was expected at the platinum mining and processing company as this was due to the comminution and flotation of ore, the bulk of which was discarded as tailings after milling and flotation and slag after smelting. The data and information gathered provided the base for deciphering the importance of the challenges faced by the companies and the need to attend to some of the glaring shortfalls. Virtually at all the companies, 86% of the engineering managers believed that low capacity utilisation was due to the economic recession in the region and in Zimbabwe in particular. However, although they felt it was useful to employ new technologies or strategize for continued and sustainable operations, 66% of this group of respondents felt it was a luxury, costly and an unnecessary investment. The impression from the responses was that it was more critical to focus on the short-term requirements to ensure that the companies survived the recession, and perhaps long-term planning and strategizing could be done when operations normalised. Almost 72% of all three categories of respondents felt that the low capacity utilisation was due to erratic power supplies and unscheduled load shedding that Zimbabwe experienced since the economic recession of 2008. The responses obtained from all categories of respondents at the platinum mining company showed a general deviation from those of the other companies. This was understandably so because of the full automation, foreign ownership of the company and technical backup from the parent company in Australia. Virtually all respondents (90%) in this company were very satisfied with their working environment, state-of-the-art equipment available, the level of automation and continuous professional development supported by the company. Apart from their highly popularised corporate social responsibility schemes such as supporting local communities with amenities such as clinics, schools, provision of water etc., the platinum mining and processing company also had a well-­ established employee share ownership scheme, where all employees were given the opportunity to own part of the company through these shares. This obviously made the company a very attractive employer (Chiunya et al. 2017). More than 80% of the staff from the other four companies, particularly artisans and engineers, expressed dissatisfaction with their working environments, which were largely

150

7  Capacity Building and Sustainability: Research Findings and Recommendations

unsafe due to hazardous waste such as saw dust and, in some cases, inadequate provision of personal protective equipment (PPE) and safe machine tools. The inference derived from this observation and statistic was that even in a struggling economy, worker motivation can help improve company performance in terms of productivity and capacity utilisation, as alluded to by Aviso et al. (2018).

7.4  Capacity Building in Engineering Education As established in earlier chapters, a major challenge faced worldwide was the shortage of engineering skills, albeit at different levels depending on which part of the world. This research was conducted in Southern Africa with occasional reference to the United Kingdom by way of benchmarking an industrialised country in order to draw lessons. Coupled with the shortage of engineering skills, Southern Africa suffered from a persistent mismatch of skills produced by tertiary institutions to those required by industry, primarily due to the wide gap between industry and academia and lack of access to modern equipment and technology by engineering institutions (Kanyarusoke 2016). In addition, tertiary institutions also faced a challenge of the widening gap between young and inexperienced and mostly retired engineering academics. This was one of the major drivers to establish foreign supported interventions such as NUSESA, EEEP and HEP SSA. The high vacancy rates and attrition at most tertiary institutions in Southern Africa were largely a result of migration of engineers to other parts of the world in search of better opportunities (Nyanga et al. 2012). As a result, most tertiary institutions had to make do with available expertise which included fresh graduates and a few professionals in their retirement. However, this was not the same for all countries in Southern Africa but depended on the gross domestic prodcuts (GDP), with most of those with low GDPs suffering the most. Fresh, inexperienced and young engineering academics were not only unable to confidently dispatch their lecturing duties but were also unable to carry out research or lead students in laboratories, due to lack of exposure and the absence of institutional training policies for staff. Invariably, this had the consequential effect of inadequately trained engineers who faced challenges in accreditation by regional professional bodies (Byrne et al. 2013) and hence reduced mobility of engineers within the region and beyond. The implementation plan that was developed for the EEEP was designed to make use of midsemester breaks for both engineering academics and students for secondments and attachments, respectively. Based on the responses from the questionnaire and survey, Fig. 7.1 summarises the significance and level of relationship between HEIs and industry as perceived by industry. This also revealed that industry dealt more with student attachments as the concept for academic secondments was new but in fact helped to enhance the skills and experiences of staff and boost their confidence in lecturing apart from creating opportunities for industrial-based projects. As evidenced by students’ mid-semester reviews and the lecturers’ feedback reports, a blended approach of access to modern

7.4  Capacity Building in Engineering Education

151

Relationship with HEIs 80

Respondents

70 60 50 40 30 20 10 0

Furniture Boilermaking Manufacturing

Foundry and Heavy Vehicle Machineshop Maintenance

Platinum Mining and Processing

Industry and Business Operations Staff Secondments

Student Attachments

Total Respondents

Fig. 7.1  Relationships of industry with higher education institutions

technology and equipment, in the form of both student attachments and academic secondments, was highly recommended. This had the net effect of exposing both students and engineering academics to the same equipment and technology to reduce mismatches. Responses from the survey also revealed that the more capitalised and automated companies, the more interactions there were between the company and tertiary institutions, either through attachments or secondments. Due to scaled-down operations at the boilermaking company, not much could be concluded. The comparative statistic obtained from the few employees from this company simply indicated a desire for such close linkages between industry and academia. Almost the same inference was drawn from the heavy vehicle maintenance company, a well-­ capitalised company but most of their operations and backup were from the parent company in Sweden. All their vehicles were imported, fully assembled and ready for sale and the company’s main business was provision of repairs and maintenance and not manufacturing or assembling. The involvement of both students and engineering academics at this company were limited to maintenance with occasional improvements in some spare parts through import substitution and redesign of some components of the heavy vehicles such as brakes. Evidently, the platinum mining and processing company was not only involved in hosting both students and engineering academics on attachments and secondments but was also heavily involved in supporting tertiary institutions for various interventions. One of the most significant contributions by the company was the provision of a fully funded Professorial Chair in Mining Engineering at the University of Zimbabwe. In addition, the same company, and many of those that were directly or indirectly involved in this research or with NUSESA, EEEP or HEP

152

7  Capacity Building and Sustainability: Research Findings and Recommendations

Respondents

Joint Projects and Sharing of Resources with HEIs 80 70 60 50 40 30 20 10 0

Furniture Boilermaking Manufacturing

Foundry and Heavy Vehicle Machineshop Maintenance

Platinum Mining and Processing

Industry and Business Operations Joint R&D Projects

Sharing of Resources

Total Respondents

Fig. 7.2  Joint projects and sharing of resources between industry and HEIs

SSA, contributed in kind to enhance the training of engineers. Some of these included: adoption of some laboratories in order to ensure that equipment in such laboratories were well maintained and gainfully used by students and staff and provision of various pieces of equipment, as detailed in Chap. 8. Figure 7.2 shows the level of interest derived from interactions with HEIs in terms of joint and industry-­ based projects and sharing of resources. The trend observed from Figs. 7.1 and 7.2 provided sufficient proof that the same companies that interacted well with HEIs evidently had some joint R&D projects and also shared equipment and human resources. For instance, practising engineers from the platinum mining and processing company and those from the foundry and machineshop company frequently provided seminars to both students and staff at the University of Zimbabwe while, and in turn, engineering academics from the University of Zimbabwe also presented CPD courses on latest technologies to practising engineers at these companies. In addition, the same companies shared equipment such as the mass spectrometer at the University of Zimbabwe for metal analysis and the hardness tester at the foundry company, which was used by students for laboratory work. The level of operations and automation at such companies was also in line with the level of support provided and availed to their staff for professional development and training. The platinum mining and processing company actually had a training centre for their own staff and those that they hosted on behalf of the Chamber of Mines of Zimbabwe (2017). Whereas the engineering managers from the other companies were desirous of empowering their staff through interactions with HEIs and continuous professional development, a major limitation was the capacity and funding to do so, apart from the lack of appropriate expertise to offer gainful seminars to students and academics. This research also revealed that secondments can be utilised for the double purpose of exposing engineering academics to modern

7.5  Centres of Excellence and Doctoral Training Centres

153

equipment, methods and technology and following up students on attachments. In addition, shared mentorship of students by practising engineering also helped significantly in closing the gap between industry and academia. Ultimately, the desired capacity with matching skills can thus be built to drive industry.

7.5  Centres of Excellence and Doctoral Training Centres Doctoral Training Centres (DTC) can be thought of as essentially centres of excellence in a particular field of engineering. The establishment of DTCs is really a top-down approach to significantly improving the standards of academic teaching and associated research in the region and thus by association upgrading the standards of engineering teaching, research and practice throughout. This will result in the improvement of the economic and social standing of countries in the region by the use of better applied engineering and the advancement of engineering practice. The effect should be to encourage countries to invest in their own future and improve their economic outlook by obtaining better value for their products and services. This should also help to attract inward investment into the countries to support economic development by allowing investments to generate a better return on capital. The general effect of this would be to improve the living standards of the general population in the region with an increase in the numbers of educated middle class people, such as in the BRICS (Brazil, Russia, India, China and South Africa) economies. DTCs should help the retention of trained and qualified engineers within the region by advancing the career prospects and opportunities available to particularly talented engineers. Currently, academics and teaching staff are often poorly qualified and inexperienced with little research interests. Laboratory equipment, which is needed for teaching and research, may not be available in university departments. This leads to a demotivation of teaching staff who may not be able to give the quality of teaching that they would like. The teaching staff may also feel that there is little prospect of the situation improving significantly in the foreseeable future.

7.5.1  Doctoral Training Centres: UK Perspective The Royal Academy of Engineering’s HEP SSA and the Industry-Academic Partnership Program (IAPP) grants were a relatively small but significant contribution to the advancement of engineering within Sub-Saharan Africa (SSA). However, the Royal Academy of Engineering grants concentrated on encouraging the production of graduates suitable for roles in industry, but these grants were not sufficient in producing future academics or qualified consultant engineers. There are known difficulties within SSA countries of retaining the graduate engineers that are produced as they are often poached by other countries with more advanced economies and

154

7  Capacity Building and Sustainability: Research Findings and Recommendations

technology that are able to offer the opportunities and rewards that may not be readily available in the region. This is serious as graduate engineers service the economy as it is and are very valuable. However, there is a need to move the SSA economies forward by innovation and research, which is the province of engineers with postgraduate knowledge of the particular field. In the United Kingdom, the Engineering and Physical Sciences Research Council (EPSRC) is the main UK government agency for funding research and training in engineering and the physical sciences, from mathematics to materials science and from information technology to structural engineering. In effect, the EPSRC funds a large number of research projects and research centres in the United Kingdom, including the full breadth of engineering and physical sciences, including nanoscience, computing and medical devices. In certain specific fields, the EPSRC has set up doctoral training centres in response to national requirements and to make use of the expertise available in a particular field. In general, students at a UK DTC undertake a 4 -year PhD that is designed to give the students advanced knowledge of the subject area combined with in-depth research experience of the latest equipment and techniques. The most common structure for doctoral training is for the first year to allow students to explore the research area and build expertise in their ‘home’ discipline while developing the skills and knowledge to cross disciplinary boundaries effectively. Students also undertake a formal programme of taught coursework to develop and enhance technical knowledge across a range of appropriate disciplines and enhancing skills. The actual content and the balance between taught coursework and advanced research in each year is a matter for individual universities and associated DTCs, but it is to be expected that the amount of taught coursework will decrease and the amount of advanced research will increase after the first year. Students would be expected to write research paper(s) in conjunction with their supervisors during their 4-year course at the DTC, which would finish with the traditional PhD thesis.

7.5.2  Doctoral Training Centres in Sub-Saharan Africa Although the concept of Doctoral Training Centres has been widespread around the world, including some parts of Africa, such as West Africa, where they have received support from the World Bank (British Council 2018), the concept is fairly new but of necessity in Sub-Saharan Africa in order to bolster the number of highly qualified personnel at tertiary institutions. The aim of Doctoral Training Centres is threefold: • Bringing forward and training new academics and engineers who will eventually become the leading authorities in their particular field, either in academia or in industry • Carrying out focussed research and as a result developing new techniques that can be applied in industry for product development; bringing forward new asso-

7.5  Centres of Excellence and Doctoral Training Centres

155

ciated products and therefore increasing the profitability and value added premium to products • Becoming a Centre of Excellence within the particular field of the DTC DTCs are not really feasible unless the centres combine doctoral training with active research and innovation. A DTC should focus on a particular subject area in the same way as DTCs do in the United Kingdom in order to become a centre of excellence in the subject area. The subject should be closely related to a particular current industry need or an identified field of research innovation linked to that industry or government infrastructure needs.

7.5.3  DTC Initiation and Funding DTCs cannot be funded in the same way as existing IAPP- and HEP SSA-type grants, which are principally aimed at the improvement of the quality of graduates coming from industry rather than being concerned with the quality of the academic teaching staff and the research being carried out in African universities. A DTC will require significant funds for its initiation and then further funds to be sustained over a period of at least 10 years, possibly longer. If the DTC is located in an existing university, the initial set-up costs could be kept to a minimum but will still need office and laboratory space as well as administrative support to be provided for the DTC to function satisfactorily. The use of external facilities to the university provided by either government resources or by industry cooperation could also be considered. Locating the DTC at an existing university would enable the running costs to be minimized. Initially, DTCs could be supported by government grants and funding from other sources such as the World Bank and Overseas Development Funds. These possibilities need to be actively explored to gain sufficient start-up funds for a DTC. It is known that the World Bank has similar aims and could be approached as a potential source of funding as they have a similar programme to establish centres of excellence in West Africa. Similarly, SSA governments in the region should be encouraged to make contributions and that this funding should represent a long-term commitment to the DTC in the same way that government research councils do in the United Kingdom. For a DTC to be successful, collaboration with industry is vital, both as a source of funding and to provide the impetus for the research agenda to be carried out by the DTC. This industry funding is very important as industry should contribute to the costs of problem-solving and consultancy projects that it requires. The same applies for government infrastructure projects where it is in the national interest to gain expertise in the projects and for a DTC to be able to make a significant contribution to the projects. In this context, industries should be encouraged to think in terms of long-­ term projects rather than short-term consultancy projects, although these will also play a part in sustaining a DTC. However, industry is likely to set the agenda for

156

7  Capacity Building and Sustainability: Research Findings and Recommendations

projects, but a DTC should be free to investigate other potential ‘blue sky’ projects in their field of research if they can be justified and show a reasonable chance of success. Sustainability is the key to a successful DTC in SSA. An individual DTC needs to have an absolute minimum life of 8–10 years or about two PhD cycles but could be counted as a successful enterprise if the life extends to 20 or more years while the technology that the DTC supports continues to be current. In this context, government funding on a long-term basis is very important.

7.5.4  DTC Potential Areas of Research in Southern Africa There are a number of potential areas for a DTC in the region, such as aspects of mining, water resources, agriculture, transport systems, energy, food technology and process and systems engineering. Mining seems a particularly promising field for a DTC. There are so many mines of all types in the region which are very profitable for the companies concerned. There are a number of aspects of mining that could be studied, such as the efficiency of mining operations and improving mining practice, particularly with regards to safety. One key area for research would be the extraction of rare earth metals and other valuable minerals from ores in an efficient and economic manner. These metals are becoming increasingly important in advanced technology manufacture and are becoming very valuable. Exploring this would add value to the mining and mineral extraction process, making the products more profitable for the region. For transport systems, modernizing and extending the rail network, either regionally or locally, should be worthwhile. The region seems suitable for high-speed rail links if there is ever the funding available to consider this. However, freight links remain the most economically important part of the rail network. Tram systems for public transport are gradually being introduced in European cities and may be worth considering in an African context. For energy, research into power generation, particularly using renewables and solar power, are always issues for any society. For solar power and other renewables, energy storage is a significant issue. The efficient use of the power distribution grid and the minimization of losses are also important. Eventually economies will transit to a low carbon outlook where conservation of energy has a high importance. Enabling this transition in an African context is important. The use and conservation of water resources is very important for the region together with the associated waste treatment and management. Improvements and new technologies for the management of water resources would be a very good field of research for a DTC. A DTC that might be applicable to a large number of industries is research in the field of process and systems engineering, looking at modelling, simulation and optimisation of production systems to boost efficiency, productivity and capacity utilisation. There are a number of other possibilities for successful DTCs in the region. The United Kingdom has a number of DTCs that are established in a variety of engineering fields from where cooperation could be gained.

7.5  Centres of Excellence and Doctoral Training Centres

157

7.5.5  DTC Implementation and Self-Sustenance For the initiation and running of a successful DTC, funding is likely to be a key issue. Funding will require a number of sources to be successful, both initially and in the long term. When approaching potential sources of funding, it is very important to build a good case for the required support before contacting potential sources of funding, presenting the case and applying. DTCs should be located at places where there is a strong group of academics in the field of interest that can form the nucleus of a DTC. Collaboration with other universities in the region could be used to strengthen a DTC. Collaboration with a corresponding UK DTC in the same or a closely related field is a good strategy particularly in the early stages while a DTC is being established. Initially setting up a few DTCs in the region would be quite an achievement and could lead to others being established depending on the success of the first ones. One DTC in each subject area should be sufficient for the SSA region, but this requires cooperation/collaboration between countries in the region. Individual countries in the SSA region are not sufficiently large to support more than one or two DTCs – eventually it would be preferable to distribute DTCs throughout the region with a DTC for each subject area if regional collaboration can be achieved. Once the concept of DTCs has been accepted as a valid way forward for engineering teaching and research in the region, it would be best to produce the best possible case to be presented to the required authorities, including any and all potential sources of funding. A strategy might be to initially limit the number of DTC applications to 2–4 within the region, concentrating on those with the best chance of success to establish the precedent and show that the concept works. There should be a fitness test for potential DTCs. These are effectively the requirements for a successful DTC, such as: • Is there a potential host university which is prepared to make facilities available for the potential DTC (there are implicit costs involved)? • Are there a core group of senior academics at the potential host university (more can join after the DTC is established and other senior academics from other universities in the region can be actively involved)? • Is the chosen engineering field of strong national, strategic and commercial interest, such that there will be strong reasons to fund the DTC (effectively a Centre of Excellence)? The overall costs for a particular DTC will need to be estimates in terms of facilities, initial research equipment, required additional equipment, staff costs, both academic and technical, and administrative costs. As alluded to earlier, funding will be needed for the initial set-up costs and also sustained funding for a period of about 10 years. It should be noted that for industry-funded projects, Intellectual Property and commercial considerations may well be an issue with suitable arrangements being

158

7  Capacity Building and Sustainability: Research Findings and Recommendations

put in place by the DTC to satisfy these requirements. A key question is how the case for a given DTC will be presented to potential sources of funding, such as the university concerned, the government education department, the World Bank etc. This needs to be considered carefully and as good a case as possible be presented to the relevant parties concerned. An additional question is how will the DTC be marketed to potential students. The concept of Doctoral Training Centres as Centres of Excellence in both advanced academic teaching and research is a good one that has proved to be very successful in the United Kingdom and should also prove suitable for Sub-Saharan Africa. The initial costs and long-term funding for a DTC are relatively high, but the benefits to the SSA region should be considerable in the long run. The focussed research will enable the region to be less dependent on foreign assistance, which may have its own agenda. DTCs will supply the region with a pool of highly qualified engineers who can significantly advance the capabilities of the region to manage their own resources. As centres of research excellence, the DTCs should be able to provide research and innovation that is entirely focussed on African needs.

7.6  Chairs and Adjunct Appointments Equally and as much as engineering academics can contribute to the reorganisation and optimisation of process flows in industry through projects such as those outlined in Chap. 6, industry could also contribute to the development of human resources required to drive industry. Ordinarily, this would not be done in a way that may be viewed as donations to the tertiary institutions but rather augmenting the efforts of governments in funding tertiary education for the development of the required human resources to drive industry. Due to inconsistences in this type of contribution from industry, some governments in Southern Africa have actually imposed mandatory taxation to contribute towards human resources development. Examples of such taxes are: the Zimbabwe Manpower Development Fund (ZIMDEF), the company concession tax system in South Africa, etc. While these were noble ideas of taxation to ultimately benefit industry in general, such funds were managed from state institutions, some of which were mismanaged and abandoned. The industrial training board and the company concession tax systems in South Africa were abandoned due to gross mismanagement and abuse but were later replaced by another system of grants provided, managed by the Department of Labour for the industrial training boards (World Bank 2002). The report also noted that such a noble system was not being used in Botswana due to the lack of knowledge or complex procedures in implementing the policy. In the case of Mauritius, the World Bank report also revealed some complications in the implementation, which led to conflicts over the governing rules of the policy. Faced with such information, this research also sought to look at how such noble initiatives can be properly managed for the benefit of governments, industry and tertiary institutions. The research employed a holistic and systems thinking

7.6  Chairs and Adjunct Appointments

159

approach to integrate efforts by industry through direct interventions such as Professorial Chairs and Adjunct Professorships. The idea of the two options would be direct funding and contributions from industry to tertiary institutions to avoid the bureaucracies, underutilisation or possible mismanagement or abuse of the funds as was the case with the systems in Zimbabwe, Botswana, South Africa and Mauritius.

7.6.1  Professorial Chairs Professorial Chairs have been an avenue created by industry and academia in order to support the development of human resources by utilising skilled personnel. A professorial chair is normally an academic position at a tertiary institution at the level of Full Professor and in recognition of significant contribution to research and knowledge as well as internationally recognised scholarly work. This is usually awarded to individuals who have distinguished themselves in their area of specialisation and normally comes with a full package that may comprise a full salary or top up salary from the industry partner or such other agent supporting the Chair. The package usually comes with a grant to enable the Chair to execute their responsibilities. In recognition of the contribution by the industry partner or funding authority, the Professorial Chair is usually designated and named after both the institution, funding agent or industry partner as well as the area of specialisation. During the EEEP and as a result of the positive interactions between the University of Zimbabwe and Zimbabwe Platinum Mines (Zimplats), the company offered to provide a grant for a fully funded UZ-Zimplats Professorial Chair in Mining Engineering. The intervention came in at the right time as the institution was failing to attract highly experienced professionals in most of the engineering disciplines. This facility enabled the recruitment of a Full Professor from Penn State University in the United States. The responsibilities for such chairs can be many, but this particular one focussed on teaching postgraduate students, mentoring young academics to PhD level, providing technical advice to the funding industry partner, liaising with other industry players to raise funds for research and equipment for the mining discipline at the University of Zimbabwe and providing the leadership and guidance in research and scholarship. The Professorial Chair route is one very clear and transparent way of industry supporting higher education in that the funds are directed to the institution and the recipient Chair will be accountable to both the institution and the industry providing the funds, unlike the levies that have either been abused or underutilised in some countries.

7.6.2  Adjunct or Visiting Professorships Provided the expertise is available in industry, particularly for professional engineers with a reasonable level of education of say up to Master’s degree level, practising engineers can be appointed on a part-time basis to provide tuition for both

160

7  Capacity Building and Sustainability: Research Findings and Recommendations

undergraduate and postgraduate teaching. This concept is practised quite a lot in the industrialised world but different nomenclature is employed. In the United States, such appointments are referred to as Adjunct Professors, while in the United Kingdom they are referred to as Visiting Professors. An Adjunct or Visiting Professor is ordinarily a practising professional employed full time in industry but can teach at a tertiary institution on a limited-term contract and as such not eligible for permanent appointment, commonly referred to as ‘tenure’ by most HEIs. There are many such appointments in the United States and the United Kingdom, and these professionals hold other permanent professional positions such as engineering managers and designers elsewhere. However, there is usually a requirement for them to demonstrate scholarly work, either through recognised and acceptable publications or simply being a ‘guru’ in their area of specialisation. The responsibilities of Adjunct or Visiting Professors vary from institution to institution, but generally, they are expected to spend a lot of time with students to instil and inculcate a culture of professionalism in their area of expertise. As such, teaching and interacting with students becomes the core of their responsibilities of which they are normally remunerated as and when they avail themselves for such duties. However, there is need for flexibility in order to fulfil these responsibilities as they are equally expected to fulfil their professional duties at their companies. Normally, for one to be engaged as an Adjunct or Visiting Professor, an agreement must be reached between their industry employer and the tertiary institution to ensure that none of their responsibilities at both places of work are compromised. Ordinarily, Adjunct or Visiting Professors are not expected to carry out research and publish as is expected of Professorial Chairs or other academics. The major motivation for Adjunct or Visiting Professorships is the desire by many professionals to continually interact with students at lower levels. This has proved beneficial in many ways as students have been known to provide innovative ideas and solutions, which could have long-term impacts and influence on how some of the professionals’ businesses are conducted. In addition, tertiary institutions also subscribe to the idea for such appointments as they have a firm belief that their products (graduates) will have more appropriate experience to match that which is required by industry. More importantly, the human resources cost for higher education is significantly reduced as professionals are paid for their appearance in lectures only, thus no contribution by HEIs to pensions, insurance and other benefits. Thus, in a way, this would be industry’s indirect contribution to human resources development.

7.7  Integrated Approaches Using Systems Thinking The surveys carried out by the engineering academics on secondment at the five companies also sought to derive and establish the relationships, linkages and integration of the operating units through the methodologies they employed, available engineering skills and policies on health, safety and environment as well as general

7.7  Integrated Approaches Using Systems Thinking

161

Elements of Integration 80

Respondents

70 60 50 40 30 20 10 0

Furniture Boilermaking Manufacturing

Foundry and Heavy Vehicle Machineshop Maintenance

Industry amd Business Operations Technologies

Training

Policies

Linkages

Platinum Mining and Processing

Total Respondents

Fig. 7.3  Factors influencing integration

continuous professional and human resources development. This was meant to establish how the integration of these several factors influenced capacity utilisation, performance and productivity of the particular business. In conjunction with the results obtained and presented in Chap. 6, the data collated from the survey, as contained in Appendix A7.1, is summarised in Fig. 7.3. The responses received from section 2 of the survey provided the inferences for deriving the status of technologies at the different companies. These included the age of machine tools, methodologies employed, whether the machine tools were computer numerically controlled or not and the frequency of breakdowns. The information gathered determined whether their equipment and practices were sufficiently modern with computer integrated or flexible manufacturing. Responses obtained from section 3 of the survey (Continuous Professional Development) provided the base for the companies’ training strategies. These included: availability of in-house training programs, support of their engineering staff for further and higher qualifications and how the companies rewarded their staff for exceptional performance. The policies, which were mainly derived from section 4 of the survey but also from the other parts of the questionnaire, included: documentation of procedures, plans for ISO certification, remittances of the training levies to government as well as the companies’ relations and support of higher education institutions and in what form. The responses obtained from section 5 of the questionnaire, coupled with observations made during the secondments, provided indications of the companies’ capacities in terms of volumes that their machine tools were capable of handling, downtimes, operating efficiencies, meeting customer orders timely, frequency of breakdowns and repairs to machine tools. In addition, section 6 of the survey questionnaire provided details of the viability and sustainability of the company operations. The input to the universal systems thinking model for bridging the gap

162

7  Capacity Building and Sustainability: Research Findings and Recommendations

between industry and academia, as outlined in Chap. 12 of the book, was a direct interpretation of the respondents’ views on these various issues, albeit broadly grouped as Technology, Training and Policies. While the foreign-owned and supported platinum mining and processing company exhibited almost 100% of full integration with modern policies and practices such as SHEQ, well-implemented business management systems, fully automated mining and processing plants, support and provision for the development of staff, the other companies appeared to lag behind. This was established from the various operations of the other companies that employed conventional machine tools and traditional methods of manufacturing and processing which were largely manual. About 60% of the engineering managers and 45% of the engineers on the shop floor, but none of the artisans at these companies knew what documentation of processes was and how this could help to improve their operating systems, let alone knowing what systems thinking was all about. The same pattern revealed that documentation and systems management sounded like good ideas, but management at these companies felt it would not be a worthwhile investment to pursue as they doubted the capacities of their juniors to drive such initiatives as sustainability planning. Documenting processes and procedures as well as the adoption and implementation of systems thinking to analyse and integrate different aspects of a company could be helpful in resolving challenges faced by companies in depressed economies, by way of rehabilitating the companies to cope with the effects of recession (Schiuma et al. 2012). However, as evidenced by the surveys, interactive interviews and observations during secondments, the biggest challenge faced by most of the companies was the lack of expertise and knowledge to implement such initiatives. Trying to hire expertise would equally be costly for companies already suffering from the effects of recession but instead, preferred to operate and produce enough to remain in business, hence the notion by some that such techniques were a luxury. Most of the strategies and solutions developed by the engineering academics on secondment, as outlined in Chap. 6, have been adopted and implemented by these companies, a clear indication of the inputs by researchers and academics at minimal cost, most of which can be taken as in-kind costs in exchange for access to modern equipment, technology and industrial operations in order to impart appropriate skills to engineering students. Such potential and capacity was demonstrated by the University of Zimbabwe team of engineering academics and technicians who developed the groundwater project on campus, saving the institution over USD 1 million if professional practising engineers were engaged to undertake the project. This enterprise model is explained in detail in Chap. 13. Engineering change management and transformation has been regarded as the cornerstone to turn around organisations by learning from previous knowledge and using that to develop future strategies for sustainability (Senge 2006). Modern business operations require that the methodologies and technologies employed need to be directly linked to the policies and the required skills in an interconnected manner (Schiuma et al. 2012). Figure 7.4 shows the ideal Systems Thinking model linking the three, distant but related aspects of academia

7.8  Continuity of Donor-Funded Projects

163

+

-

R

B

+

+ +

R

+

Fig. 7.4  Systems integration of technology training and policies

and industry operations, the foundation of which will be used to develop the bridge to narrow the gap between academia and industry. Figure 7.4 summarises the systems integration and links among Technology, Training and Policies. Due to the fourth industrial revolution, technology has been rapidly changing at a much faster pace than before, hence the rapid changes put a strain and increased demand for equal changes in the way engineering students (future engineers) are trained, hence the negative balancing loop. The shortage and mismatch of skills in Southern Africa reaffirms the need for restructuring the training of engineers and the need for curriculum development and review. In the same vein, both industry and academia policies on training and continuous professional development must also change in tandem with the rapid changes in technology, hence the positive  reinforcing feedback loops. Equally, government policies and support for human resources development (training) and the tertiary institutions’ response to meet these demands must be matched.

7.8  Continuity of Donor-Funded Projects As detailed in Chap. 1, several initiatives have been supported by various aid agencies such as Sida and the Royal Academy of Engineering, all in a bid to build capacity and quality of engineering graduates and services they provide in Sub-Saharan Africa. The projects supported under these initiatives progressed well and produced outcomes that matched original objectives. For example, Sida supported four faculties of engineering in Mozambique, Tanzania, Uganda and Zimbabwe to forge partnerships for engineering and technology for sustainable development, focussing on

164

7  Capacity Building and Sustainability: Research Findings and Recommendations

research education and development (Mwamila and Thulstrup 2001). Reasonable strides were made and achievements ranged from collaborative research that led to the establishment of innovative systems and innovative clusters among the partnering faculties to the establishment of NUSESA for the sharing of scientific equipment and expertise. The Royal Academy of Engineering supported similar initiatives through the EEEP program in Eastern and Southern Africa (RAEng 2018). The focus for the EEEP was mainly to address the shortage and mismatch of skills by improving the quality of engineering graduates through secondment of engineering academics and exposing them to industrial operations and equipment. The projects supported by Sida and the Royal Academy of Engineering had noble objectives to reinforce and enhance the quality of engineering education, but both could not continue beyond the funding period. Continuity of such projects has also been problematic in other parts of the world. Some have blamed the recipients of such grants for not taking full ownership to enable the continuation after the sponsorship officially came to an end. This was primarily one of the reasons why the EEEP was modified and scaled up to the HEP SSA scheme under the same support from Global Challenges Research Fund (GCRF) through the Royal Academy of Engineering, which is perhaps also the main objective for this book, to find all the possible ways to bridge the gap between academia and industry using systems thinking. Ideally, this concept was premised on the need and realisation to ensure continuity of such noble initiatives and be able to sustain the objectives. Bringing industry closer to academia is primarily meant to recognise that financial support comes from the productive sector (industry) and should therefore be encouraged to take ownership of the initiatives, instead of leaving this to donor agencies. While the support from foreign aid agencies is appreciated, it should really be considered as seed support, the activities of which should be taken over by the locals (industry and academia). Engineering skills are vital to achieving self-sustenance for capacity building and sustainability, thus less dependence on foreign aid (Nyemba et al. 2016). This book therefore brings to the fore various avenues in which academia and industry can effectively work together, for the benefit of both parties, to take ownership of the initiatives with seed support from aid agencies.

7.9  Conclusion Several studies conducted in Sub-Saharan Africa have revealed the shortages of engineering skills coupled with the mismatch of skills produced by tertiary institutions and those that are required by industry, apart from the evident low quality of engineering graduates. All these challenges pointed to the need to build capacity in order to produce high-quality engineering graduates to drive industry, particularly in this fourth Industrial Revolution era of dynamic and rapid changes in technology. There is a  firm belief that in order to produce appropriately skilled engineers to drive industry, there is a great need to enhance the skills and training of the trainers

7.9 Conclusion

165

(lecturers) by exposing them to modern methods of engineering and manufacturing, technology and equipment in order for them to impart knowledge and skills to future engineers in a more confident and comfortable manner. Several initiatives have been developed and implemented, assisting institutions of higher learning in the process. These included NUSESA, EEEP and HEP SSA, all funded by foreign aid agencies. The initiatives have all focussed on capacity building and the improvement of quality of engineering skills in Sub-Saharan Africa but less focus on sustainability, which is expected to be driven by the recipients of the grants. The main purpose for this book is to bridge the gap between industry and academia using a systems thinking approach of integration. The support from aid agencies has mostly been channelled through institutions of higher learning in Sub-Saharan Africa to collaborate and partner among themselves as well as with regional industries and also in partnership with institutions from the industrialised world. While the foreign aid and support have been useful to drive different objectives to enhance the quality of engineering education, the buy­in and ownership of such initiatives, particularly from local and regional industries, have not been impressive. In order to maintain continuity of such initiatives, support from all key stakeholders, government, tertiary institutions and industry are vital. In most cases, these projects have received full support from governments and tertiary institutions but not much from industry, hence the need to bring industry closer to academia in order to work together for continuity and sustenance of these objectives. This chapter looked at various avenues in which industry and academia can work together and closely for the benefit of both parties in their bid to build capacity for this era of dynamic and rapid changes in technology, using systems thinking integration and research. This included the creation of Centres of Excellence and Doctoral Training Centres by tertiary institutions to offer specialist services to industry to avoid importing foreign skills by industry, which can be prohibitively expensive. Professorial Chairs and Adjunct Appointments could be some of the ways in which industry can directly support the development of human resources, in a more transparent manner than through development levies. The next chapter focusses on more details on access to modern equipment and technology by academics.

References Aviso, K. B., Mayol, A. P., Promentilla, M. A. B., Santos, J. R., Tan, R. R., Ubando, A. T., & Yu, K.  D. S. (2018). Allocating human resources in organizations operating under crisis conditions: A fuzzy input-output optimization modeling framework. Resources Conservation and Recycling, 128(2018), 250–258. British Council. (2018). Building PhD capacity in Sub-Saharan Africa, International Higher Education. London: British Council. Available: https://www.britishcouncil.org/sites/default/ files/h233_07_synthesis_report_final_web.pdf. Accessed: 6 Nov 2020. Byrne, E.  P., Desha, C.  J., Fitzpatrick, J.  J., & Hargroves, K. (2013). Exploring sustainability themes in engineering accreditation and curricula. International Journal of Sustainability in Higher Education, 14(4), 384–403.

166

7  Capacity Building and Sustainability: Research Findings and Recommendations

Chamber of Mines of Zimbabwe. (2017). 2017 – Stae of the mining industry: Survey report. The Financial Gazette. Harare: Zimbabwe. Available: http://miningzimbabwe.com/wp-content/ uploads/2017/12/The-2017-State-of-the-Mining-Industry-Survey-Report-2.pdf. Accessed 12 May 2018. Chiunya, N., Mhembwe, S., & Dube, E. (2017). Community Share ownership trusts in Zimbabwe: Prospects and challenges. International Journal of Education and Social Science Research, 1(1), 1–15. Hove, M. (2012). The debates and impact of sanctions: The Zimbabwean experience. International Journal of Business and Social Science, 3(5), 72–84. Kanyarusoke, K.  E. (2016). Teaching engineering in Sub-Saharan Africa: The need for ‘Pracademics’. In Proceedings of the 6th African Engineering Education Association 2016 (AEEA2016) conference, Bloemfontein, South Africa, September 2016, pp. 153–159. Kluczek, A. (2017). An overall multi-criteria approach to sustainability assessment of manufacturing processes. Procedia Manufacturing, 8(2017), 136–143. Mohammed, Y. S., Mustafa, M. W., & Bashir, N. (2013). Status of renewable energy consumption and developmental challenges in Sub-Saharan Africa. Renewable and Sustainable Energy Reviews, 27(2013), 453–463. Mwamila, B. L. M., & Thulstrup, E. W. (Eds). (2001). Engineering and technology for sustainable development – Research, education and development. In Proceedings of a Regional Meeting, Bagamoyo, Tanzania, October 17–21. Nyanga, T., Mpala, C., & Chifamba, E. (2012). Brain drain: Implications for sustainable development in Zimbabwe. Journal of Sustainable Development in Africa, 14(8), 141–153. Saadatian, O., Tahir, O. M., & Dola, K. (2010). Identifying challenges in implementing sustainable practices in a developing nation. Journal of Sustainable Development, 3(2), 107–116. Schiuma, G., Sole, F., & Carlucci, D. (2012). Applying a systems thinking framework to assess knowledge assets dynamics for business performance improvement. Expert Systems with Applications, 39(9), 8044–8050. Senge, P. (2006). The fifth discipline: The art and practice of the learning organization. London: Random House Business Books. ISBN: 9781905211203. World Bank. (2002). Financing vocational training to meet policy objectives: Sub-Saharan Africa. Africa region human development working paper series. Washington DC: World Bank Group.

Chapter 8

Access to Modern Technology: Smart Partnerships for Research and Practice

Abstract  Several studies carried out in Sub-Saharan Africa have pointed to the perennial and persistent shortage of skills, let alone the access to modern equipment and technology by engineering academics, resulting in the compromised quality of engineering graduates and mismatch of skills required by industry and those that tertiary institutions produced. This has been largely due to the lack of capacity by the institutions to replenish old and conventional equipment. Through several projects instituted in the region since the new millennium, supported by various aid agencies, a situational analysis and research was carried, leading to the development of the smart procurement, use and maintenance model in the form of strategic partnerships with industry. This chapter focusses on the development of this model as one of the feeders to the universal model for bridging the gap between industry and academia for academics’ ready access to modern and relevant technology in industry to enable them to produce quality and employable graduate engineers. Keywords  Build-Operate-Transfer · Capacity building · Engineering equipment · Maintenance · Modern technology · Obsolescence · Original equipment manufacturers · Procurement · Situational analysis · Smart partnerships · Sustainability

8.1  Introduction The Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) was established out of the collaboration of five countries in Sub-Saharan Africa, namely Malawi, Mozambique, Tanzania, Uganda and Zimbabwe in 1989, and by the turn of the new millennium, there were 14 members (Lindgren 2001). A

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_8

167

168

8  Access to Modern Technology: Smart Partnerships for Research and Practice

regional taskforce comprising four faculties of engineering from Makerere University (MU) in Uganda, University of Dar es Salaam in Tanzania, Universidade Eduardo Mondlane (UEM) in Mozambique and the University of Zimbabwe (UZ) was set up to carry out surveys, establish common challenges and proffer solutions for the maintenance of scientific equipment in the region. The collaboration, which dated back to 2001, was supported by the Swedish International Development Cooperation Agency (Sida). One of the significant outcomes of this collaboration was the establishment of innovation systems and innovative clusters, out of which NUSESA was nurtured, with the broad aim of sharing expertise in terms of proper maintenance and use of scientific equipment in the region. The collaboration was prompted by studies which had revealed that research output in engineering in Sub-Saharan Africa may have been seriously affected by the state of laboratory equipment. Therefore, there was need for long-term strategies for sustainable development through the improvement of acquisition, use and maintenance of scientific equipment (Mwamila and Thulstrup 2001). Apart from enhanced capacity building, sustainability and collaborative research, training and exchange of staff among the regional faculties of engineering, one of the major focuses for NUSESA was to establish the state, use and maintenance schedules of common equipment used in the engineering laboratories with a view to foster a culture of preventive maintenance to enhance and prolong the life of such equipment (Nyemba et al. 2017). Scientific equipment, normally used in laboratories for engineering students in most of the countries in Sub-Saharan Africa,, were provided as aid in the 1960s–1970s by the colonial governments when these institutions were established as colleges of universities, mostly from Europe. The equipment also came with expatriate staff who had the skills to use and maintain such equipment. Sadly, when the institutions were weaned off from the parent universities to become fully fledged and independent institutions, no sustainability plans had been created to ensure continuity, leading to deterioration, obsolescence and in some cases underutilisation due to lack of expertise. Ultimately, this meant that engineering students and academics had no access to engineering equipment for their laboratories, let alone modern and relevant equipment used in industry, leading to a mismatch of skills. The challenge of obsolescence of equipment was compounded by the flight of highly skilled technicians who left in search of better opportunities abroad around the same time that the expatriate staff, including academics, and technicians gradually returned to their home countries. This could not have happened at a worse time than the global financial crisis that followed 2008 onwards (Bakrania and Lucas 2009). The collaborating institutions were faced with challenges in maintaining the old equipment, let alone replenish them with more modern ones due to limited financial capacities as the institutions relied wholly on government grants. These revelations prompted the need to carry out research to establish the state of engineering training vis-à-vis available equipment and how it was being maintained and utilised. The research established that apart from the equipment being at least 15 years old, albeit still functional, the technology employed in those machines was outdated. Invariably this resulted in the training of engineering students who were not

8.1 Introduction

169

Fig. 8.1 (a) Analog process control simulator, (b) conventional lathe machines (Source: Nyemba and Mbohwa 2018)

readily employable after graduation. Figure 8.1a shows an analogue pneumatic and process control simulator which was installed in the Department of Mechanical Engineering at the University of Zimbabwe in 1976. While the simulator is still functional, it is no longer relevant for training engineering students, hence resulting in irrelevant skills. In addition, the Original Equipment Manufacturer (OEM) for this simulator, TecQuipment, no longer supported that type, let alone supply the spare parts that may be required. Figure 8.1b, on the other hand, shows a crowd of students sharing conventional machine tools such as the lathe. The number of students at tertiary institutions have continued to rise over the years but with no matches in the increase in infrastructure. Invariably, this also compromised on the quality of engineering graduates and training in general. The research also established that there were virtually no links between industry and academia, which resulted in costly ventures for prospective employers who were forced to either offer further training to graduates from local institutions or ended up hiring costly skills from abroad to maintain their equipment (World Bank 2010). Ordinarily, that training and acquisition of skills were the preserve and responsibility of tertiary institutions. However, due to these incapacitations, tertiary institutions were forced to make do with whatever equipment was at their disposal but regrettably resulting in inadequately trained engineers. To avoid the costly training of engineers after graduation, the onus was on the potential employers to chip in to the training of their future workforce through access to their equipment and systems prior to graduation. Engineering is almost all about working with machines, and such challenges as lack of access to modern and appropriate equipment obviously created scenarios where both academics and students lost interest or developed a fear for working with machines due to the lack of exposure. Apart from establishing the state of equipment and engineering in Sub-Saharan Africa, the research also aimed at utilising the data that was gathered to develop strategies and models that enabled both engineering academics and students to have ready access to modern technology and equipment and improved procurement, use and maintenance while enhancing

170

8  Access to Modern Technology: Smart Partnerships for Research and Practice

capacity building and sustainability in the training of engineers in the region. The strategies and sub-models were eventually integrated into the universal model to facilitate and create formal linkages for bridging the gap between academia and industry.

8.2  Situational Analysis The industrial transformations detailed in Chap. 2 were initially gradual but later became rapid particularly from the 3rd to the 4th Industrial Revolution but more so and to the extent that within the 4th Industrial Revolution, there have been equally rapid changes in technology, equipment and the way of performing tasks. The industrialised world has responded to these changes dynamically and has not only coped with the changes but kept in tandem with the dynamics. However, for industrialising countries, some of which have hardly gone past the 3rd Industrial Revolution, the rate of adaptation has not been the same. Regrettably, there was probably no choice but to keep up with the pace for the rest of the world as the industrialising countries relied heavily on input from the industrialised world, in terms of technology and equipment. During the course of the NUSESA initiative, institutions within the partnership agreed that individually, situation analysis needed to be carried out in order to establish the extent to which such engineering institutions had access to modern equipment and technology based on the state of their laboratory equipment and expertise available to use and maintain these. The results contained in this chapter were mainly drawn from the University of Zimbabwe, although on reflection and comparison, these were mirror images of the state of laboratory equipment in the other three institutions, sufficient enough to draw inferences and make recommendations to improve the accessibility of such equipment to engineering academics in Southern Africa. The rapid and dynamic changes in technology, particularly within the 4th Industrial Revolution, has seen Original Equipment Manufacturers (OEMs) modifying engineering equipment they manufacture more rapidly and to a great extent modifying the technologies and software that drive these machine tools (Martinez et al. 2010). Although there were emerging OEMs, which meant global competition, expected to reduce the cost of laboratory equipment, these remained inaccessible and unaffordable to institutions in industrialising countries (Allais and Gobert 2016). The modifications on laboratory equipment and the technologies and software by OEMs also introduced other dimensions of cost and complexity. Most OEMs are based in and manufacture their equipment from industrialised countries that have the capacity to cope with and keep in tandem with the dynamic changes through continually replenishing equipment whenever changes were made. In some cases, industry or academia entered into agreements with OEMs to facilitate such changes as and when they occurred. Such complexities included the need to continuously develop staff to equip them with skills to be able to use or operate the ever-changing machines and technologies, which was a costly requirement (Ahuja

8.2  Situational Analysis

171

and Khamba 2008). The expertise to provide continuous professional development was usually only available from the OEMs and thus also presenting another challenge for accessibility of the same, apart from maintenance and regular calibration (Ju 2012). A quick survey and analysis of the laboratory equipment at the four institutions showed that they were mostly acquired through the British Overseas Development Authority (ODA) in the cases of Makerere University, University of Dar es Salaam and University of Zimbabwe (Zinyemba 2010) and from the Organisation for Economic Cooperation and Development (OECD) from Portugal in the case of Universidade Eduardo Mondlane (Macauhub 2013). Whereas the aid organisations donated the equipment or provided funds to procure the equipment, the upkeep and maintenance of the equipment were assumed to be the responsibility of the recipient institutions. However, due to limited capacities and paltry government grants, the laboratory equipment was either not replenished or maintained well, leading to obsolescence and in some cases underutilisation. On realising this, most aid agencies now demanded recipient institutions to prove that such donations would not be put to waste by demanding sustainability plans or proof for the availability of expertise otherwise without those, the donors will not readily release such support. Due to the complexities and cost of new equipment, the need for proper use and maintenance became more important than simply acquiring the equipment as more emphasis was now placed on ensuring longer life spans as well as value for money. Taking a snap survey of the institutions, it was also established that apart from the capacity to procure the equipment, the institutions also faced added challenges which were purely administrative, such as lack of maintenance documentation, policies or guidelines for preventive maintenance. While engineering faculties were mandated to develop human resources to drive industry, the ‘products’ in recent years have not quite matched the requirements for industry, due to the type of equipment used in training being at variance with those found in industry. This spelt out the need for academia to work very closely with industry through the formulation of university education to be in sync with operations in industry, particularly in view of the rapid and dynamic changes in technology and industrial systems (Abdullah and Alias 2005). In line with these changes and in particular for technical education, systems of instruction and training needed to be changed and revamped to keep pace with the technology dynamics, ensuring that future engineers were adequately equipped with relevant skills and expertise to use the technology and equipment in industry (Ahmad 2011). Student attachments for problem and industry-based learning as well as secondments, to and from industry and academia, assisted in bringing the two to work closely as demonstrated from various parts of the industrialised world. The exposure to modern equipment and technology by engineering academics and students not only helped to sharpen the lecturers’ practical skills and boost their confidence in delivering lectures through real problem solving but also inculcated a culture for research and development in industry, a trend that was clearly visible in the industrialised world. The two-way connection between industry and academia, that is student attachments and academics secondments and practising engineers’ CPD training and motivational talks to students, helped in cementing relations between the two.

172

8  Access to Modern Technology: Smart Partnerships for Research and Practice

The four institutions under the NUSESA collaboration relied on foreign aid to a great extent. However, these development aid agencies were controlled by their national governments in such a way that there was a limit to which they provided support. The reliance on foreign aid dated back to the colonial times but have continued in recent years although at lower scales. The danger with such support was that it was often unsustainable as it was finite and usually only provided for a limited period, with the expectation that the recipients invested that as seed capital to carry on and develop sustainable activities. Providing the necessary skills through access to modern and relevant technology in industry and promoting collaborations and sharing of resources among institutions within the region as well as strengthening ties between industry and academia helped to achieve self-sustenance and reduce perpetual dependence on foreign aid (Nyemba 2017). As succinctly put by Iung and Levrat (2014), this called for the need to develop systems that met the needs of the present without compromising the ability of future generations to meet their own needs. To prolong the life of laboratory equipment and to avoid the high costs associated with the lack of preventive maintenance, OEMs have encouraged equipment users to stick to stipulated maintenance schedules. In turn, users, particularly institutions of higher learning, were not only sticking to these schedules but also placing emphasis on regular calibration of equipment and replacement of spare parts as recommended by OEMs (Khalaf et al. 2013). In an investigation to establish challenges in transforming manufacturing organisations into product service providers, Martinez et al. (2010) observed that although manufacturing output in the United Kingdom had remained stable and in some cases increases were noted, profitability had actually been declining. This was attributed to global competition, which forced OEMs to reduce their costs in order to remain competitive. The continual improvements of laboratory equipment were necessary in order to curtail costs and contain global competition. This was one of the reasons why there were continual and rapid changes in technology and the software that drove the equipment. Consequently, both OEMs and users of their equipment needed to adopt flexible and adaptive systems management that was not only responsive but agile for an organisation’s key functions, including maintenance. While the major challenge observed in the four institutions was the failure to preserve value of their equipment, let alone the capacity to maintain them, industrialising countries could actually utilise the equipment for both education and research but more importantly to generate income through consultancy services in order to properly maintain the equipment. This can be accomplished in parallel to using the same equipment in the training of students as well as future users and operators of the same equipment (Abu-Goukh et al. 2013). However, this required some effort in engineering change management and the reorientation of mindsets through systems thinking and innovations to transform engineering education (Staniskis and Katiliute 2016). The general framework for the situational analysis conducted by the four institutions under NUSESA was based on a series of meetings and interactive interviews with operators of the laboratory equipment at each of the institutions. In addition, a

8.2  Situational Analysis

173

form was designed for completion by the operators as part of the data collection to establish the manufacturer, origin, cost, frequency of use, operators, age, condition, maintenance schedule and purpose of the equipment among other parameters necessary to establish the status of the equipment. Assistance and guidelines were provided to all the departments that took part in the survey in order to maintain uniformity for the ultimate purposes of comparison. Principal investigators for this research were the chief technicians for each of the participating departments. The pair-wise analysis and results that follow were those obtained from the University of Zimbabwe but with occasional reference to the other three institutions. The series of graphs were descriptive interpretations of the aggregated data which was collected from the existing six departments in the Faculty of Engineering at that time.

8.2.1  Age of Equipment and Origins The Faculty of Engineering at the University of Rhodesia (Zimbabwe), which was a college of the University of London, was established in 1974 with three traditional departments: Civil, Electrical and Mechanical Engineering. The funding and support, inclusive of equipment and staff, were from the British ODA (Zinyemba 2010), hence the bulk of equipment (63%) in the faculty, originating from the United Kingdom, as shown in Fig.  8.2b. In 1985, three additional departments, namely Surveying, Mining and Metallurgical Engineering, were established, albeit considerably smaller than the first three, and these were funded from the German Technical Cooperation Agency (then GTZ and now GIZ) with total equipment contribution of about 20%. Naturally, the OEMs and suppliers of most of the equipment (83%) were either from the United Kingdom or Germany. The rest of the equipment was obtained from other sources, such as Japan through JICA, the United States through USAID and UNESCO-IHE. As evidently shown in Fig. 8.2a, most of the equipment had surpassed 10 years for the newer departments while for the first three departments it had gone beyond 15 years, a statistic which was not very ideal for a tertiary institution mandated with

Fig. 8.2 (a) Average age of equipment and (b) countries of origin (Source: Nyemba et al. 2017)

174

8  Access to Modern Technology: Smart Partnerships for Research and Practice

the development of human resources to drive industry in the 4th Industrial Revolution. Another notable observation from the pair-wise analysis was that only 7% of the equipment was procured from the local Government of Zimbabwe grants, which was primarily the main source for funding tertiary institutions in the country. Even then, with this paltry figure, the equipment procured was the basic kind of laboratory equipment, such as clamping devices, jigs etc., which could be sourced locally. The more sophisticated equipment, such as milling and turning machines, could only be sourced from abroad.

8.2.2  Condition and Utilisation of the Equipment Figure 8.3 shows the pair-wise analysis of the condition of equipment and utilisation of the same for the six departments. A notable observation from this was that for the equipment that was classified as functional but not utilised for teaching, research or consultancy there was a clear indication of lack of expertise, in terms of technicians or academics, for operating such machines. Even though some of the equipment was less than 10 years old, the institution lacked experienced personnel, thus resulting in gross underutilisation. The Department of Surveying recorded a high number (43%) of equipment that were classified as either obsolete or not working. On further reflection, it actually revealed that the machines were not really obsolete but could be utilised in the training of students. However, the low level of staffing in that department could have contributed to this misnomer. While most of the equipment were still operational and being utilised mainly for teaching and research, the uptake for use of the same equipment for consultancy services was very low. This could well have been a great opportunity to generate income for maintenance. This was largely attributed to the young and inexperienced academics within the six departments.

Fig. 8.3 (a) Condition of equipment, (b) utilisation of equipment (Source: Nyemba et al. 2017)

8.2  Situational Analysis

175

8.2.3  Maintenance Expertise and Sources of Spares The most notable observation from all six departments was the absence of maintenance documentation, most of them exhibiting minimum maintenance schedules. In most cases, the departments relied on the few experienced technicians who were still available as well as institutional memory for servicing and maintenance of the equipment, particularly where maintenance manuals were either lost or were unavailable. As evidenced from Fig. 8.4, most of the maintenance of equipment in the first three departments of Civil, Electrical and Mechanical Engineering were performed by local expertise whereas the newer departments relied on outsourcing for repairs and maintenance. This was attributed to the sizes of the departments and the number of technical staff who had been exposed to the functioning and operations of the equipment, whereas for the newer departments, provision of support was limited to procuring the equipment, but no staff had been trained with the assumption that the institution would provide that. The records that were obtained from the six departments were inconclusive and could not provide much in terms of meaningful statistics or inferences since they all relied on breakdown maintenance. Largely, the costs for maintaining the equipment were provided by the institution whenever funds were available. The survey carried out in conjunction with the data collection presented above revealed that all six departments faced common challenges that ranged from old and outdated equipment, underutilised equipment due to lack of expertise and capacity to maintain the equipment or source spares which were mostly imported as these were not available locally, as shown in Fig. 8.4b. In the absence of local expertise or local availability of spare parts, the institutions were forced to import both expertise and spares, and due to inadequacies in funds, some of the equipment ended up not being repaired or maintained. These were part of those that were classified as functional but not in use. This was coupled with the unavailability of imported spare parts, particularly for equipment that OEMs had phased out. On reflection, the general trend of the observations made at the University of Zimbabwe were a mirror image of the other institutions, albeit at different levels.

Fig. 8.4 (a) Maintenance expertise, (b) sources of spares (Source: Nyemba et al. 2017)

176

8  Access to Modern Technology: Smart Partnerships for Research and Practice

The common factors extracted from the four faculties of engineering that were collaborating under NUSESA were obsolescence due to old age and outdated technology, underutilisation due to lack of expertise and non-functional due to lack of spares for maintenance and repair. Almost all the universities had some form of modern or recent equipment, such as Computer Numerically Controlled (CNC) machines, but these were very minimal in all the institutions largely due to them being capital intensive, whereas the numbers of students continued to increase. The bulk of the equipment at all the institutions was above 15 years. This trend needed to be addressed at the training institutions in order to provide appropriately skilled engineers to drive industry in the 4th Industrial Revolution.

8.2.4  Combined Analysis of Factors The underlying patterns and relationships between factors were established from a pair-wise analysis from the results obtained from the situational analysis at the University of Zimbabwe, a mirror reflection of the other three collaborating institutions. The biggest challenges observed were moderate to old equipment coupled with outdated technology which OEMs could no longer support, either in the provision of spares or back up service. The obsolescence of some of the equipment was a result of failure to maintain or use the equipment. Even though the last three departments were established a decade after the first three and thus had newer equipment, the old equipment in the traditional departments were more functional than the ones in the newer departments. This was attributed to two factors, firstly that the equipment were supplied from OEMs in Germany and thus the available manuals were not in English. The departments also relied on institutional memory and the guidance left by German expatriates who had long since left without translating the manuals. Secondly, the newer departments also had less skilled technicians and academics. The three older departments exhibited high percentages of functional equipment and expertise in terms of skilled technicians, translating to higher utilisation of such equipment. The underutilisation of equipment in Civil and Mechanical Engineering was a reflection of the need to train more operators and technicians. The newer departments had expensive but mostly obsolete equipment, and for those which were functional, there was least utilisation due to the low staff establishment (technicians and academics) in those departments. Although most of the technicians had at least 10 years working experience, this was with different and older technology equipment but they had not been exposed to the newer equipment, thus requiring further training and hands-on maintenance and maximum utilisation of the equipment. Staffing in the traditional departments was generally higher, hence better utilisation of equipment.

8.2  Situational Analysis

177

Local maintenance expertise was generally not available for all the departments, although the situation in the traditional departments was much better as industry operating in Zimbabwe at the time were mostly British companies, thus the same OEMs supplied equipment to both academia and industry. However, the shortage of spare parts remained a big challenge due to the non-availability of these locally and the fact that OEMs had phased out the type of equipment. This required some form of innovation that called for a close collaboration between industry and academia in order to be able to manufacture the spare parts as a way for import substitution, a desirable aspect that was revealed by the survey and inputs from the operators. One of the major observations was on the absence of documentation in terms of maintenance and procedures. To ensure longer lifespans for the laboratory equipment, a recommendation was made for the institutions to develop and put in place maintenance policies to address issues of procurement in terms of life cycle costing as a basis for buying equipment in future, and if necessary to translate all manuals into English. In terms of the equipment that was heavily underutilised due to whatever reasons, the same maintenance policy should contain procedures for the disposal of duplicate equipment, some of which could easily be shared among departments or institutions. The funds generated from the disposal could well be used for training of operators and purchasing spares for the retained equipment. Similarly, specialised equipment that was costly to procure may well be available in local industries and through special public–private partnership (PPP) agreements; any research work by academics could be carried out at the company with the specialised equipment. In the same vein, specialised equipment available at tertiary institutions could also be used for industry’s R&D work through the same PPP agreements. Another observation made was that some of the equipment was procured by those in management or individuals within the department with little involvement of the rest of the users. Procurement of equipment should be done holistically, involving all members within the same department or faculty, as there was the danger that if the individual who procured equipment resigned from their post, there was a likelihood that the equipment could either become obsolete or underutilised. This was the case with most equipment which were classified as functional but not being utilised. When most academics and technicians were familiar with equipment in their departments, there were higher chances that this could be used widely, particularly for postgraduate courses and undergraduate projects, to ensure maximum utilisation and the promotion of a culture of research-based learning through which capacity was built. Regional capacity can also be built through the creation of Centres of Excellence (CoE) to offer specialised Continuous Professional Development (CPD) courses by way of utilising available and specialised equipment at these CoE.  Such regional frameworks were not only beneficial for the mobility of engineers within the region but also facilitated regional accreditation of degrees.

178

8  Access to Modern Technology: Smart Partnerships for Research and Practice

8.3  Build-Operate-Transfer Scheme Whereas strategic partnerships between public and private entities have been in existence as far back as the twentieth century, they have become more pronounced in recent years due to the realisation that no entity can successfully operate in isolation but in unison for the benefit of all stakeholders. Even if one party was a customer to the other, parties can enter into agreements to capitalise and benefit from each other’s strengths for the uplifting and benefit of each other’s business. This is the basis on which the concept of Build-Operate-Transfer (BOT) was established and has particularly found wide application in construction projects such as roads, bridges and buildings (Asao et al. 2013). The BOT was a business concept where two parties entered into a concessionary agreement where the recipient provided the space and facilities and the funder provided the capital to execute a project until completion and then operated the business for an agreed period until the initial capital was recovered, at which point the business was transferred or handed over to the recipient. A typical example was where a national government provided space for a private sector construction company to put up infrastructure such as a building or a road at the completion of which the private company can rent out the building or collect toll fees along the road until all the money they initially invested was recovered and the infrastructure was then handed over to the national government for continuation with the business. Such investments through Public Private Partnerships (PPP) have become the norm for flourishing businesses in the twenty-first century as both parties benefit in the long run. Although the BOT concept has been widely pronounced in large construction projects, the same general idea can be extended to purchase of equipment by state-run tertiary institutions, employing the same principles but probably with slightly different timelines and activities. Since equipment may not have the same long lifespan similar to roads, bridges and buildings, the specific arrangements could zero in on equal utilisation of the equipment for teaching, training, research and consultancy. Instead of waiting for the typical duration that may be required for the industry to recover their costs, both parties, academia and industry, can claim benefits from equipment purchased by industry in that academia can offer free research and development services to solve industry problems while utilising the equipment for those services and training students in a specially agreed and specialised concession. Even then, once the initial capital is recovered, the equipment can be handed over to the tertiary institution to utilise it specifically for teaching, training and possibly consultancy services to other companies in need of such services. Unlike roads and bridges, the specific agreements must be explicit on the lifespans of the equipment to avoid taking over obsolete technology. There are however a number of risks associated with such type of agreements, probably the reason why such agreements were not common except in large projects, such as infrastructure development. Some of these risk factors include formulating accurate costs, anticipated revenue in a dynamic environment, contract

8.3  Build-Operate-Transfer Scheme

179

duration and lifespan of the product, whether it be road, bridge, building or equipment (De Marco et al. 2012). Yang et al. (2010) assessed the schedule delay causes for PPPs in construction projects and noted that there were three different risk factors which revolved around technical, financial and political issues, ultimately becoming an intertwined issue which required an integrated approach to avoid such risks. They accomplished this by way of adoption of key success factors through various stages from the concession agreement to handover on completion. However, such risk factors varied from country to country as these are dependent on macroeconomic policies and to some extent political stability. Researchers throughout the world have analysed different aspects of BOT, particularly issues to do with risks and generations of revenue. For instance, Asao et al. (2013) compared the revenue generated from toll road construction in the Philippines using annual and cumulative revenues. Useful information was derived from the research, and this enabled the Philippine government to make informed decisions, especially for future similar projects. However, the experiments and simulations carried out in this research had limited numbers of inputs, which led to the researchers recommending the inclusion of other variable parameters, direct and indirect factors. This is partly the essence of this chapter, to provide such information in developing models that will allow easy access to modern technology by engineering academics, while at the same time benefitting from upskilling students during training. On the other hand, De Marco et al. (2012) established the factors that influenced equity share of BOT projects and also concluded that such projects were affected by inherent risks which required an integrated approach. Based on the foregone situational analysis, a number of risk factors were identified, such as reduced or inadequate grants to procure new equipment or maintain existing ones, underutilisation and the need to train operators and outdated technology. Taking cognisance of all the risk factors identified in the NUSESA collaboration as well as those identified by other researchers from other parts of the world, it was also important to note that although there were so many multidimensional risks in such projects, BOT financing for capital projects has become the norm throughout the world as reasonable returns can be realised to benefit all parties. When economies were booming in Southern Africa in the late 1980s to early 1990s, many companies acquired state-of-the-art machine tools, which were reasonably modern at that time. However, over the years, due to recession in most of the countries, particularly due to the global financial crisis of 2008 (Bakrania and Lucas 2009), many skilled engineers and technicians left the countries in search of better opportunities, leaving a void that led to underutilisation of the available equipment and eventually obsolescence. In circumstances such as these, both industry and academia were affected to the extent that universities could not produce the right skilled engineers and industry did not have the skills to drive industry and in particular manage the ever-increasing sophisticated equipment. Industry and academia needed each other more than ever before. The research on scientific equipment under the NUSESA collaboration therefore sought to establish the various factors that were used to develop a framework to guide tertiary institutions and industry in the procurement of equipment

180

8  Access to Modern Technology: Smart Partnerships for Research and Practice

Fig. 8.5  Systems thinking causal loop flow diagram for the BOT

using a systems thinking and integrated approach to benefit both academia and industry in capacity building and self-sustenance. The approach adopted was the Smart Procurement and Partnerships (SPP) model, which was based on the BOT phenomenon. Figure 8.5 shows the general systems thinking causal loop flow diagram for the BOT scheme from where the SPP was derived. The reinforcing causal loop between academia and governments was that the more support, in terms of grants that the government provided in the development of human resources, the more skills were generated from academia for the development of the country. The balancing loop between academia and industry demonstrated that through secondments and access to modern industry equipment and technology, industry could equally benefit through CPDs. In the same vein, equipment procured by industry through special concessionary BOT agreements can be used by academics for industry’s benefit through R&D solutions to their problems. Government’s provision of adequately trained human resources as well as facilitating BOTs was balanced by taxation from industry for the development of the country.

8.4  Smart Procurement, Use and Maintenance of Equipment While several challenges such as obsolescence, underutilisation, old age technology and lack of skills were identified in the  NUSESA collaboration and results, the focus for EEEP and HEP SSA were meant to find lasting solutions to solve these challenges. Therefore, the focus for this chapter is to develop smart models that

8.4  Smart Procurement, Use and Maintenance of Equipment

181

allow academia to improve access to modern technology to enable them to develop appropriate skills to drive industry, without relying too heavily on unsustainable foreign aid. The results obtained from the collaborating institutions evidently pointed to a need to increase linkages between academia and industry. A systems thinking model that interconnected academia and industry was developed with deliberate links through government key stakeholders in both the development of human resources through the grants that they provided and also their interest in taxation generated by industry. The systems thinking model was based on the BOT principles with obvious variations in relation to operations and was dubbed the Smart Procurement Partnerships (SPP) model (Nyemba and Mbohwa 2018). This was premised on a concessionary arrangement by both academia and industry where academia was assumed to have and provided the expertise for research and development in the provision of solutions to industry’s challenges, such as what has been demonstrated in Chaps. 5 and 6, where solutions were provided through problem-­ based and industry-based learning. On the other hand, the SPP also assumed that industry possessed either the funding required to procure modern equipment and technology or they already possessed the equipment in their operations to allow academics access and use during training, research and consultancy. The role of government in this instance would be to facilitate such linkages through statutory bodies as professional associations, such as the Zimbabwe Institution of Engineers or regulatory bodies such as the Engineering Council of Zimbabwe through appropriate manpower and professional development policies such as the Zimbabwe Manpower Development Policy or the Company Concession Tax System in South Africa (World Bank 2010). While it was reasonable to make these assumptions, it was not entirely accurate as most of the institutions, except those in South Africa and Namibia, did not have adequate skills at reasonably high levels of education, such as PhD. Industries in those countries also faced challenges of using conventional machine tools that often broke down. While this can be argued that academics could still have access to these, it would enable them to impart the knowledge to future engineers as the skills would be ‘appropriate’ for their future employment. This created an additional challenge where engineering students would be trained and confined to old and limited technology, leading to reduced mobility of engineers within the region or abroad. While some institutions and countries were reasonably equipped, the SPP went further to explore the need for stronger collaborations through coopetition, an issue handled in Chap. 9. Partnership agreements for procurement, use and maintenance of equipment can be crafted between individual institutions and targeted industry partners or as consortiums of tertiary institutions and industries, preferably within the same locality for logistical purposes. While the SPP agreements were concessionary, each party would be expected to focus on their strengths, what value they brought into the SPP with the overall aim of saving costs. Figure 8.6 summarises the relationship among the key stakeholders in the systems thinking causal loop  flow diagram for the SPP model.

182

8  Access to Modern Technology: Smart Partnerships for Research and Practice

Fig. 8.6 Smart procurement and partnerships model (Source: Nyemba and Mbohwa 2018)

While the information gathered from the other three NUSESA collaborating institutions of Makerere, Dar es Salaam and Eduardo Mondlane revealed some similarities in the trend for obsolescence, outdated technology and underutilisation of equipment, the move to co-opt the University of Johannesburg (UJ) and Namibia University of Science Technology (NUST) under the EEEP and HEP SSA schemes was a deliberate one to blend institutions within varying income economies. Within the region, South Africa, Namibia and Botswana were regarded as semi-­industrialised economies to the extent that the technology employed in their tertiary institutions and in their industries was a cut above the other SADC countries (SADC 2014) and closely matched with those from the industrialised world. The purpose of bringing such institutions on board was twofold, firstly to take advantage of available modern equipment at their institutions and secondly to collaborate in regional research and pooling of resources for regional Centres of Excellence, as detailed in Chap. 7 and Chap. 9 on coopetition. The SPP was therefore premised on the assumption of such collaborations in view of the unpredictable and unsustainable donor support and reduced industrial activities in most countries within the region, following the global financial crisis of 2008. Being premised on the BOT and PPP phenomena, the overall objective of the SPP was to increase academics’ access to modern equipment and technology, improving the quality of engineering graduates and anticipated savings on R&D costs by industry through focus on core businesses of production by industry and R&D and training by HEIs.

8.5  Consultancy and Research The transformation of the NUSESA initiative to the EEEP and eventually the more recent HEP SSA was prompted by research carried out in conjunction with these projects in order to improve access to and utilisation of modern equipment,

8.5  Consultancy and Research

183

ultimately improving the quality of engineering graduates and bridging the gap between industry and academia. Other similar initiatives carried out in Sub-Saharan Africa, in particular research carried out by Abu-Goukh et al. (2013), revealed that laboratory equipment can be utilised for consultancy services in order to generate income in addition to training and research. This was after the challenges faced in securing financial resources for either maintaining or replenishing laboratory equipment in Sudan. Industrial attachments for students and secondments for engineering academics have also been utilised as avenues to access modern equipment and technology while carrying out research to solve industry’s challenges through problemand industry-based learning (Ahmad and Rashid 2011). In addition, the more enterprising students and academics created opportunities for consultancy services and in some cases, entrepreneurships through creating spin-off companies, an issue dealt with in detail in Chap. 11. The continued exposure to practices and operations in industry not only removed the fear for working with machines but inculcated a research for development culture while ties between industry and academia were strengthened. Through the NUSESA collaborative research, the results did not reveal distinct patterns between the conditions of laboratory equipment and their functions. It was therefore concluded that failure to access equipment or utilise the same was not due to misuse but lack of knowledge and expertise, hence underutilisation and, in some cases, obsolescence. This illustrated the need for regional collaborative research where available equipment could be utilised to the maximum through sharing in order to recover the initial capital investment, whether the source of funds were government grants or from industry. Some of the equipment actually became obsolete even before being used due to unavailability of spare parts and outdated technology where OEMs would have phased them out. In some instances, some of the laboratory equipment did not have operational manuals and some had manuals that were not written in English, thus making it difficult to utilise them. This entailed additional costs for either sending technicians for training abroad or to bring in experts from the OEMs to provide training, a challenge that could readily be solved by collaborative research and sharing of expertise available in the region. The absence of maintenance schedules also meant that some of the equipment were used for long periods without maintenance, thus leading to reduced lifespans. Preventive maintenance routines that may not have been readily available due to lack of skills and expertise were necessary. Appropriate link agreements between academia and industry could also be utilised for the provision of expertise for maintenance. The Smart Procurement and Partnerships model has been tried out at the University of Zimbabwe since 2013, and the results have been quite impressive. One of the platinum mining companies furnished an entire computer laboratory and provided a fully funded Professorial Chair in Mining Engineering, who not only provided services to the company but also mentored young and inexperienced academics. The success of this collaboration led to more companies realising the need to invest in higher education, primarily in exchange for the provision of solutions and contributions by academics for the efficient operations of their plants. Hence, in the same vein, a local telecommunications company provided a live Global System

184

8  Access to Modern Technology: Smart Partnerships for Research and Practice

Fig. 8.7  Equipment acquired through the SPP model

for Mobile Communications (GSM) base station in exchange for academics and students’ provision of solutions to the company. The Southern African Power Pool (SAPP) donated a Day Ahead Marketing (DAM) electricity trading platform, while the Austrian Development Cooperation provided a fully fledged renewable energy laboratory in the form of a solar trailer. Having realised the contributions made by industry towards the training of the much needed human resources, the Government of Zimbabwe also provided additional support to augment these initiatives. Although it was not adequate to cater for all the modern equipment that the Faculty of Engineering required, a computer numerically controlled (CNC) machine for printed circuit boards was procured and used by both students and staff. Figure 8.7 shows pictures of the various laboratory equipment availed to the University of Zimbabwe through the SPP, a move that many companies continued to emulate. All the equipment is now used for teaching, research and consultancy. As alluded to in Chap. 5, the provision of solutions to industry’s problems through problem- and industry-based learning was one clear avenue in which academia could easily gain the support required from industry. Apart from generating income from consultancies or running spin-off companies, the skills acquired from industry by technicians or academics on secondment could be utilised to manufacture spare parts as a way of substituting costly imports. Collaborative research, pooling and sharing of resources among training institutions or between industry and academia can assist in reducing running and maintenance costs, apart from making maximum utilisation of available equipment. The same expertise can also

References

185

be shared through virtual networks especially in view of the restrictions brought on by the COVID-19 pandemic. Although the focus would be for self-sustenance, foreign aid agencies were particularly keen on funding collaborative and regional research and practice instead of solitary work.

8.6  Conclusion A pair-wise analysis of factors was carried out following a NUSESA regional collaborative research at four faculties of engineering in Sub-Saharan Africa. The detailed results used in the analysis were collected from the University of Zimbabwe and compared well with the other three institutions. A combined analysis of the factors was also carried out to establish underlying patterns in procurement, use and maintenance of equipment used in the training of engineering students. The results obtained generally reflected old equipment with outdated technologies that OEMs no longer supported, obsolete equipment due to lack of spare parts and in some cases functional equipment but underutilised due to lack of expertise. Conclusions drawn from the research showed that formalising and improving links between academia and industry would help to strengthen ties and enable academics’ access to modern equipment and technology in order for them to produce appropriately skilled and high-quality engineering graduates. Using the Build-Operate-Transfer phenomenon and systems thinking research, a Smart Procurement Partnership model was developed and has been tried out with phenomenal results at the University of Zimbabwe where students and academics had ready access to various laboratory equipment procured through some special agreements or through secondments in industry. While the NUSESA collaboration was among four institutions with almost the same levels of staffing and status of equipment, the collaboration was expanded through the EEEP and HEP SSA where institutions from South Africa and Namibia, with relatively higher levels of staffing and equipment, were co-opted. This was meant to blend institutions in industrialising and semi-industrialised countries for best practices in terms of procurement, use and maintenance of equipment and policies thereof. This move also resulted in the expanded scope and pooling of resources through Centres of Excellence and Doctoral Training Centres.

References Abdullah, M.  F. A., & Alias A.  J. (2005). University-industry smart partnership in enhancing aviation technology education. In: Proceedings of the 2005 regional conference on engineering education (pp.  437–439). Centre for Engineering Education, Universiti Teknologi Malaysia. Available: http://tree.utm.my/wp-­content/uploads/2013/02/PRT-­Mohd-­Fakhrulrazi-­ A-­Abdullah-­Ahmad-­Jais-­Alias_ok.pdf. Accessed 21 Nov 2020. Abu-Goukh, M. E., Ibraheem, G. M., & Goukh, H. M. E. A. (2013). Engineering education for sustainability and economic growth in developing countries (the Sudanese Case). Procedia – Social and Behavioral Sciences, 102(2013), 421–431.

186

8  Access to Modern Technology: Smart Partnerships for Research and Practice

Ahmad, M.  F. B., & Rashid, K.  A. A. (2011). Lecturers’ industrial attachment programme to increase lecturers’ soft skill and technological competencies for global stability and security. Journal of Sustainable Development, 4(1), 281–283. Ahuja, I. P. S., & Khamba, J. S. (2008). Strategies and success factors for overcoming challenges in TPM implementation in Indian manufacturing industry. Journal of Quality in Maintenance Engineering, 14(2), 123–147. Allais, R., & Gobert, J. (2016). A multidisciplinary method for sustainability assessment of PSS: Challenges and developments. CIRP Journal of Manufacturing Science and Technology, 15, 56–64. Asao, K., Miyamoto, T., Kato, H., & Diaz, C. E. D. (2013). Comparison of revenue guarantee programs in build-operation-transfer projects. Built Environment Project and Asset Management, 3(2), 214–227. Bakrania, S., & Lucas, B. (2009). The impact of the financial crisis on conflict and state fragility in Sub-Saharan Africa. GSDRC Applied Knowledge Series. Available: http://www.gsdrc.org/go/ emerging-­issues#crisis. Accessed 24 Mar 2016. De Marco, A., Mangano, G., & Zou, X. Y. (2012). Factors influencing the equity share of build-­ operate transfer projects. Built Environment Project and Asset Management, 2(1), 70–85. Iung, B., & Levrat, E. (2014). Advanced maintenance services for promoting sustainability. Procedia CIRP, 22, 15–22. Ju, H. (2012). Design a training and maintenance system based on code identification. IERI Procedia, 1(2012), 155–159. Khalaf, A. B., Hamam, Y., Alayli, Y., & Djouani, K. (2013). The effect of maintenance on the survival of medical equipment. Journal of Engineering, Design and Technology, 11(2), 142–157. Lindgren, E.  S. (2001). Sida’s support to Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) Final Evaluation Report. Stockholm, Sweden: Swedish International Development Cooperation Agency (Sida). ISBN: 91-586-8824-2. Macauhub. (2013). Mozambique is 2nd largest recipient of public aid from Portugal. Available: http://www.macauhub.com.mo/en/2013/01/17/mozambique-­i s-­2 nd-­l argest-­r ecipient-­o f-­ public-­aidfrom-­portugal/. Accessed 23 April 2020. Martinez, V., Bastl, M., Kingston, J., & Evans, S. (2010). Challenges in transforming manufacturing organizations into product-service providers. Journal of Manufacturing Technology Management, 21(4), 449–469. Mwamila, B. L. M., & Thulstrup, E. W. (Eds). (2001). Engineering and technology for sustainable development – Research, education and development. In Proceedings of a Regional Meeting, Bagamoyo, Tanzania, October 17–21. Nyemba, W. R. (2017). Engineering skills are the key to achieving sustainable development and reducing foreign aid dependency. Huffington Post (UK) (2017). Available: http://www.huffingtonpost.co.uk/wilson-­nyemba/engineering-­skills-­are-­th_b_14135774.html. Accessed 6 June 2018. Nyemba, W. R., & Mbohwa, C. (2018). Smart and strategic procurement, use and maintenance partnerships in engineering equipment for sustainable development and training in Sub-­ Saharan Africa using a systems thinking approach. In Proceedings: ACRID 2017 European Alliance for Innovation (EAI) International conference for research, innovation and development for Africa, 20–21 June 2017, Victoria Falls, Zimbabwe, pp. 149–158. European Alliance for Innovation. ISBN: 978-1-63190-160-7. https://doi.org/10.4108/eai.20-­6-­2017.2270632. Nyemba, W. R., Mashamba, A., & Mbohwa, C. (2017). Equipment maintenance challenges and solutions for capacity building and sustainability in the training of engineers: the case for the University of Zimbabwe. Procedia Manufacturing, 7(2017), 303–308. SADC. (2014). Integrated paper on recent economic developments in the Southern African Development Community. Central Bank of Lesotho. Available, https://www.sadcbankers. org/Lists/News%20and%20Publications/Attachments/195/Integrated%20Paper%20-­%20 Aug%202014%20Final.pdf. Accessed 8 Mar 2017.

References

187

Staniskis, J. K., & Katiliute, E. (2016). Complex evaluation of sustainability in engineering education: case & analysis. Journal of Cleaner Production, 120(2016), 13–20. World Bank. (2010). Reform and regional integration of professional services in East Africa: Time for Action. World bank report No. 57672-AFR.  Washington: World Bank. Available: http://siteresources.worldbank.org/INTAFRREGTOPTRADE/Resources/ NEWReformProfessionaServicesEAC Report.pdf Yang, J. B., Yang, C. C., & Kao, C. K. (2010). Evaluating schedule delay causes for private participating public construction works under the Build-Operate-Transfer model. International Journal of Project Management, 28(2010), 569–579. Zinyemba, R. (Ed.). (2010). Academia and the dynamics of transformative leadership: The experience of the University of Zimbabwe in the first decade after Zimbabwe’s Independence (1981-1992). Harare: University of Zimbabwe Publications.

Chapter 9

Coopetition and Virtual Collaborations: Global Competitiveness in Research and Practice

Abstract  Collaborations among tertiary institutions for research and other related activities have never been more important, particularly in this era of dynamic and rapid changes in technology. Performance of institutions have also become topical as more ranking organisations have been created to assess the integrity and competitiveness of tertiary institutions. While tertiary institutions were expected to embrace both competition and cooperation concurrently, it was vital to develop strategies that could enhance such collaborations. Many initiatives have been undertaken to address these gaps, but along came COVID-19, which forced businesses to operate under restrictive measures and mostly virtual. This chapter focusses on the Higher Education Partnerships for Sub-Saharan Africa (HEP SSA) and how it has strategised and achieved its goals through coopetition and virtual collaboration as a way of bridging the gap between academia and industry. The results have demonstrated that coopetition was not only a strategy for market share and protection but also led to the access of resources that were usually unavailable in solitary operation. Keywords  Competition · Cooperation · Coopetition · Engineering change management · HEP SSA · Internationalisation · Knowledge sharing · Team performance · Regional integration · SAE2Net · Dynamic trends · Virtual collaborations

9.1  Introduction Coopetition is a modern and innovative business strategy derived from mathematical and game theory aimed at making competitors work together (cooperate) for the benefit of all parties; hence, the word is a portmanteau of cooperation and

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_9

189

190

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

competition (Raza-Ullah et al. 2014). Although it may not have been known as such in the past, it was popularised in the 1990s and credited to Harvard and Yale business professors, Brandenburger and Nalebuff (1996). The insights derived from game theory helped players in coopetition to know exactly when it was best to compete and and when to cooperate. Coopetition was largely driven by mathematical models that were used to establish in what form cooperation among competing parties can increase benefits to all participants and how this can help to grow their businesses and market share, thus allowing competitors to divide the benefits in relative proportions in the same way as buying into or investing in an existing business. While coopetition has been widely applied as a viable business strategy in industry, it can equally be applied to higher education institutions (HEI). It is important to note that all parties into a coopetition must go in with a unity of purpose and not with the intention of outdoing the other party, hoping to knock them out. Parties in a successful coopetition must maintain their individual identities and not for one to appear as having absorbed or swallowed the other. Coopetition models depended largely on the types of businesses in which players strategised to compete and/or cooperate, but whichever way they were modelled, they were based on a value net designated by a diamond-shaped structure with four distinct players at each corner; comprising the competitors, complementors, suppliers and customers (Del-Soto and Monticelli 2017). Complementors were usually competitors whose products and services added value to the business strategy in coopetition. Figure 9.1 shows a typical and simplified value net system for the business of higher education and training. The objective of the coopetition strategy in this regard was to progressively move the participants from a zero-sum game in which the winner took all and the loser was left with nothing to a plus-sum game where the end result was when competitors beneficially worked together in a more profitable manner. During this process, it was vital to identify which variables affected the participants and influenced them to either compete or work together and also to be careful and aware when it was a participant’s advantage not to be part of the coopetition strategy. There are obviously pros and cons for businesses to enter into coopetition or to opt out, but this has to be with extreme due diligence, the deciding factors being the customers, suppliers and those producing complementary products that added value to the business strategy.

9.2  Coopetition in Higher Education Higher education institutions are mandated to develop human resources required to drive economies throughout the world. The financial support for these institutions usually comes from the governments in the form of grants in the case of state-run institutions. This was particularly the case with government-run institutions in Southern Africa where a small proportion of the funding came from tuition fees paid by the students (Teferra 2013). However, for industrialised countries, such as the

9.2  Coopetition in Higher Education

191

United States and the United Kingdom, a significant chunk of the funding came from the private sector through grants for research, consultancy and related activities (Zhang et  al. 2016). Whichever way the institutions were funded, they were expected to perform well enough to produce competitive human resources for the future. In recent years, there have been more organisations established to rank institutions by looking at a number of parameters, such as the number of scholarly publications, level of qualifications and number of academics within an institution, infrastructure, access to the institutions’ online resources, among various other performance and measurable characteristics. In a way, the ability to resource and train graduates for the future was the competition among tertiary institutions. One of the leading HEI-ranking organisations is the Times Higher Education (THE), which assesses and ranks institutions annually by subject areas as well as overall rankings in the world. The original criteria employed by the THE comprised 13 indicators, which were categorised in five segments as follows: teaching (30%), research (30%), citations (32.5%), international mix (5%) and industry income (2.5%) (Times Higher Education 2010). Within each category, it was really the quantum that mattered, for example the number of publications and citations that each institution amassed annually, but this had to be from internationally recognised publishers. As such, many respected publishing houses such as Elsevier and Thomson Reuters were part of this evaluation of HEIs. The evaluations have been further expanded to include rankings throughout the world, rankings by subject area and rankings within certain and comparative regions of the world such as Asia, Latin America, BRICS and Emerging Economies. However, in such methodologies, there are always some outcries from other quarters such as industrialising countries that have raised concern over the authenticity and sometimes ‘unfair’ criteria and associated scores, which sometimes sidelined non-science subjects as well as non-English instructing institutions (Lim 2018). However, regardless of the issues that may be raised, systems were necessary to evaluate the integrity, reputation and competitiveness of these as business enterprises. On the other hand, publications and citations of researchers from different institutions carried more weight than those from the same institution, hence the need for cooperation in research and teaching. Relationship networks in general and in higher education in particular were the basis upon which coopetition was grounded, a more recent and modern strategy between industry and academia. This was the basis upon which institutions described in the next section were based, in collaboration with peripheral (complementing partners), with the fundamental inquiry on how regional institutions of higher learning used the combination of cooperation and competition to foster their mandates in the development of human resources and solving industry’s problems through regional integration and collaborative research. Coopetition has been employed in the contextual and process approaches where it was visible in the value chain of an organisation made up of customers, suppliers, competitors and complementors (Fig. 9.1). In this regard, coopetition can be experienced in game theory, as previously alluded to. As a process, coopetition employed strategies of competition and cooperation concurrently between competing players through different levels of interactions.

192

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

Fig. 9.1  Value net system for coopetition in higher education

Coopetition has been applied successfully in the business world, with recent examples such as Facebook and WhatsApp (Esayas 2017), Amazon and Kindle (Ritala et al. 2014) etc. The important aspects of these business strategies and collaborations was that while cooperation added value to a player, competition divided that value, hence the need to isolate and separate the cooperation and competition thrusts in view of the dynamic nature of such business partnerships. As such, when entering into such relationships, it was vital to scrutinise the boundaries between cooperation and competition (Cygler and Sroka 2016). Coopetition strategies were therefore useful to establish how competition and cooperation can be employed concurrently, the timing of which differs depending on the dynamism of the relationship. Despite its weak global linkages, Southern Africa was one of the worst affected regions of the world after the global financial crisis of 2008 (Bakrania and Lucas 2009) because of its heavy reliance on foreign aid and expertise. The global financial crisis left many industrial operations as well as tertiary education suffering economically from globalisation. This was further worsened by the COVID-19 pandemic, forcing many players, including industry and academia, to

9.2  Coopetition in Higher Education

193

adapt to the new normal for the twenty-first century as well as virtual and online operations. Naturally, under such circumstances, tertiary institutions were expected to take the lead and come up with new innovations and ways of doing business. Hence, the emergency of policies and strategies to cope with such demands and effects of the COVID-19 pandemic, such as virtual collaborations, online learning and teaching, development of virtual laboratories for students in the case of engineering and other practically based courses. This thrust has not only encouraged but forced tertiary institutions to collaborate. As depicted in Fig.  9.1, academia was mandated with the development of human resources which were in turn used to develop the countries through industrialisation. There was therefore a need for engineering change management and new inter-institutional arrangements. While some studies and research have revealed the need to cooperate in the education sector, demonstration of competitiveness remained a key requirement for the integrity and value of programs offered by tertiary institutions. This chapter explores interactions and collaborations among HEIs in Southern Africa in liaison with peripheral partners such as industry, government, research organisations and professional and regulatory bodies in a systems thinking manner. Under normal circumstances, engineering change management started with the institutions and then strategically filtered to the other complementary organisations.

9.2.1  V  irtual Collaborations and Networks in Higher Education In view of globalisation and the COVID-19 pandemic, businesses including academia and industry have adopted a new normal (World Bank 2020). Faced with travel restrictions and social distancing, the traditional approaches to physical interactions at conferences, face-to-face teaching and physical collaborative meetings for research and related activities have been abandoned or scaled down. Development of strategies to grow businesses under the circumstances had to be developed, and naturally, this started with innovative arrangements such as online teaching and conferences. However, this has been problematic for science and engineering professions where access to laboratory equipment was a vital necessity, hence the worldwide development and expansion of the concept of virtual laboratories (Ray and Srivastava 2020). Virtual collaborations and networks therefore entailed interdependent groups of professionals working across the globe in different geographical boundaries, with communication networks to facilitate the networking. As a response to globalisation and the restrictions on travel, virtual networks have become the new normal and basic requirement for any business, be it in academia or industry. The main aspects for collaboration in higher education were the ability to cooperate in research which addressed common challenges, possibly regional ones, deliverables and team performance and knowledge sharing across the country and institutional borders. While virtual team performance was derived from the level to

194

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

which the institutions in collaboration achieved their objectives and deliverables, knowledge sharing required individual researchers or institutions sharing their experiences with partners in order to foster acceptable solutions that were repeatable. However, while this summed up the cooperation among the collaborating institutions, they should still be evaluated individually to determine their world rankings, thus competition. Invariably, this resulted in complex networks where assessors must possess tools and the ability to evaluate performances individually and collectively, leading to whether or not competition and cooperation provided a trade-off for outcomes and impacts such as knowledge sharing and collective performance. This chapter focusses on virtual and online collaborations as opposed to physical interactions.

9.2.2  Coopetition at Multiple Levels in Higher Education The use of coopetition in pursuit of capitalising on the strengths of partnering entities in order to boost their fortunes has been on the increase over the years (Brandenburger and Nalebuff 1996) due to a multitude of factors that motivated or encouraged businesses to collaborate in the complex network of interactions. Despite the increase in the adoption of coopetition, in some cases there were visible tensions that emanated from the relationships and interactions between two parties. Conceptual frameworks to address these tensions holistically have been developed by researchers over the years by segregating the features that contributed to these tensions and how they can be resolved (Raza-Ullah et al. 2014). Coopetition must be visualised and appreciated through an analytical lens as it involved rival organisations in collaboration and the complexities therein. The motivations for organisations to enter into coopetition were not always the same; hence, there was also an imbalance in expectations. There were also dangers that one interaction or party turns out stronger, and this introduced the risk of the possibility of minimal benefits to be gained from the coopetition, which led to dissolution of the partnership or the complete absorption or ‘swallowing’ of one party by the other(s). Thus, one of the major objectives for a successful coopetition would be for the implementers to be strategic to avoid such eventualities by way of balancing the relational matrices. Partly, this chapter explores ways in which such collaborations in higher education were unified through the use of segregation of responsibilities and multiple levels for successful coopetition. Whereas the concept for coopetition has been embraced by many, especially those in industry and business operations, by taking advantage of the strengths of parties, the multiple levels of the strategy were still in the developmental and growth stage as players continued to improve its operation systematically to realise benefits for all parties (Raza-Ullah et al. 2014). It was essential to distinguish the level of coopetition in line with the effects of partners. Tertiary institutions entered into coopetition at different levels in order to minimise risks and uncertainties, maximise benefits, create opportunities for grants from industry, while ultimately improving

9.3  Higher Education Partnerships in Sub-Saharan Africa

195

the quality of their graduates and world university rankings. Multiple levels of coopetition were also beneficial and strategic to penetrate industry for the much needed support for research and innovation while influencing other stakeholders such as research organisations, government and professional bodies. High or low levels of tension in strategic collaborations in higher education can obstruct operations, resulting in reduced benefits and performance of parties. There must be a clear understanding of the possible tensions between coopetition partners in order to manage them. In general, the different levels of coopetition can be classified in five different categories: individual (researchers collaborating and co-authoring research but also competing for promotion), intra-institutional (within the same institution), inter-institutional (between institutions), network and inter-network.

9.3  Higher Education Partnerships in Sub-Saharan Africa 9.3.1  NUSESA and EEEP Coopetition Models Several initiatives have been supported by international aid agencies to enhance the training and quality of engineering graduates in order to respond to the demands of the fourth Industrial Revolution. These included the Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA), supported by the Swedish International Development Cooperation Agency (Sida), which was a collaboration of the Faculties of Engineering at the Universities of Dar es Salaam, Makerere, Malawi, Eduardo Mondlane and Zimbabwe, later growing to incorporate other institutions within the region. While many strides and successes such as sharing of scientific equipment, expertise, exchange of professional staff and knowledge sharing were realised, the initiative could only live up to the end of the funding period but the concept of innovation systems and innovative clusters continued, albeit at a lower scale due to insufficiencies in funding. Following studies carried out in the region, including evaluation of the NUSESA initiative, the Royal Academy of Engineering provided support to the Universities of Zimbabwe and Dar es Salaam to lead as hubs for the collaboration of engineering faculties in Southern and Eastern Africa, respectively, in hub and spoke arrangements where the two universities led the other institutions for three main objectives and activities: knowledge sharing, secondment of engineering academics to industry and professional development of both engineering academics and practising engineers. Figure 9.2 shows the hub and spoke arrangement that was put in place for the collaboration and implemented from 2013 to 2015 with loose links to a few industry partners and related organisations (Nyemba et al. 2019). The Enriching Engineering Education Program (EEEP) as it was referred to, had a major thrust and different from NUSESA in that it emphasised the inclusion and participation of industry as the major recipient of human resources developed by universities. The partnering institutions comprised the University of Zimbabwe as the hub (lead partner) and six spoke institutions in Southern Africa, namely the

196

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

Fig. 9.2  EEEP hub and spoke arrangement (Source: Nyemba et al. 2019)

University of Botswana, Universidade Eduardo Mondlane, Polytechnic of Namibia, Chinhoyi University of Technology, Harare Institute of Technology and National University of Science and Technology, Zimbabwe. The peripheral or advisory partners who did not have much influence or control included the Government of Zimbabwe through its Ministry of Higher Education, the Zimbabwe Institution of Engineers, the Research Council of Zimbabwe, Scientific Industrial Research and Development Council (SIRDC) of Zimbabwe and very few industry partners such as Zimbabwe Platinum Mines and the Zimbabwe Electricity Supply Authority (ZESA). The EEEP also realised some major accomplishments, such as financial and material input from industry, which included laboratory equipment and one Professorial Chair in Mining Engineering at the University of Zimbabwe. Engineering academics who were seconded to industry from four departments at the University of Zimbabwe, developed a groundwater system as an example of a production enterprise to solve the institution’s perennial water challenges. Academics from Civil Engineering designed and constructed the sump, water tanks and excavations for the pipe work, those from Surveying provided the optimum routes and levelling of the pipeline network, those from Mechanical Engineering designed and sized the pumping station and provision of the purification of the water while those from Electrical Engineering designed the electrical power system and control of the

9.3  Higher Education Partnerships in Sub-Saharan Africa

197

groundwater system. Since 2013, this typical intra-institutional coopetition has been providing sufficient clean water to the university community of 20,000 students and 5,000 staff. Ordinarily, this would have cost the UZ in excess of $1 million, but all the professional work and fees were covered by the academics.

9.3.2  HEP SSA Coopetition and Virtual Model: SAE2Net While substantive achievements were recorded under the NUSESA and EEEP coopetition models, the lack of firm support from local governments and industry partners may have contributed to the slow uptake of some of the recommendations. Both local governments and tertiary institutions had not completely bought into the initiative in order to take ownership. However, the Royal Academy of Engineering noticed a lot of potential in the collaboration by institutions in Southern Africa that they decided to further expand and scale up the activities by including more institutions while placing emphasis on involving all stakeholders, particularly industry, in a refined initiative of the Higher Education Partnerships in Sub-Saharan Africa (HEP SSA) that stretched from Southern to Eastern and West Africa. The focus for this chapter is on this expanded version of EEEP and in particular the HEP SSA project that was implemented in Southern Africa. In 2019, the University of Zimbabwe once again teamed up with seven institutions in Southern Africa and one in the United Kingdom where they successfully applied for a HEP SSA grant from the Royal Academy of Engineering, focussing on building on the EEEP achievements and resolving challenges encountered, aimed at strengthening ties and bridging the gap between industry and academia using a systems thinking approach for capacity building and sustainability through innovation, industrialisation, entrepreneurship and commercialisation. The emphasis in this thrust was to involve industry more, and hence, there were five industry partners, primarily meant to buy into the initiative and take ownership together with tertiary institutions. One of the key deliverables for this HEP SSA initiative was to develop a network of engineering institutions and industry in Southern Africa to improve the quality of engineering graduates and the practice of engineering in general. Figure 9.3 shows the revamped hub and spoke arrangements for the HEP SSA partnership that was inaugurated in 2019 (Nyemba et al. 2020). The first deliverable for the HEP SSA project was to establish the Southern Africa Engineering Education Network (SAE2Net), a coopetition model through which the various objectives for strengthening ties with industry would be achieved. SAE2Net was thus an association of HEIs, established to forge a strong, demand-­ driven and sustainable network of universities, research institutions and industry in Southern Africa, leveraging on expertise from the United Kingdom through the UK partner, University of Leicester. SAE2Net comprises of eight tertiary engineering institutions of higher learning in Southern Africa with the University of Zimbabwe as the hub and seven spoke institutions, namely the University of Johannesburg, Universidade Eduardo

198

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

Fig. 9.3  Revamped hub and spoke HEP SSA arrangement coopetition model

Mondlane in Mozambique, Namibia University of Science and Technology (formerly Polytechnic of Namibia), Chinhoyi University of Technology, Zimbabwe National Defence University, National University of Science and Technology and Harare Institute of Technology, all from Zimbabwe, as well the University of Leicester as the UK partner. These nine institutions (inner ring on Fig. 9.3) formed the core of the competitors and co-operators, anchored by the complementors (outer ring on Fig.  9.3) that comprised policymakers, in this case the Government of Zimbabwe through the Ministry of Higher and Tertiary Education, Innovation, Science and Technology Development, five industry partners representing the various disciplines within engineering, namely Econet Wireless for telecommunications, Pretoria Portland Cement (PPC) for manufacturing, Masimba Holdings for construction, SINET Africa for Renewable Energy and the Chamber of Mines of Zimbabwe, for all the mining and mineral processing companies. The collaboration was also anchored by professional bodies like the Zimbabwe Institution of Engineers (ZIE) and regulatory bodies, the Postal and Telecommunications Regulatory Authority of Zimbabwe (POTRAZ) and the Engineering Council of Zimbabwe (ECZ), as shown on the outer ring on Fig. 9.3.

9.3  Higher Education Partnerships in Sub-Saharan Africa

199

For sustaining activities under the HEP SSA and SAE2Net initiatives, the major support came from the Royal Academy of Engineering, income generated from Continuous Professional Development (CPD) courses conducted by the tertiary institutions under the HEP SSA coopetition model. The five industry partners were not only carefully selected to represent the wide range of disciplines in engineering but were from Zimbabwe, simply for logistical reasons. Although the official partners were five at the time of inauguration, these have grown through secondments of engineering academics to industry, inclusive of Mikrodev Southern Africa in Johannesburg, Maputo Thermal Power Station in Mozambique, Virgo Energy Group in Namibia, Chloride Zimbabwe and Turnall Holdings Zimbabwe. Many of the companies have also provided support for secondments through in-kind contributions such as provision of accommodation and meals for the secondees who were stationed at the companies out of their home areas. The participants for CPDs were local practising engineers, and thus the income generated from such professional courses was also in a way industry’s contribution to the development of human resources and the improvement of the quality of engineering graduates and the engineering profession in the region. SAE2Net aimed at expanding the funding basket to sustain its activities through offering of more and a wide variety of engineering CPD courses to practising engineers, royalties from innovative projects, innovations or patents supported to commercialisation, consultancy services and spin-off companies from problembased learning (PBL) and industry-based learning (IBL) initiatives. While SAE2Net was mooted during the EEEP, it was formally established in 2020 to pool and share complementary resources among its members and strengthen ties and bring industry closer to academia using systems engineering for capacity building and sustainability by way of utilising potential expertise and access to modern equipment and technology at the various industrial operations. The solutions provided by engineering academics on secondment were used as a way of convincing industry to get involved in the training of engineering students to provide for future engineers to drive industry. The operation of SAE2Net from the second quarter of 2020 and beyond was altered in line with the COVID-19 restrictions, and thus all activities were virtual or online. This has been one of the major departures from NUSESA and EEEP which turned out to be a blessing in disguise in that much of the travel budget has been channelled for other uses as virtual and online execution of the collaboration appeared to be quite effective. SAE2Net coordinates all its activities through the network to promote and enhance engineering practice in the region in line with rapid and dynamic trends in engineering technology aligned with the fourth Industrial Revolution through various objectives.

9.3.3  HEP SSA Coopetition Model Objectives Systems thinking was an approach to integration that was based on the belief that the component parts of a system acted in a beneficially cooperative manner when connected to the system’s environment or other parts of the system (Arnold and

200

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

Wade 2015). It was this belief upon which the collaboration through SAE2Net was conceived in order to bring various aspects required in the development of engineering academics to solve the regional shortages of engineering skills and mismatch of the skills produced by HEIs and those required by industry. Through the broad aim of bringing industry closer to academia, the HEP SSA project focussed on improving the quality of graduates produced by HEIs and their fitness for subsequent roles in industry or further academic study. This was accomplished by improving the quality of the academics responsible for teaching and also improving laboratory and other equipment used in teaching. While the main thrust for SAE2Net was to pool complementary resources, both human and equipment, the first objective was to deliver and strengthen jointly owned regional postgraduate degree programs and specialised Continuous Professional Development (CPD) training in Engineering through Centres of Excellence (CoE) and Doctoral Training Centres (DTC) at particular institutions, to promote the mobility of engineering students and graduates within the region, ultimately boosting sustainability and avoiding duplications. Initially, eleven CPD courses were selected to be offered by engineering academics within the partnership to practising engineers and technicians in industry. The database for such courses and the demand continued to increase, thus realising the quality of engineering as well as income to sustain activities of the network. On average, not more than 25% of engineering academics who teach in engineering faculties in Southern Africa were trained up to PhD level (Government of Zimbabwe 2018). The majority of the academics were Masters holders. This has partially contributed to the mismatch of skills required by industry and those that the HEIs produced. As part of HEP SSA’s endeavour to establish and forge a strong, demand-driven and sustainable network of universities and industry, strengths at each of the partnering institutions were identified, sufficient to establish Centres of Excellence (CoE) and the phased implementation, as shown in Table  9.1. Apart from offering specialised training in CPDs for practising engineers and academics, the CoE were also earmarked to spearhead the training of engineering academics to PhD level through the DTCs. Through these strengths and overwhelming acceptance by HEP SSA members, nine DTCs were agreed upon, as shown in Table 9.1, with the inclusion of the University of Cape Town, originally not part of the SAE2Net coopetition model but brought in specifically to complement the other regional institutions with their expertise in mining and mineral processing. The phased implementation of the DTCs commenced in 2020 with the first three expected to be operational in 2021, on the basis of which the rest will be established. Ideally, academics from partner institutions enjoyed the benefit of the availability of specialised training at partner institutions for either CPDs or training up to PhD at negotiated and reduced tuition fees. In addition, the institutions also entered into a Memorandum of Agreement for the sharing of resources, particularly laboratory equipment and specialised technical skills. Secondments of engineering academics to industry as initiated in the EEEP remained one of the key objectives for the collaboration between industry and the partnering institutions. This exposed them to modern equipment and technology,

201

9.3  Higher Education Partnerships in Sub-Saharan Africa Table 9.1  Southern Africa doctoral training centres under the HEP SSA coopetition model Institution 1 University of Zimbabwe 2 University of Johannesburg 3 University of Cape Town 4 National University of Science and Technology 5 Universidade Eduardo Mondlane 6 Namibia University of Science and Technology 7 Harare Institute of Technology 8 Chinhoyi University of Technology 9 Zimbabwe National Defence University

Country Zimbabwe

DTC speciality Water resources engineering and management South Africa Intelligent systems and 4IR South Africa Mining and mineral processing Zimbabwe Manufacturing systems Mozambique Food science and technology Namibia Renewable energy technologies Zimbabwe Technopreneurship and machine design Zimbabwe Mechatronics & industrial instrumentation Zimbabwe Aeronautical engineering and avionics

Implementation date 2021 2021 2021 2022 2022 2022 2023 2023 2023

thus enriching their skills and enhancing their confidence in teaching as well as creating opportunities for industry-based projects (IBP) and problem-based learning (PBL). Since the launch of the HEP SSA initiative, 11 engineering academics from all the HEP SSA partner institutions, as previously discussed and shown in Table 4.5 in Chap. 4, were seconded to various industry partners where they were actively involved in industrial practice, following which they presented reports and subsequently prepared conference papers which were accepted for the second African Industrial Engineering and Operations Management Conference. In addition to developing their work during secondment into acceptable conference papers, each seconded academic generated at least three projects for students, hence turning student projects into practical and industry based ones. Over and above the original EEEP objectives, additional thrusts and objectives were incorporated to stimulate, regionalise, internationalise and strengthen engineering research in Southern Africa through supporting regional journals and conferences for Engineering, Science and Technology to disseminate and share research findings and knowledge. Through the HEP SSA coopetition model, the University of Zimbabwe has established a regional Journal for Science and Engineering for Sustainable Development (JSESD), which will be utilised by academics from all the partner institutions, either through collaborative and regional research (inter-­ institutional) or intra-institutional research. This was made possible by pooling resources in start-up activities such as availing specialised expertise from the partnership for the purposes of reviewing papers. In order to further strengthen relations between industry and academia, the HEP SSA coopetition model also aimed at promoting entrepreneurship, industrialisation

202

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

and innovation among engineering students and staff by supporting regional integration, entrepreneurship and innovation competitions to feed into the Royal Academy of Engineering Africa Prize for Engineering Innovation and any such pitching for business ventures and spin-off companies. This aspect is handled in more detail in Chaps. 10 and 11. The coopetition model took over the traditional intra-institution and inter-institution student project competitions for Zimbabwe and introduced the inter-institution competitions for the region where national winners for each country would compete to produce a regional winner. However, the support for the Royal Academy of Engineering’s Africa Prize for Engineering Innovation remained the preserve for all the national winners. Such competitions have been held virtually following the COVID-19 travel restrictions, where the online presentations were just as good as the physical ones. The combination of competitions at different levels, such as intra-institution followed by inter-institution (local) and inter-institution (regional), while cooperating in other spheres such as research publications, demonstrated excellent coopetition among institutions.

9.4  HEP SSA Coopetition Model Outcomes and Impact SAE2Net’s aims and objectives dovetailed with Southern Africa’s new thrust for engineering education that included industrialisation and innovation in addition to the traditional university teaching, research and community service. There was an inherent need to produce appropriate engineering skills to handle dynamic changes in technology in the fourth Industrial Revolution (Industry 4.0) but more so prepare the human resources required for the Digital Ecosystem (Industry 5.0). The HEP SSA collaboration has empowered engineering academics and improved linkages between industry and academia, bolstered by the establishment of Innovation Hubs for incubation and product development as well as Industrial Parks for commercialisation at various universities in the region, as detailed in the next two chapters. The HEP SSA coopetition model was premised on the UN Millennium Development Goal #8 (Global Partnerships for Development) and the UN Sustainable Development Goal #17 (Partnerships for Sustainable Development) and sought to address more specifically the Sustainable Development Goals such as SDG #7 (Affordable and Clean Energy) and SDG #9 (Industry, Innovation and Infrastructure). While these were the general outcomes, the HEP SSA collaboration progressed fairly well under the circumstances and the onset of the COVID-19 pandemic. A properly skilled engineering academic was one who was sufficiently trained to a high level (PhD), confident of lecturing, knowledgeable of industrial systems, a researcher able to write and publish conference and journal papers, have the ability to offer consultancy and community services in an innovative and confident way. All these aspects were the reasons why this HEP SSA initiative was executed using the systems thinking methodology for the key objectives in order to develop a ‘whole’ academic. In line with the aim to bridge the gap between industry

9.4  HEP SSA Coopetition Model Outcomes and Impact

203

and academia, the model has realised some achievements in terms of outcome and impact using the following key indicators. While it may be difficult to quantify the quality of graduates produced by the education system and their fitness for subsequent roles in industry or further academic study to the lasting benefit of the country and the Sub-Saharan Africa region as a whole, the improvement to the socioeconomic status of the region should show a definite improvement in the foreseeable future. In order to improve the quality of engineering education, it was essential to improve the quality of the teaching staff and facilities. The concept of doctoral training centres was overwhelmingly accepted by all the SAE2Net partners as a way forward to accomplish this. The first three DTCs were earmarked for establishment in 2021, while the rest will be established in a phased approach. The framework was accepted by authorities of the various HEIs as it will bring a relief and long-term impact for PhD holders teaching at these institutions. Most of the CPD courses were conducted in 2020 and will be rerun due to their popularity and importance. The impact was that practising engineers from industry partners were provided with sufficient skills and modern ways of engineering and manufacture in order to improve capacity utilisation and efficiencies. The CPDs also provided SAE2Net with a platform to generate income in order to sustain activities. The impact of the establishment of DTCs should be substantial in the long run. The increased number of engineering academics on secondment was commended by authorities of the HEIs while welcoming the idea of scaling them up as it not only impacted on the academic, by improving their skills, confidence and knowledge, but also enhanced the profiles of the institutions as well as the provision of skills for optimising industrial processes and efficiencies of operations. The engineering academics who were seconded to industry were carefully selected from the young and inexperienced ones who were still due for tenure. Most engineering academics failed to research, let alone publish their work due to lack of financial capacities by their institutions. At the same time, the institutions were ranked worldwide partially by their competences and amount of scholarly publications that their academic staff produced. The SAE2Net coopetition model enabled the registration of 10 conference papers that were accepted for the 2nd African Industrial Engineering and Operations Management conference through financial support and further support earmarked for these to be extended to journal papers. Ultimately, a ‘whole’ academic was developed, and the impact was that after the regulatory 3 years of probation, these academics will be tenured and become permanent members of the academic staff of their institutions as they are required to demonstrate excellence in teaching and produce scholarly publications before they can be granted permanent appointment (tenure). The impact for scholarly publications was generally felt annually when ranking organisations such as the Times Higher Education considered research output for each institution. The output from intra-institution and inter-institution has been commendable in such a way that the impact will continue to be significant for their institutions as these publications contribute to raising of the bar and rankings of their institutions.

204

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

Over the years, many engineering students have developed some interesting innovations through their undergraduate and postgraduate projects. These have traditionally been showcased through students’ competitions, but many of these ideas sometimes ended up ‘buried’ as there was no capacity to see them through to commercialisation. The SAE2Net coopetition model provided support to some of these outstanding projects for the developers to realise their dreams. More details are covered in the next two chapters. The impact of this support was to ensure that at least some of the innovative projects were developed further and perhaps found potential investors. The outcomes were wholly positive and the impact was qualitatively good, judging by the key indicators.

9.5  Challenges and Opportunities in Virtual Collaborations While coopetition has been successfully employed to bring competing organisations to work together for the benefit of all players, there are several considerations that must be taken into account, including due diligence before parties can commit themselves to the partnership. Some of the considerations include possible challenges that could be handled in such a way that they can turn to opportunities for furthering the businesses of the partners, but there are also numerous advantages. The process of due diligence must be thorough and carried out prior to commitments. This process starts with the fundamental reasons for entering into the coopetition, followed by weighing the benefits against the disadvantages before an agreement was drawn up. Coopetition almost invariably resulted from the complexity of markets for businesses and the operating environment, particularly in view of increased globalisation and the dynamic trends of the fourth Industrial Revolution. In view of the rapid changes in technology, whether the businesses were manufacturing, service provision or higher education and training, globalisation of economies normally led to hyper-competition, thus the need for increased cooperation (Cygler et al. 2018). While there were numerous tertiary institutions that have been developed around the world, there were equally an increased number of students requiring higher education. Zimbabwe alone established more than 10 HEIs during the period 1990–2010 (Zinyemba 2010) and institutions around the region also established more HEIs, especially those that were converted from either polytechnics or technikons. These increases meant that institutions competed for the best students despite the increased numbers of students from high schools. In addition to competing for the best students, institutions also competed for research grants from various sources, including industry. Therefore, the thrust for tertiary institutions has been for sustainability in order to achieve economic and social benefits, thus prompting coopetition for survival and sustainability. HEIs have thus been more willing than ever before to enter into coopetition for the institutions’ survival and sustainable development, faced with stiff global competition for ranking, students and research grants (Del-Soto and Monticelli 2017). SAE2Net was established as a coopetition

9.5  Challenges and Opportunities in Virtual Collaborations

205

model to take advantage and pool complementary resources, both human and equipment, such that no institution spent unnecessary amounts of capital to purchase specialised and expensive equipment for use alone, when probably the bulk of the time the equipment may be underutilised. Challenges encountered in terms of shortages of skills may also be resolved through the specialised Centres of Excellence and exchange of staff within the network. Synergies were thus created among HEIs where the complementary resources made them more valuable and useful for competing on the global arena, hence the reason why such possessions became a prerequisite for institutions to enter into such partnerships. Collaborations that combine competition and cooperation among tertiary institutions stimulated and urged the innovation of players and further development of technology to respond to the growing demands of the fourth Industrial Revolution. SAE2Net was strategically developed by co-opting a UK partner, University of Leicester, to learn and adopt practices from an institution in an industrialised country, thus the transfer of technology, skills and knowledge. Sharing and exchange of knowledge not only helped to avoid ‘reinventing the wheel’ but also helped in penetrating new markets and competing on the global arena. Coopetition also reduced operational costs by minimising the risks associated with solitary operations, thus creating and increasing value for institutions, ultimately generating benefits in terms of technological advancement, research grant sourcing, collaborative research and publications. Obviously, due to the maintenance of identities in coopetitions, there were associated risks in inter-institutional relationships. The biggest risk in coopetition of businesses with similar ventures such as inter-­ institutional partnerships was that it might promote opportunistic behaviour unless partners clearly spelt out intellectual property rights, such as patents developed in the partnership. Where an innovation was developed out of inter-institutional collaboration, ownership of the outcome may pose challenges even if the coopetition agreements spelt out the finer details of such eventualities. Partnerships in HEIs are also associated with low levels of trust, thus rendering the coopetition a temporal relationship. Sometimes successful coopetitions collapse because some partners may opt out, either if they see that their contributions were more than the others or when a partner has realised their benefits from the cooperation but feel they don’t need the partnership anymore. Coopetitions involving many partners are prone to risks such as uncontrolled leakage of information, even though this may be covered by the coopetition agreements, which may ultimately lead to one or more partners losing their grip or dividends, either from royalties or intellectual property rights. The benefits derived from coopetition by HEIs, say in research results, innovations, royalties or associated dues, may be difficult to apportion in accordance with the contributions made by partners at the inception of the partnership and may lead to unstable relationships among the institutions. Conflict among coopetition members may actually reduce the effectiveness of the partnership and the benefits thereof. Decision-making can be heavily compromised in a coopetition unless clearly spelt out in the partnership agreements, but such agreements also limited partners from associating with or partnering other potential parties outside the coopetition. There was no doubt that in

206

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

any coopetition, members strived to outdo the others, and this can cause unnecessary instabilities in the partnership, creating the possibility of changing the coopetition into a zero-sum game, resulting in further conflicts and possible aggression among parties, with consequences of losing the competitive advantage. However, if managed well and agreements entered into, diligently, the benefits of coopetition outweighed the losses or dangers of the resulting conflicts.

9.6  Conclusion Although coopetition has been widely used in recent years to boost the fortunes and benefits of competing companies that decide to cooperate, the same concept can be extended to higher education institutions that are mandated to develop human resources. While the same principles can be applied in the training of engineers, it is important to take cognisance of the varying regional and national education policies in order to develop a holistic approach to satisfy all players. The implementation of coopetition strategies in higher education is based on the need to collaborate in research and teaching and pool complementary resources such as specialised skills and equipment, while the same institutions may be required to compete for the best students to be enrolled at their institutions and for the global university rankings and research grants from industry. The latter may be inter-institutional and regional, while intra-institutional coopetition can be within the same institution. The adoption of coopetition has expanded to many sectors due to globalisation where the higher education and training sectors were no exception. While parties to a coopetition entered and maintained their identities, there were bound to be conflicts emanating from the complexities of the partnership agreements. However, if due diligence was taken and the coopetition agreements drawn up well, the benefits of such partnerships among tertiary institutions far outweighed the risks and conflicts that may arise. Following the successful implementation of initiatives to improve the quality of engineering education in Sub-Saharan Africa, such as NUSESA and EEEP, which were funded by foreign development aid partners, there was a lot of scope to scale up and expand the activities to involve industry more. This was accomplished through the revamped HEP SSA initiative, with additional focus on promoting innovations, entrepreneurships and commercialisation through increased partnerships with industry. This was after the realisation that a systems thinking methodology was the most suitable avenue to address the shortfalls of NUSESA and EEEP which could not be sustained beyond the funding period, hence the need to include all stakeholders such as governments for facilitation, industry for provision of financial support, professional and regulatory bodies for the standardisation of engineering curricula and the mobility of engineers within the region. HEP SSA was also formulated on the need for virtual and online collaborations due to the COVID-19 pandemic. The major deliverable for the HEP SSA scheme was the establishment of SAE2Net, a virtual coopetition network of eight engineering institutions in Southern

References

207

Africa, leveraging on UK expertise from the University of Leicester and anchored by complementors in the form of industry, policymakers and professional bodies. The coopetition objectives of SAE2Net were achieved through the maintenance of a robust and demand-driven network through centres of excellence, secondment to industry, knowledge sharing and promotion of innovations.

References Arnold, R.  D., & Wade, J.  P. (2015). A definition of systems thinking: A systems approach. Procedia Computer Science, 44(2015), 669–678. Bakrania, S., & Lucas, B. (2009). The impact of the financial crisis on conflict and state fragility in Sub-Saharan Africa. GSDRC Applied Knowledge Series. Available: http://www.gsdrc.org/go/ emerging-­issues#crisis. Accessed 24 Mar 2016. Brandenburger, A.  M., & Nalebuff, B.  J. (1996). Co-opetition. New  York: Crown Publishing Group. ISBN: 978-0385479509. Cygler, J., & Sroka, W. (2016). The boundaries of coopetition: A case study of polish companies operating in the high-tech sector. In J. Ateljevic & J. Trivic (Eds.), Economic development and entrepreneurship in transition economies: Issues, obstacles and perspectives (pp. 253–269). Cham: Springer. Cygler, J., Sroka, W., Solesvik, M., & Debkowska, K. (2018). Benefits and drawbacks of coopetition: The roles of scope and durability in coopetitive relationships. Sustainability, 2018(10), 2688. Del-Soto, F., & Monticelli, J. M. (2017). Coopetition strategies in the brazilian higher education. Revista de Administração de Empresas, 57(1), 65–78. Esayas, S. (2017). Competition in dissimilarity: Lessons in privacy from the Facebook/WhatsApp Merger. CPI Antitrust Chronicle, 1, 57–64. Government of Zimbabwe. (2018). National Critical Skills Audit report. Harare: Government of Zimbabwe Printers. 2018. Available: https://safrap.files.wordpress.com/2018/12/2018-­ zimbabwe-­nationalcritical-­skills-­audit-­report.pdf. Accessed 22 Oct 2019. Lim, M. A. (2018). The building of weak expertise: The work of global university rankers. High Educ, 75, 415–430. Nyemba, W. R., Carter, K. F., Mbohwa, C., & Chinguwa, S. (2019). A systems thinking approach to collaborations for capacity building and sustainability in engineering education. Procedia Manufacturing, 33(2019), 732–739. Nyemba, W.  R., Chikuku, T., Chiroodza, J.  R., Dube, B., Carter, K.  F., Ityokhumbul, M.  T., & Magombo, L. (2020). Industrial design thinking and innovations propelled by the Royal Academy of Engineering in Sub-Saharan Africa for capacity building. Procedia CIRP, 91(2020), 770–775. Ray, S., & Srivastava, S. (2020). Virtualization of science education: A lesson from the COVID-19 pandemic. Journal of Proteins and Proteomics, 11, 77–80. Raza-Ullah, T., Bengtsson, M., & Kock, S. (2014). The coopetition paradox and tension in coopetition at multiple levels. Industrial Marketing Management, 43(2014), 189–198. Ritala, P., Golnam, A., & Wegmann, A. (2014). Coopetition-based business models: The case of Amazon.com. Industrial Marketing Management, 43(2014), 236–249. Teferra, D. (2013). Funding higher education in Africa: State, trends and perspectives. Journal of Higher Education in Africa, 11(1–2), 19–51. Times Higher Education. (2010). World university rankings subject tables: Robust, transparent and sophisticated. Available: https://www.timeshighereducation.com/world-­university-­ rankings/2010-­11/world-­ranking/analysis/methodology. Accessed 27 Nov 2020.

208

9  Coopetition and Virtual Collaborations: Global Competitiveness in Research…

World Bank. (2020). COVID-19 Crisis: Through a migration lens. In Migration and development brief 32. Washington DC: World Bank Group. Zhang, Q., Kang, N., & Barnes, R. (2016). A systematic literature review of funding for higher education institutions in developed countries. Frontiers of Education in China, 11(4), 519–542. Zinyemba, R. (Ed.). (2010). Academia and the dynamics of transformative leadership: The experience of the University of Zimbabwe in the first decade after Zimbabwe’s Independence (1981-1992). Harare: University of Zimbabwe Publications.

Chapter 10

Incubation and Technology Parks: Recent Trends, Research and Approaches

Abstract  The direct and dynamic relationship linking academia with industry has been the ability by academia to provide practical solutions and innovations to solve industry’s challenges. In recent years and in response to the rapid changes in technology, higher education institutions have invested in innovation hubs for incubating novel ideas as well as technology and industrial parks for developing the same ideas to commercialisation. This chapter focusses on business incubation principles and the establishment of innovation hubs, science and technology parks by institutions under the Southern Africa Engineering Education Network (SAE2Net), how these have prospered and how the technology parks improved technology transfer. Although SAE2Net members are situated in the same region, this chapter also analyses how the different country environments affected the development of such parks. Success variable factors for product development and sustainability of the parks as well as constraints and challenges were analysed to enhance bridging of the gap between academia and industry through science and technology innovations. Keywords  Customisation · Flexibility · Incubation · Industrial and technology parks · Innovation hub · Innovators · Invention · Product development · Success variable factors · Technology and knowledge transfer

10.1  Introduction As detailed in Chap. 9, the Southern Africa Engineering Education Network (SAE2Net) is an association of nine tertiary institutions that was established to forge a strong, demand driven and sustainable network of universities, research institutions and industry in Southern Africa, leveraging on expertise from the United Kingdom through the UK partner, University of Leicester. The various institutions © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_10

209

210

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

that make up the network have excelled in different areas of engineering education to be accorded Centres of Excellence (CoE) in their own right. Such centres are involved in various activities ranging from conceptualisation of ideas, product and services development, innovation, incubation and to some extent, production of goods and services for a wide range of clientele including the provision of innovative solutions to industry. Apart from detailing business incubation and product development strategies that were employed in tertiary institutions through their science and technology parks, this chapter also focusses on some of those CoE that have excelled within the SAE2Net partnership. Science and technology parks are specialised centres managed by professionals with the main focus to increase the wealth of investors or communities by engaging in the development of innovative ideas and incubating such ideas by promoting the use and transfer of knowledge and technology based at or in collaboration with research and development or Higher Education Institutions (HEIs). There has been a resurgence of science and technology parks throughout the world, particularly in recent years and mostly orchestrated and driven by tertiary institutions in response to the need to be practically relevant and thus working very closely with industry in nurturing innovative ideas and transfer of knowledge and technology (Steruska et al. 2019). Science and technology parks were best located at HEIs or research institutions due to the availability of professional and specialised expertise that forged a culture of research, collaboration, innovation and knowledge transfer. Science and technology parks, often referred to as Centres of Excellence (CoE), are normally established to stimulate and promote the relationship and the transfer of knowledge and technology between academia and industry. Based on the information and data gathered from the various centres established within the SAE2Net consortium of institutions and industry in Southern Africa, this chapter provides some insights into the feasibility of establishing science and technology parks by tertiary institutions, the success factors, constraints and challenges and how the institutions can draw lessons from these experiences in order to improve the performance of the centres. The focus for evaluating such centres would be to encourage tertiary institutions to promote the culture of innovation, incubation, product development and commercialisation through the development of bankable ideas and the provision of advanced and innovative solutions to industry’s challenges, thereby bridging the gap between industry and academia. Centres of excellence, in the form of science and technology parks, particularly operating and providing services within a region, facilitated and enhanced regional integration and development through support for business enterprises and clusters (Al-Kfairy et al. 2020). The successful operation of such business clusters forms the much needed foundation for industrialisation in order for both academia and industry to remain afloat in this competitive global economy and the fourth Industrial Revolution. The industrialised world across the globe have invested varying but significant proportions of their national budgets for research and development, innovation and commercialisation, and the industrialising world, such as Southern Africa, required these centres even more, hence the need to set the tone and platform through which these can be developed, nurtured or improved in the case of existing

10.1 Introduction

211

ones. High failure rates of such centres have been reported across the world by the World Bank (Kelly and Firestone 2016), hence the need to provide guidance for potential institutions wishing to invest in such high technology centres. Based on the established centres in Southern Africa, this chapter also looks at what has made some prosper and what has been hampering those that have failed. The success of innovation hubs or science and technology parks was hinged on their ability to attract the most suitable and promising innovations that were bankable and that industry can choose to invest in. The selection and arrangement of clusters within a technology park also had a bearing on the performance and life span of such centres. Apart from analysing the performance of science and technology parks through financial returns (income generated) or volumes (quantities produced), the way the centres were structured and their modus operandi also played a key role in determining their success or failure (Al-Kfairy et al. 2020). Failure in some instances has been due to heavy-handed and bloated structures whose bureaucracies simply hampered operations. In deciding where to establish a CoE where a science and technology park can operate successfully, a number of considerations have to be taken into account. In the case of the SAE2Net consortium, this had to be mostly the concentration and availability of certain expertise in order to drive the centres. As such, it was not just a question of geographically distributing these but rather focus on available capacity and this may result in a concentration of such centres in the same locality. Consequent to the industrial transformations as detailed in Chap. 2, there was a general belief among decision makers (governments) and researchers that innovation and innovative solutions for industry invariably resulted in wealth creation at different levels of administration, whether nationally or regionally (Phan et  al. 2005). In the same vein, a concerted effort in investing in innovation, research and development facilitated industrialised countries to compete globally and made use of the generally affordable labour in industrialising countries, thus creating more opportunities for employment, regardless of the locations of the science and technology parks. This was probably one of the reasons why industrialised countries found sense in investing in the development of such parks in developing economies. However, strategically locating the incubation centres not only helped in business acceleration but knowledge and technology transfer as well as resource sharing. Most of the science and technology parks established around the world have been supported by industry who have invested in HEIs to manage such centres as start-up incubators based on their knowledge and technologies. Numerous science and technology parks have flourished at many reputable HEIs in the industrialised world, such as the University of Warwick Manufacturing Group’s Tata Research Centre, Jaguar Research Centre, Energy Innovation Centre, with government investment of £4.25  million support (University of Warwick 2017), Centre for Transportation and Logistics at MIT, Silicon Valley, both in the United States and Engineering Design Centre at the University of Cambridge (Clarkson 2005), to name just a few. However, the distribution of these around the world has been somewhat skewed, with over 1000 in the United States alone and 850 in the European Union as of 2005 (Phan et al. 2005). However, these numbers were still very low in industrialising countries such as those in Southern Africa.

212

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

The proliferation of such centres in the industrialised world and a few that started mushrooming in Southern Africa has propelled academia to explore ways to enhance their performance, particularly in relation to the synergies and links with industry in the different parts of the world. This has also pushed academia, governments and industry to invest more in such ventures, hence the thrust for this book on engineering change management using systems thinking where all stakeholders were involved in order to bring industry closer to academia. The formulation of the positive sum game and strategies for successfully establishing and managing such centres is therefore critical, particularly in view of the fact that these are driven mostly by governments and academia, traditionally oriented toward non-profit-making, thus the importance of collaboration with business and profit-making industries. This was probably why the majority of science and technology parks were a result of public–private partnerships, with input and interest from a wide range of stakeholders. While a lot of research and data have been gathered from the successful centres established around the world, little or no information was available from the few established in Southern Africa, hence the importance of analysing the few and draw synergies with those from other parts of the world but in particular paying attention to the different economic environments.

10.2  Business Incubation Principles In general, business incubation is a process where an organisation (business incubator) invests and supports the development and start-up of a business enterprise following the successful testing of a prototype or an innovation (Vanderstraeten et al. 2016). Viability and feasibility of the venture would have been analysed through financial appraisals and growth potential to weigh the opportunities before committing or channelling funds into the incubation process. The overall objective of any business incubation process is to increase the success possibilities of a business venture derived from an appropriate analysis of the pros and cons of the proposed business which is dependent on a number of success variables. In the case of science and technology parks that were developed to operate in conjunction with tertiary institution, the responsibility for drawing up the proposals to develop the ventures rested with the institutions. This should be done in a convincing enough model that attracted investors (industry) to support it. There are variable parameters associated with business incubation ranging from economic development tools that assist in creating businesses in communities to technology and knowledge transfer hubs linking academia (knowledge and technology base) to industry (finance and production). The investors who are usually industry-based support emerging business start-­ ups with services such as strategising, developing business and marketing plans, provision of professional expertise in the form of engineers and management teams, as well as access to modern equipment and other technologies for production.

10.2  Business Incubation Principles

213

The rise in the number of business incubators around the world and particularly in the industrialised world has been due to a number of factors including increased innovations and the desire to pursue entrepreneurships, rapid changes and emergence of new technologies, globalisation of world economies, downsizing of some industries to focus on core business in order to remain operational, and the increased demand for transfer of knowledge and technology. In tandem with the industrial revolutions, business incubation in general and specifically for science and technology, there has been a boom and evolution over the years into various units separated by different portfolios and focus to become integral parts of the modern entrepreneurial ecosystem. Business incubators supported the creation and growth of wealth through a broad range of activities (Hausberg and Korreck 2020). Such proliferations resulted in the emergency of a multitude of entrepreneurships and spin-off companies and in some instances with the potential of creating confusion within the innovation and incubation development industry. Scenarios such as this also created fragmentations in academia and industry collaborations. Although there were many studies and research carried out in business incubation, these have mostly been industry based with little or no ties to academia. However, this has gradually been transformed as industry felt the management and technology applications, and transfer within such setups was the preserve and better placed in academia (Hausberg and Korreck 2020). These studies have provided a platform and insights into the efficient and effective operations of science and technology parks. It was common knowledge that HEIs and research institutions were the major developers of technology to drive industry by way of incubation and experimentation or prototyping before releasing the idea or innovation to industry for full-scale production. Despite the fact that many business incubators, especially science and technology parks, were established with the main objective of transferring technology and knowledge, that has not been so, especially in industrialising countries. Research on business incubators, science and technology parks can be split into various segments focussing on what typical industrial companies can be accommodated in an innovation hub or technology park, those that can manage and run the innovation hubs and the level of collaboration such as HEI, country or region, as well as focussing on evaluation of the potential of the innovation, whether or not it can be pursued further to patenting and commercialisation (Phan et al. 2005). This chapter methodically considers these four areas in line with the various centres that have been developed within the SAE2Net collaboration by looking at the success variables and constraints that hindered the technology transfer stream. Previous research has not quite succeeded in connecting these four focus areas, an aspect that will be handled in this book using the systems thinking methodology. The choice for this approach was based on the fact that science and technology parks were dynamic as much as the different technologies being developed within them, hence the vital importance to link up all the major stakeholders such as academia, industry, policy-­ makers, professional bodies and research institutions.

214

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

10.2.1  Business Incubators and Accelerators While it may be straightforward to come up with an innovative idea that could easily find a market, translating the same idea to business or commercialisation may not be as straightforward. Innovators and entrepreneurs, especially the ‘green’ ones such as academics or students, need mentoring and access to capital in order to build businesses around their innovations. Apart from failure to package proposals to attract funding, this was probably the major reason why good projects, start-ups and innovations never saw the light of day or worse still, after starting, some of the ventures simply folded up in a short period of time. Such challenges may be resolved by business accelerators, typically industry or other organisations that offered support services such as funding to develop start-ups. Their modus operandi usually included programmes for mentorship as well as working space and resources to innovators to develop their ideas without fear of crumbling due to lack of these. In addition, after the conceptual process, business accelerators also offered access to capital and investment in return for equity in the business. Such start-ups were eventually weaned off from the business accelerator after a specified and agreed period of time. From the foregone, it would appear like business incubators and business accelerators serve the same purpose. However, there are some subtle differences between the two. A business incubator usually helped to develop a venture or start-up by the provision of a shared operating space, networking opportunities, mentoring resources and access to shared equipment and technology. Due to the proliferation of incubators, run by not-for-profit organisations like tertiary institutions, they generally do not demand equity in a company or access to funding or resources in the same manner that accelerators do. As such, start-up ventures generally received much less access to capital investment in a business incubator than they would from an accelerator. That requirement as well as the specified time for business acceleration made business incubation more attractive than business acceleration at growing the business (Hausberg and Korreck 2020). This was because, in general, start-ups took years to develop instead of the fixed number of months that may be allocated to the accelerator programme. Thus, the business accelerator programme would be more suitable for those innovators who will be very sure of their innovation and simply require support to kick-start, instead of developing and growing it within the business incubation period. However, different start-ups require different support and different levels of investment in order for them to succeed. Ultimately, some innovators and investors use the terms incubator and accelerator interchangeably. However, accelerators tend to provide the best of both worlds for both innovators and investors, although they required more in terms investment for start-up owners. Rubbing shoulders with experts while sharing space and developing innovations, start-up owners also benefitted from cohabiting and mingling with peers from where competitions can be generated to boost development.

10.2  Business Incubation Principles

215

10.2.2  Classification of Business Incubators Due to global competition, some industry players have established research and development units that were devoted to improving their existing operations as well as scouting for innovations and opportunities to grow their businesses. These probably form the largest pool of business incubators as they have the potential to use their ‘excess’ profits to focus on possible start-ups. The high concentration of these incubators was in modern technology and other high technology areas with ICT as their main tools (Hausberg and Korreck 2020). Their main emphasis was to facilitate and support innovators to enable them to fast track start-ups lead time in order to capture the market share before others ventured into the same business. This was usually easier to implement for small-to-medium enterprises as bureaucracy and organisational inertia usually got in the way for larger organisations. Sometimes, such conflicts led to investors within large organisations to creating their own corporate incubators with which they used to partner with innovators to drive some start-up businesses. Dedicated units such as corporate incubators even assisted their own staff through employee ownership schemes that actually developed the innovations and start-ups to separate business units or spin-off companies. As such, corporate incubators were also an avenue for open innovation which can be considered as outside-in or inside-out (Weiblen and Chesbrough 2015). However, in general, all organisations were potential incubators through the influence they put on employees through different schemes that encouraged them not to leave the organisations, such as allowing them to take ownership of any spin-offs that may arise from their own initiatives. In contrast to business incubators, accelerators normally provide shorter and fixed term programmes for mentoring and training of a cohort of innovators or start-­ ups, connecting them with professionals and experienced venture capitalists and other investors for proposal development and packaging to enable them to pitch their ideas to other investors. Through the Africa Prize for Engineering Innovation, the Royal Academy of Engineering has been playing this role to boost the skills and innovations by young engineers in Africa (RAEng 2017). Unlike industry-supported business incubators that were streamlined for wealth creation and profit, publicly sponsored incubators were more focussed on employment creation and sustainability of the start-ups. In broad terms, business incubators supported the foundation and growth of start-ups in line with their strategic goals, while in specific terms, the support was extended to new businesses with tangible resources such as modern equipment, space and intangible outputs such as knowledge and access to networks. As such, the two clear categories of business incubation were those sponsored by industry (private) and those sponsored by government or related institutions (public). Within those two categories, business incubators can be further characterised by management and exit policy, tenancy and resulting revenue or other characteristics that distinguished their specific operations.

216

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

10.2.3  Academia Business Incubation Process and Selection Selection of appropriate innovators to support start-ups and the capacity to monitor and mentor them as well as the availability of resources were the key elements for business incubation and acceleration. These can be extended in some instances to mediation, infrastructure and graduation and exit policies as additional elements (Hausberg and Korreck 2020). The quality of proposals and how they were packaged provided the initial step toward the success of a start-up. For the specific example of the Royal Academy of Engineering’s Africa Prize for Engineering Innovation, shortlisted candidates from across Africa were taken through a mentoring and training programme to expose and groom them to the requirements of the competition, way before the competition such that when they eventually met for the final selection, all the innovators will be at the same grounding and understanding of the requirements. The objective of the Africa Prize for Engineering Innovation was to stimulate, celebrate and reward innovation and entrepreneurship in Sub-Saharan Africa by recognising innovations that were appropriate in the provision of solutions for the region’s challenges, such as provision of clean water, smart farming, responding to disasters such as Cyclone Idai and the COVID-19 pandemic, upon which the selection criteria was based. Other criteria such as potential for growth, revenue generation, impact and number of people to benefit from the innovation were usually incorporated to refine the selection process. Common areas in the business incubation process included patenting and intellectual property rights for the very outstanding innovations, sales projections, drawing up of contracts, packaging and presentation of the proposals, marketing and advertising. The investor tended to maximise between service provision and the specific requirements of the start-up and continually monitored innovators to guide them in order to avoid making mistakes because the success of the innovator translated to the success of the incubator. Likewise, the innovators also needed to be familiar with their proposal in terms of knowledge and resources in order to recognise the potential of their innovation and support from the incubator. The desire to make use of resources and the support from incubators increased throughout the lifecycle of a venture even when they graduated and exited or weaned off and became independent. Business incubators do not always have all the resources required by an innovator or entrepreneur, even if their innovation may well be within their business scope. In cases like this, incubators played a mediation role where they can link the innovator with appropriate and specialised expertise or businesses through networking. Ultimately, the incubator has to content with and manage their own internal affairs as well as external linkages with either competitors or collaborators. The Royal Academy of Engineering has maintained networking and cooperation activities between winners and runners up of the Africa Prize for Engineering Innovation through annual interactions, knowledge-sharing workshops and other platforms that helped innovators to continually develop their ideas.

10.2  Business Incubation Principles

217

10.2.4  Incubation Performance and Impacts As much as it was important for business incubators to vet, select and monitor innovators and entrepreneurs under their stable, it was equally important for outsiders including the innovators to be accorded a chance to evaluate the performance and impact of business incubators. Given choices, especially with the rising number of business incubators and accelerators, entrepreneurs may also have a choice of which stable to work with in order to prosper their innovation. There were various ways in which this has been carried out in recent developments, such as determining the impact of incubators at various innovators, previously supported innovations and how successful they were, amount of capital invested cumulatively, number of failed ventures under their stable, number of graduates periodically and a host of other peripheral measures that helped to inform the entrepreneurs. Thus, the business incubator performance was general to the extent to which incubator outputs or outcomes matched with incubator goals. Collaborative networks also played a very important role in evaluating the effectiveness and impact of business incubators. Lasrado et  al. (2016) evaluated whether entrepreneurs graduating from tertiary institution-linked incubators attained high levels of performance after incubation, from which they concluded that incubated firms benefited immensely from their link with university incubators. The results also showed that after graduating from these business incubators, entrepreneurs created a lot of employment as well as boosting their sales, compared to the non-university incubated firms. Business incubator performance differed according to the type of incubator extracted from, university incubators, industry (private) incubator, research incubator or regional incubator. Researchers have categorised the performance measures to include research and development programmes, active participation, inputs and outputs, as well as employment creation and growth of the venture (Hausberg and Korreck 2020). Generally, using the performance measures, private and research incubators performed way above the others. The other conclusion was that incubators on their own cannot affect business survival but instead required a combination of other influential factors such as larger companies, or relocating to other sectors with higher rates of survival, where they can be an effective economic development tool. Performance measures can also be classified using multi-dimensional frameworks, broadly categorised as performance outcomes, management policies and service provision and value added (Hausberg and Korreck 2020), which can be further classified into other peripheral measures such as sharing and pooling of resources, consultancy services, networking, location, costing, source of funds and the public image of the incubator. These factors were entirely dependent on the type of incubator and possibly its geographic location. These performance measures within the main categories as well as the sub-categories were used to assess the various centres of excellence within the SAE2Net partnership in order to assess their effectiveness and recommendations for boosted performance.

218

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

10.3  Innovation Hubs and Industrial Technology Parks In response to the demands of the fourth Industrial Revolution and global competition, as well as to keep in tandem with developments around the world, many tertiary institutions in Sub-Saharan Africa have adopted many strategies to remain afloat. The competitions for research grants and even for students had stiffened over the last 20–30 years where countries in the region experienced steady growth in the number of universities established, either from scratch or from converting polytechnics and technikons to universities. Coupled with global competition that saw industry scaling down to focus on core business, that meant that grants for research from industry also dwindled and the many universities that were created had to compete for the much smaller ‘cake’ than was traditionally available. This pushed some institutions to go further and develop innovation hubs for incubating ideas from academics and students as well science and industrial parks for commercialising the innovations, either in competition or in collaboration with selected industry partners. The recent thrust by the Government of Zimbabwe through the Ministry of Higher and Tertiary Education, Innovation, Science and Technology Development for their 2018 focus for Education 5.0 to include innovation and industrialisation as additional pillars to the traditional teaching, research and community service was a typical example of some of the changes that were being effected to tertiary institutions in Southern Africa. Similar trends were observed in other regional institutions where the focus was to produce goods and services as opposed to the traditional training which resulted in employees as opposed to both employees and employers (entrepreneurs). This thrust has seen the recent proliferation of innovations hubs (university incubators), science and industrial parks throughout the region, with the major objectives for growing wealth, producing goods and services and creating links between academia and industry. The following sections analyse the different innovation hubs, centres of excellence or science and industrial parks, with a view of using them as a bridge between academia and industry. Not all the available centres of excellence, innovation hubs, science and technology parks managed by institutions within SAE2Net were analysed but a selected few from each of the four countries within this network, that is, Mozambique, Namibia, South Africa and Zimbabwe. For each institution, a number of parameters were considered, such as purpose of innovation hub or centre, expertise available, activities involved, patents and intellectual property rights registered, income generated, links with industry and government and what support has been availed for these centres. This was coupled with current performance, success variables, constraints and challenges, with a view to expand the scope and grow wealth. The information was derived from visits to the sites, observations and interviews with academics on site.

10.3  Innovation Hubs and Industrial Technology Parks

219

10.3.1  I nnovation Hub and Agro-Industrial Park: University of Zimbabwe In 2019, the Government of Zimbabwe committed a significant amount of money to construct innovation hubs at tertiary institutions offering science and engineering education as well as science and industrial parks at selected institutions in the country. This was out of a realisation that in order to develop, the country must invest in skills development through innovation and industrialisation and through the provision of facilities that helped to improve science and engineering skills required for the country’s re-industrialisation in line with the thrust for Education 5.0. This move was also meant to address the skills gap, mismatch and shortages of skills in science and engineering in order to drive industry in the fourth Industrial Revolution. Several innovative projects have been incubated within the innovation hub at the institution. The commissioning of the Agro-Industrial Park in 2020 following the successful incubation of some of the ventures within the innovation hub, marked the beginning of the processing of agricultural produce for consumption as well as extraction of essential medicines from some plants. The engineering innovations included systems to harvest essential oils from plants for pharmaceutical purposes, predicting congenital heart diseases using machine learning, decentralised water access, primer solar pumped water design solutions to aid the COVID-19 fight and various others. Another noteworthy innovation was the development of the university’s groundwater project in 2013, described in detail in Chap. 13, hence the designation of the institution as a centre of excellence for water resources management under the SAE2Net partnership. This was a typical production enterprise that saved the university over USD 1 million in professional fees by making use of various skills that academia possessed, with the potential of converting such skills and outcomes to spin-off activities.

10.3.2  Centre for Minerals Research: University of Cape Town The Centre for Minerals Research (CMR) at the University of Cape Town is a multi-­ disciplinary, inter-departmental research centre based in the Department of Chemical Engineering. The CMR conducted research with the overall purpose of developing models, methodologies and heuristics for the design, simulation and optimisation of mineral-processing concentrators. In addition, the CMR placed priority on the provision of high-level human resources to the South African mining and mineral-­ processing industry through rigorous postgraduate research training, hence its designation as a Doctoral Training Centre (DTC) under SAE2Net. The main focus of research was on the processes of comminution, classification and froth flotation, arguably the most important unit operations in mineral beneficiation. In excess of 2,000 million tons of more than 100 different mineral species were recovered annually through the process of flotation.

220

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

Inefficiencies in mineral processing throughout the region have been due to a number of factors including shortages of skills, which sometimes forced mining companies to export partially processed ore and in the process translating into loss of revenue and unnecessary waste of the world’s valuable and steadily declining mineral reserves. Research at CMR was conducted using industrial, laboratory and computational methods, to develop robust models and heuristics for describing the performance of mineral-processing concentrators. The CMR research enjoyed extensive support from statutory funding agencies as well as a wide spectrum of leading mining and mineral-processing companies, both locally and globally. There was also close collaboration with other research groups at universities and research organisations nationally and internationally. The level of skills at the CMR was quite high and well resourced, with several PhD holders. Mining and mineral processing at the University of Cape Town was ranked highly owing to the academic researchers who strive for excellence and collaborate with industry.

10.3.3  I nstitute for Intelligent Systems: University of Johannesburg The University of Johannesburg was established as an amalgamation of two universities and two technikons in 2005, with one of its strategic objectives to provide a leadership role in Africa to encourage and drive towards the implementation of the fourth Industrial Revolution, despite the different levels of attainment of this revolution in different parts of Africa, hence their institution motto, ‘The Future. Re-imagined’. The institution has several centres of excellence in the various faculties and disciplines within the institution. Of particular focus and hence the selection as a Doctoral Training Centre under the SAE2Net partnership was the Institute for Intelligent Systems (IIS) which was established in 2016 to act as a catalyst and in fulfilment of the University of Johannesburg strategy for global excellence. IIS was thus the institution’s flagship in the provision of solutions and cementing the links with industry and drove the vision for the institution’s realisation and achievements for Industry 4.0. The institute operated through and was based on three main pillars: multi-­ disciplinary development of academics to higher degrees and CPDs for professional and practising engineers, strategic partnerships and research for development in collaboration with industry and other institutions as well as enterprise development and incubation of innovative ideas. The capacity-building initiatives under IIS were accomplished through artificial intelligence, data science and analytics, machine learning, Internet of Things and other modern technological methodologies. The institute was well resourced and supported by the university as well as through government grants from the Department of Science and Technology (DST) as well as the National Research Foundation (NRF). IIS’s active research was focussed on cyber physical systems, optimisation, predictive maintenance, controls, telecommunications, etc. Together with the dedicated

10.3  Innovation Hubs and Industrial Technology Parks

221

Technology Transfer Office, the institute supported start-ups and incubation for innovative projects.

10.3.4  T  echnopreneurship Development Centre: Harare Institute of Technology The Harare Institute of Technology (HIT) was established in 2005 as a university following its upgrade from a technical college. They carried on with the thrust for technological development and working very closely with industry in the provision of solutions particularly to the chemical and processing industries. To enhance their operations, the Government of Zimbabwe also established an innovation hub at the institution to bolster the activities of the Technopreneurship Development Centre (TDC) which was central to the realisation of the mandate of HIT as a technopreneurial university. Their thrust for excellence in this regard earned them the centre of excellence for technology transfer between industry and academia, with a culture of innovation and wealth creation through technopreneurship education, an emerging trend that was critical for the development of African economies. Under the SAE2Net collaboration, HIT was earmarked for the Doctoral Training Centre in technopreneurial studies and for linking the processing and chemical industry with academia. Innovation and incubation were the key drivers for TDC’s activities as they aimed for economic growth and social development as well as capacity building and the provision of highly skilled engineers and technologists to drive the processing and chemical industries. Technopreneurial studies and research enhanced and empowered engineering academics and practising engineers with design and operations thinking capabilities in order to manage and optimise industrial operations effectively and efficiently for a global and competitive economy. Apart from the innovation hub, the institution has also received support from industry as well as the Indian government through the provision of hi-tech equipment such as CNC machine tools. The institution partnered with many local and international organisations in their pursuit for commercialising research as a spring board for economic development.

10.3.5  F  ood Science and Technology: Universidade Eduardo Mondlane Universidade Eduardo Mondlane (UEM) is the oldest tertiary institution in Mozambique comprising of several faculties and departments, some of which were well resourced in terms of funding and levels of academics. Food Science and Technology (FST) within the Department of Chemical Engineering was one of

222

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

those specialisations that have excelled resulting in receiving support in terms of grants from the Government of Mozambique as well the Swedish International Development Cooperation Agency (Sida) to establish doctoral training, hence the selection of this as a centre of excellence for the DTCs under the SAE2Net partnership. FST prioritised the application of natural resources, local knowledge and low-­ cost materials in the development of new technologies to reduce post-harvest losses, especially at the level of small farmers. FST research and innovations focussed on characterisation of food products, safety and quality control of food products and food technology, post-harvest food management, innovative processing of food products and development of new products as well as food security associated with nutritional aspects and society. All these focus areas were well resourced in terms of skills and by the availability of professors and PhD holders. Students or innovators who were engaged in FST were often expected to carry out multi-disciplinary research involving other specialisations such as Agronomy and Forest Engineering, Veterinary Sciences and other closely related areas dealing with processing or consumption of food products.

10.3.6  R  enewable Energy: Namibia University of Science and Technology Namibia University of Science and Technology (NUST) was transformed from the Polytechnic of Namibia to a full-fledged university in 2015 focussing on areas of technology including various disciplines in engineering. The university in general was very well resourced through funding from the Namibian government and industry. Most of the disciplines revolved around engineering and technology, and some had high levels of skills and highly trained academics including professors and PhD holders. Renewable energy was one such area which was multi-disciplinary, involving academics from Mechanical, Electrical and Environmental Engineering. Owing to the excellence in their execution of research in this area, several well-funded projects have emerged, making the institution a centre of excellence in renewable energy, hence the choice to designate them the DTC specialisation in renewable energy under SAE2Net. The renewable energy projects (incubation facilities) include the Network of Energy Excellence for Development (NEED) and the Centre for Renewable Energy and Energy Efficiency (CREEE). Despite the abundant solar irradiation, Southern Africa still suffered from the ability to secure sustainable energy supplies due to lack of capacity and technical know-how to tap into this resource. NEED and CREEE focussed on skills development and technology transfer in conjunction with industry in order to capitalise on the use of solar energy. Their establishment was to upscale and incubate the numerous solar projects that had been developed at a small scale, apart from boosting the weak links that existed among research and educational institutions, industry as well as government institutions. The Participatory Integrated Assessment of Energy Systems to Promote Energy Access and Efficiency

10.4  Incubation Success Variables and Factors

223

(PARTICIPA) involved three universities, NUST, Stellenbosch and Botswana, funded by the European Development Fund (EDF) and the Development Co-operation Instrument – Relations with South Africa (DCI), involving FAO and NEPAD for developing and implementing innovative and competitive graduate programmes. Biomass Utilisation by Sustainable Harvest (BUSH) was another initiative where NUST was actively involved in research and development for bush-based products, technology transfer as well as applied research on bush control.

10.4  Incubation Success Variables and Factors The success or failure of business incubation was dependent on a number of variables and factors. The focus for this section is on business incubation success variables and factors, particularly for those science and technology parks that were managed or owned by universities as derived from the six such centres of excellence or innovation centres described in the previous section. The information used in this section was based on visits and interactive observations and interviews with personnel within the six operating units within the region. Science and technology parks played a critical role in nurturing innovative ideas from conception to commercialisation, apart from ensuring the global competitiveness of economies around the world (Guadix et al. 2016). However, for such parks managed or owned by tertiary institutions, these can hardly prosper without the requisite input from industry or other players with the capacity to support the incubation financially. Many innovative ideas have been abandoned mid-stream for failure to attract business incubators or investors due to several reasons. The various centres available in Southern Africa as outlined in the previous section were a clear indication of the need for such centres judging by the interest from funding partners such as industry, governments, academia and foreign funding agencies. There was obviously a concentration of these in some parts of the region such as Namibia and South Africa, presumably owing to the well-functioning economies in those countries where they afforded to set aside funds for research and development as well as incubation. Most of them had some connections to tertiary institutions with which industry was involved in technology and knowledge transfer from academia, but by and large they were all involved in research and development of various kinds. More such centres continued to be developed from collaborations between industry and academia. The capital investment in the centres was variable depending on the sources and purposes of funds. For instance, in line with Education 5.0 which focussed on teaching, research, community service, innovation and industrialisation, the Government of Zimbabwe established innovation hubs at five universities for a total of USD 6.5 million and ZWL 6.47 million (USD 80,000). In addition, two industrial parks were established at two of the institutions: University of Zimbabwe Agro-Industrial Park and Chinhoyi University of Technology Artificial Insemination Agro Park, both with an initial capital investment of USD 100,000. These amounts could be

224

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

matched with those invested by other governments in the region, albeit at different scales. The amount of support from industry and foreign aid agencies also varied from country to country and from project to project. However, what was clearly noticeable was the difference between the levels of funding in Southern Africa and that in Europe where billions of US dollars have been invested for incubation and research and development (Guadix et al. 2016). Although the idea of establishing innovation hubs, science and technology parks was a noble one, demonstrated by the commitment and investments from central governments, industry and foreign aid agencies, their effectiveness to deliver expected incubation and development of start-ups remained a thorny issue. Earlier empirical studies failed to identify significant differences between potential companies undergoing incubation and the others as far as innovation outputs, research productivity or innovation processes, although in general, innovation hubs provided a supportive environment for the transfer of technology and knowledge for economic growth (Guadix et al. 2016). Housing potential companies or start-ups under ‘one umbrella’, either in an innovation hub or industrial park, helped to mould synergies and partnerships for the future, typically through coopetitions. Due to the various disciplines in engineering and technology, researchers in incubation and innovation often referred to innovation hubs and industrial parks as heterogeneous in nature, with some prospering and generating value for investors. As alluded to earlier, there were different categories of science and industrial parks, largely classified by selection policies, level of innovation, capacity to transfer knowledge and technology, potential for collaboration, the number of incubators and the level of support, materially and financially. Peripheral information related to these can also be used to establish the effectiveness of innovation hubs and industrial parks, such as space available and how many start-up innovators can be accommodated, type of employment generated either from the hub’s activities or from a successful start-up, mentoring duration and costs, services provided by the hub such as provision of power and network services, investments attracted and available funding for capital expenditure and operating costs. All these variables include the experience and number of years in which companies may be left to operate in an innovation hub, how much money was spent on research and development and how much had been generated in turn, the number of patents and intellectual property rights registered and the overall impact of the hubs on hosted companies. The University of Zimbabwe Agro-Industrial Park has not only attracted several farmers within the council locality who have accessed the facilities available for processing their agricultural produce but also attracted a number of researchers at the Food Science and Technology unit of Universidade Eduardo Mondlane, owing to the competence levels and expertise provided in not only mentoring academics in this field but also providing solutions for the local industry to boost productivity and reduce post-harvest losses. Several centres of excellence for renewable energy have been established and well supported in Namibia to tap into the solar energy resource by scaling up mini-projects to national and regional projects in solving the perennial power shortages. The global rankings for both University of Johannesburg and University of Cape Town have improved

10.5  Customisation of Incubators for Flexibility

225

Table 10.1  Selected Southern African institutions and incubation variables Government support Foreign aid support Industry support Incubation facilities Space Number of incubators (10+) Solutions for local industry Solutions for export Successful start-ups Patents registered Employment generation Mentoring COVID-19 provisions

UZ ✓ x x ✓ ✓ ✓ ✓ x x ✓ ✓ ✓ ✓

UCT ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

UJ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

HIT ✓ x ✓ x ✓ ✓ ✓ x ✓ ✓ ✓ ✓ ✓

UEM ✓ ✓ ✓ ✓ ✓ ✓ ✓ x ✓ ✓ ✓ ✓ ✓

NUST ✓ ✓ ✓ ✓ ✓ ✓ ✓ x ✓ ✓ ✓ ✓ ✓

steadily on the backdrop of the leadership in the fourth Industrial Revolution and the innovative systems for mineral processing and beneficiation respectively. These variable factors were grouped and comparisons made between the institutions in the region as shown in Table 10.1, showing the selected institutions in the region as described earlier. It was quite evident from the binary information provided that all the institutions were supported by their local governments mainly for provision of solutions to local industries. This can be boosted through provision of solutions beyond the countries’ borders by way of inter-institutional and regional collaborations such as the SAE2Net partnership. There were visible gaps where industry support was very minimal or non-existent, an issue that required addressing through promoting industry and academia close relationships through secondments, CPDs and provision of appropriate solutions to optimise industry operations.

10.5  Customisation of Incubators for Flexibility In view of the proliferation of innovation hubs, science and industrial parks around the world, there was an increased need to model and customise these in order to maximise their potential and grow them to generate the much needed wealth and transfer of technology. Obviously, with an increased number of innovators, invariably there has to be an increased number of incubators, resulting in possible competition and cooperation. In order for both the innovators and incubators to succeed, optimisation and customisation became a necessity to drive the objectives for successful incubation. This section explores the different strategies that can be employed to customise and optimise incubation processes and the general impact of this on the survival and performance of both innovators and incubators, based on information derived from the centres of excellence and innovation hubs within the SAE2Net partnership. In Sect. 10.2.4, an outline of incubation performance was provided and

226

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

these can generally be classified into several methods such as institutional performance measurement, level of achievement of objectives, spread of key stakeholders with the capability to catalyse economic development and available resources for innovator and incubator survival and growth. Researchers in innovation and incubation usually used these measures for growth and sustainability of start-ups interchangeably with those which measure revenue, growth in sales, profit generated over a period of time and the number of employment opportunities created. Although it was sensible to relate innovator success to that of the incubator, it was not always the case especially evidenced by the different levels of success of different innovators with start-ups within the same incubation hub and under the same incubator. Careful and strategic planning and implementation of the incubation process provided a foundation for optimal incubator functioning, but with a special focus on running the incubation facility in a business-like approach geared for generating profit (Vanderstraeten et al. 2016). Due to the capital investment, privately owned incubation facilities tended to get more closely involved in the start-ups’ operational activities and decision-making and thus were able to offer customised services as opposed to the publicly owned incubation facilities, which were by and large connecting agencies for the public institutions and industry, who in turn provided the customised support. Customisation of services provided by incubation facilities required resource preparation, which revolved around the institution’s structure and operations such as expertise, personnel, infrastructure or equipment and transaction activities for the provision of external information and data that enabled service customisation. In service provision and customisation, the customer or end-user played a critical role, while the interaction between the innovators and customers increased quality and institutional performance and value creation and addition. Hence, the need to carry out customisation and optimisation was necessary where customer expectations were high. The provision of adaptable solutions increased the start-up’s survival and growth. Breaking up innovations or start-ups into segments and grouping those with common customer needs helped to customise the outcome for growth and wealth creation. Segmentation and customisation were based on better empowering and equipping innovators and incubators to provide accessibility to external and related networks as well as to promote coopetition among innovators and the provision of tailored or customised services. Incubations that blended the support from both industry and national governments strengthened their innovators through the provision of specialised and dedicated services with the capacity to create accessible platforms for coopetition with other innovators and external expertise, which was essential for promoting growth. Incubators that focussed on a particular industry or business normally had the capacity to allocate their resources and investments in a focussed way to attain high levels of customisation. Business incubation was often confronted with flexibility challenges due to the concurrent need for least cost and adaptable services. Such flexibility challenges were resolved through close collaboration of innovators and end-users or by segmenting the roles where users took part in the development and manufacturing processes. Flexibility can also be achieved through customer interactions to attain high customer values.

10.6 Conclusion

227

Fig. 10.1  Incubation systems thinking process

Figure 10.1 shows the incubation systems thinking process relationships between the various stakeholders in the incubation cycle. The reinforcing loop between incubators (investors) and innovators was an indication of the increase in technology transfer also resulting in the increase in knowledge transfer, while the provision of infrastructure and space by national governments was balanced by the provision of taxation by industry, and similarly the provision of appropriate skills by tertiary institutions was balanced by the skills provided for the development of economies.

10.6  Conclusion Innovation hubs and industrial parks provided a direct link between theory (academia) and practice (industry) through the process of incubation of which the overall objective was to increase the survival and growth of business ventures, hinged on a number of success variables and factors. Most incubation facilities were linked with tertiary institutions for the purposes of facilitating knowledge and technology transfer. However, most tertiary institutions, particularly in the case of Southern

228

10  Incubation and Technology Parks: Recent Trends, Research and Approaches

Africa, were funded by their national governments with grants that were usually not sufficient to invest in the operationalisation of such ventures, hence the need to bring in industry to invest as business incubators and accelerators in a customised and flexible manner using a systems thinking strategy. An analysis of the several centres of excellence in Southern Africa, some of which were operating as incubation centres, showed that a lot still needed to be done to bridge the gap between academia and industry and in the process entice industry to invest in such ventures in order to create the ‘Silicon Valleys’ of Africa, a concept which is carried forward into the next chapter for commercialisation and entrepreneurships.

References Al-Kfairy, M., Khaddaj, S., & Mellor, R. B. (2020). Evaluating the effect of organizational architecture in developing science and technology parks under differing innovation environments. Simulation Modelling Practice and Theory, 100(2020), 102036. Clarkson, P. J. (2005). Engineering Design Centre, University of Cambridge. In Design process improvement. https://doi.org/10.1007/978-­1-­84628-­061-­0_22. Guadix, J., Carrillo-Castrillo, J., Onieva, L., & Navascués, J. (2016). Success variables in science and technology parks. Journal of Business Research, 69(2016), 4870–4875. Hausberg, J. P., & Korreck, S. (2020). Business incubators and accelerators: A co-citation analysis-­ based, systematic literature review. Journal of Technology Transfer, 45, 151–176. Kelly, T. J. C., & Firestone, R. S. (2016). How tech hubs are helping to drive economic growth in Africa. World Development Report Background Papers. Washington, DC: World Bank Group. Lasrado, V., Sivo, S., Ford, C., O’Neal, T., & Garibay, I. (2016). Do graduated university incubator firms benefit from their relationship with university incubators? Journal of Technology Transfer, 41(2), 205–219. Phan, P. H., Siegel, D. S., & Wright, M. (2005). Science parks and incubators: Observations, synthesis and future research. Journal of Business Venturing, 20(2005), 165–182. RAEng (Royal Academy of Engineering). (2017). Higher Education Partnerships for Sub Saharan Africa (HEP SSA). London: Royal Academy of Engineering. Available: https://www.raeng. org.uk/RAE/media/Grantapplications-­a nd-­g uidelines/HEP%20SSA/Higher-­E ducation-­ Partnershipin-­sub-­Saharan-­Africa-­(HEP-­SSA)-­Guidance-­Notes.pdf. Accessed 20 Oct 2019. Steruska, J., Simkova, N., & Pitner, T. (2019). Do science and technology parks improve technology transfer? Technology in Society, 59(2019), 101127. University of Warwick. (2017). Ministers announce £4.25 Million funding for battery and autonomous vehicle research at WMG. Warwick News and Events. University of Warwick. Available: https://warwick.ac.uk/newsandevents/pressreleases/ministers_announce_163425/?fbclid=IwAR300 GlPpUppRAcwl0jaU0qiob3DhKGAVfduoB 8s9ZCvPrNSRAPHUZwGI4c. Accessed 4 Dec 2020. Vanderstraeten, J., van Witteloostuijnb, A., Matthyssens, P., & Andreassi, T. (2016). Being flexible through customization. The impact of incubator focus and customization strategies on incubatee survival and growth. Journal of Engineering Technology Management, 41(2016), 45–64. Weiblen, T., & Chesbrough, H. W. (2015). Engaging with startups to enhance corporate innovation. California Management Review, 57(2), 66–90.

Chapter 11

Commercialisation and Industrialisation: Research Prognosis for Academia Entrepreneurships

Abstract  The ultimate expectation from any innovations that are nurtured through incubation and product development was to commercialise them for wealth creation, entrepreneurships and industrialisation. Several centres of excellence have been established in Southern Africa, either housed at or in collaboration with tertiary institutions, some of which have been actively involved in incubation of innovative ideas and start-ups. However, most of these innovations have not been taken beyond the innovation hubs due to several reasons such as lack of investors and adequate support from government or industry. This chapter explores ways in which ideas generated by academics can be ‘nourished’ and packaged to attract investment from industry in order to prepare them for start-ups that can be commercialised and possibly from which spin-off companies can emerge. This was accomplished by considering typical cases of this nature at universities in Southern Africa, with a view to use the developed knowledge to encourage the bridging of the gap between academia and industry. Keywords  Commercialisation · Entrepreneurship · Entrepreneurial university · Industrialisation · Intellectual property rights · Internationalisation · Spin-off · Start-up · Surrogate entrepreneur · Technology transfer office · Technopreneurship · Wealth creation

11.1  Introduction Over the years, commercialisation of innovative ideas generated by academia from research has received a lot of attention and has grown tremendously, albeit at different scales depending on which country and part of the world. This has been prompted by several reasons such as the generation of wealth to sustain activities at tertiary © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_11

229

230

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

institutions which were largely funded by insufficient government grants, the need to cope with the demands and rapid changes in technology brought on by the fourth Industrial Revolution, sustenance of a knowledge-based economy and the general provision of solutions to industry’s operational challenges and optimisation of systems. Some institutions have also used commercialisation as a way to attract potential investors for incubation and nurturing of start-ups by way of marketing their innovative ideas. Although commercialisation of research output and innovations by academics was essential for the advancement and transfer of knowledge, it can be a complex process that required well laid out systems to avoid legal challenges or failures, hence the thrust for this chapter to lay out the necessary foundation for successful commercialisation.

11.1.1  The Triple Helix Model Research on commercialisation of research output by academia has been carried out extensively in industrialised countries where models such as the triple helix have been developed to improve the synergies among academia, industry and governments (Lee et al. 2020). This has, however, been confined to the specific relationship and communication among the three. This chapter goes beyond the triple helix model by identifying the gaps that may have been created by omission of other key stakeholders and their important contributions, purposes and functions by using a systems thinking approach for integration. Some of these gaps and stakeholders that may be missing or ‘silent’ in the triple helix model were professional institutions for engineers, regulatory bodies for quality control and accreditation of qualifications, research and scientific organisations that may be privately owned or parastatals of governments. This chapter also focusses on three important aspects, commercialisation of academia research output, how academia entrepreneurships can contribute to the industrialisation of an economy, while laying the foundation and principles to assist academia to package their innovations for start-ups or commercialisation thereafter.

11.1.2  Background to Commercialisation and Industrialisation Commercialisation involves the introduction of new products or services onto the market or commerce for trading and generation of wealth from sales (Jamil et al. 2015). The term generally referred to mass production and sales, but it can also mean the transition from the innovation hub to the science and industrial park and to the market. Entrepreneurship is the generation of wealth or creation of value from a commercialised product or service (Shanker 2017). The generation of wealth in this regard is also regarded as a transformation which may include financial values but ethical and business values as well. Depending on the volumes,

11.1 Introduction

231

entrepreneurships usually cascade to industrialisation, which is an ongoing process and period of social and economic transformation that originated in the first Industrial Revolution to the current fourth Industrial Revolution. The transformations impacted on the livelihoods of people and societies from agrarian to industrial and have happened so rapidly and dynamically, in the process creating complex societies that required a complete new level of skills to drive the ever-demanding knowledge economies and extensive re-organisation of economies for manufacturing. In general, therefore, industrialisation encompassed the development of industries such as manufacturing, services, agrarian or health in a country or region on a wide scale (Nuvolari 2019). Numerous innovations have been developed by academics at tertiary institutions either through student projects or problem- and industry-based learning experiences. However, some of these innovations have not made it beyond the innovation hubs or incubation centres due to lack of investment and other related challenges. Some of the innovative ideas can be ‘stolen’ in the process and to prevent this from happening innovators are normally encouraged to register patents in order to protect their intellectual property rights (IPR). This chapter also analyses the various legislation in Southern Africa, which is largely made up of industrialising countries, with reference to some of those from the industrialised world in order to draw synergies and best practices but without altering individual countries’ legislation and how innovations and patents were protected.

11.1.3  Entrepreneurships in Academia Entrepreneurships in academia is a much wider phenomenon which covered a wide range of activities carried out by academics in partnership with industry such as commercialising innovative ideas and developing start-ups or spin-offs, part-time consultancy work in the provision of solutions for industry or continuous professional development of practising engineers in industry. Whichever one it was, the ultimate aim was to generate wealth or income in the provision of these services while industry enjoyed the profit generated from improved services. Such entrepreneurships were ‘nourished’ by investments from industry as business incubators and knowledge and technology transfer from academia. These may also include development and nurturing of start-ups to full-fledged or spin-off companies, articles of association, company formations, registration of patents to protect IPR and firmer and closer linkages with industry through formal partnerships. Entrepreneurships by academics was one sure way of demonstrating to industry and other would-be investors that solutions generated in tertiary institution laboratories were not purely for research and teaching students but actually provided solutions for societal and industrial issues. In addition, the collaborations, especially through secondments of academics and attachments of students were essential to develop databases of industry solutions through problem- and industry-based learning, thus developing appropriate

232

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

skills required by industry and hence adequately preparing students for future employment and driving industry. Well-articulated and formulated academia entrepreneurships were beneficial to all stakeholders; relevant skills imparted to future engineers, academia generating income to sustain activities and augment government grants, improved efficiencies in industry translated to higher profits, thus increases in revenue for governments through taxes. Tertiary institutions in Southern Africa have joined the bandwagon to commercialise their research through science and industrial parks in collaboration with industry as potential business incubators. As detailed in Chap. 10, the Government of Zimbabwe committed substantial capital to establish innovation hubs at all universities in the country as well as two agro-­ industrial parks at two of the main institutions. The drive was to fulfil the Education 5.0 initiative which placed emphasis on innovation and industrialisation for the provision of goods and services by the country’s tertiary institutions. This was also meant to create a situation where the institutions did not rely entirely on the small government grants for their operations. The thrust was also in line with the country’s Transitional Stabilisation Programme (TSP) (Government of Zimbabwe 2018) and the National Development Strategy 1 (NDS 1) (Government of Zimbabwe 2020) with the aim of transforming the country into an upper middle-income economy with a per capita gross income of between US$3500 and US$5000 in real terms as well as GDP of US$100 billion by 2030. Similar initiatives have been developed at other institutions in Zimbabwe and within the region. This chapter uses these case studies as the base for formulating the commercialisation and industrialisation models for academia entrepreneurships. The proliferation of incubators, science and industrial parks, especially in the Europe, the United States and other parts of the industrialised world, have realised a boom in revenue and creation of wealth by tertiary institutions (Saetre et al. 2009). This has prompted many governments to support tertiary institutions as a way to commercialise innovations by establishing policies, funding and legislation, even in industrialising countries as with the case for the Government of Zimbabwe’s establishment of innovation hubs and industrial parks, as a way to contribute to the knowledge-based economy and readiness for global competition. Innovation hubs, science and industrial parks were regarded as potential intermediaries between industry and academia (Jamil et al. 2015), hence the several stakeholders and the need to use a systems thinking approach. The major challenges in realising this noble initiative has been the lack of business incubators and investment from industry, to some extent caused by the inability to package investment proposals that can attract participation by industry. Whereas it may be viewed as if industry were not interested, it must be noted that industry, particularly the private owned ones, were not charity organisations but were businesses whose main goal was to generate profit and thus dividends for shareholders. As such, any promising and well-packaged business proposal that had the potential to increase a company’s profit was bound to attract investment, thus part of the aim for this chapter, to assist academia to package their proposals to attract investment and hence bridge the gap between academia and industry. Between 2018 and 2019,

11.2  Knowledge and Technology Transfer as Tools for Commercialisation

233

the Government of Zimbabwe developed the Education 5.0 system which included and placed emphasis on innovation and industrialisation as tools that can lead to commercialisation and the provision of goods and services to its citizens (Muzira and Bondai 2020). This was in response to correcting the colonial imbalances and the education system that was obtaining then, that focussed on developing an employee rather than an employer. The education system in Zimbabwe has been adjusted from lower to tertiary level by placing emphasis on productivity and entrepreneurship among the youths.

11.2  K  nowledge and Technology Transfer as Tools for Commercialisation Throughout the world, commercialisation received prominence in boosting the knowledge economy and creation of wealth through the participation and links between industry and academia, hence the evolvement of tertiary institutions to entrepreneurial institutions to support the commercialisation of research output and knowledge for economic growth and sustenance of the institutions’ activities (Jamil et al. 2015). In broad terms, therefore, a tertiary institution would thus be regarded as entrepreneurial when it focussed on establishing new enterprises, incubated innovations and promoted entrepreneurships from staff and students. The University of Johannesburg has embraced this notion by establishing various centres of excellence and institutes, such as the Institute for Intelligent Systems (IIS) focussed on driving and leading in coping with the fourth Industrial Revolution through ‘The Future Re-imagined’ mantra (UJ 2020). Due to the multi-faceted connections of various stakeholders such as governments as policymakers, academia as researchers and transferors of knowledge, industry for production and provision of goods, professional and regulatory bodies for the standardisation of training and curricula, a systems thinking and integrated approach was required to ensure the success of commercialisation of innovations by academia. Commercialisation was thus dependent on the success of research and development by academia, naturally followed by evaluation of the potential of the innovation, protection of intellectual property through patenting, incubation, industrial parks for production trials, licensing or spin-offs and eventually industry for mass production and release to the market or commercialised to contribute to wealth generation and thus a knowledge-based economy. As the product was marketed, it went through primarily three stages, growth, maturity and decline, at which point innovators should start to think of redesigning or rebranding in order to continue to attract sales and growth in the knowledge economy. Figure 11.1 shows the systems thinking integration of academia and industry, illustrating the core functions such as teaching, research and community service for academia, generation of profits and dividends as well as economic development for industry and research and development by research institutions in conjunction with industry. The common or intersecting activities were innovation where academia

234

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

Fig. 11.1  Systems thinking integration of academia and industry

provided ideas and knowledge and industry invested as business incubators. Commercialisation of the ideas or innovations was carried out by both academia and industry, while both activities also contributed to the industrialisation of economies. The reinforcing loop between academia and industry in this regard demonstrated that an increase in knowledge and technology transferred to industry by academia also resulted in the production and generation of profit and wealth to enable industry to further invest in innovations by academia. Much as industry enjoyed the academic freedom and interactions with academia, it must also be realised that there were elements of confidentiality related to protection of intellectual property rights. However, the linkages between the two, created dynamic situations that potentially resulted in the application of knowledge or technology transferred by academia to enable the generation of profit from successful business ventures through commercialisation. As depicted in Fig. 11.1, the transfer of knowledge and technology from academia can be through various avenues such as licensing agreements, business incubation and investment by industry or purely successful spin-offs that can flourish to become fully fledged industrial operations or start-ups (Shanker 2017).

11.3  Academia Start-Ups and Spin-Offs While research and development of innovative solutions were good for advancing knowledge and technology transfer, the ultimate objective in all these activities was to grow the knowledge economy and generate wealth to sustain the research activities and possibly invest back in order to generate other future solutions. Research activities were normally concentrated at research or tertiary institutions, the

11.3 Academia Start-Ups and Spin-Offs

235

solutions of which were fed to industry for commercialisation and production. This can be accomplished through various ways such as patents and licences. However, the most common route to creation of businesses by academia was through start-ups and spin-offs. A start-up is a business or project undertaken by an innovator or entrepreneur to develop, grow and validate a scalable business venture (Katila et al. 2012). While entrepreneurships were generalised to refer to potential businesses that may or may not grow, start-ups were usually new businesses whose potential and feasibility would have been analysed and deemed to have the capacity to grow and generate wealth. On the other hand, a spin-off is typically an academia transfer of knowledge, research output or technology to industry for production (Shanker 2017). Similar to a start-up, spin-offs involved the creation of new businesses that would have been deemed to have the potential to grow and usually this was done within a tertiary institution’s innovation hub. Under such circumstances, the institution retained the ownership or developed a business venture where the academics involved became the entrepreneurs, depending on what agreements would have been reached. Alternatively, in the absence of entrepreneurial or business acumen and skills, tertiary institutions can enter into agreements with external expertise to develop and implement the project. This can be done through technology licensing or transfer of the academics’ rights for commercialising and it is normally advisable to engage legal expertise in order to protect the innovations. Another alternative would be to package the business venture in order to attract investors from industry in the form of business incubators. However, whichever route was taken, the innovator or researcher always assumed the role of an entrepreneur under the inventor entrepreneur model or a surrogate entrepreneur model in the event that external expertise was sought (Shanker 2017). Spin-offs that are generated from government sponsored tertiary institutions normally faced some challenges due to the non-profit making nature of such institutions, hence the frequent use of surrogate entrepreneur models by such institutions. Typically, the challenges include capacity to mobilise financial and human resources, formulating the innovation in an acceptable business model that matched demands from the market. The industrialised world has gone further to classify spin-offs from universities depending on the source of the spin-off and the type of model adopted for nurturing it to grow. Some of these have been categorised as technology based but with little potential for surrounding market, appropriate technology for local solutions, venture capital-backed spin-offs and consultancy-oriented spin-offs (Shanker 2017). The development and setting up of start-ups or spin-offs by tertiary institutions, particularly those that survived almost entirely on government grants was driven by the desire to commercialise and generate income for the institutions (Mascarenhas et al. 2017). This drive also enhanced the academia–industry partnerships, which required statutory policies that encouraged industry to invest in spin-offs and start-­ ups through possible tax rebates as incentives in the same manner as manpower development funds. While there has been a push to establish university spin-offs, this has not been as successful in industrialising countries as it has been in the

236

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

developed world, due to lack of capacities and expertise as experienced in Southern Africa. However, it was pleasing to see the efforts being made by institutions in the region to be self-reliant in view of the dwindling public funds. It was also quite evident from the SAE2Net partnership that the institutions required training academics with business skills to avoid surrogate entrepreneurial models, but empower them with the capacity to manage the spin-offs.

11.4  Intellectual Property Rights in Academia Research The onset of the fourth Industrial Revolution saw the rapid and dynamic changes in technology and so were the increased numbers of inventions and innovations by research and development institutions. Although industrialising countries are still struggling to transition from the third to the fourth Industrial Revolutions, global competition and association with institutions in the industrialised world have forced institutions in Southern Africa to keep in tandem with these developments, hence the proliferation of innovations in the region. These engineering innovations in Southern Africa were now technology driven and ranged from manufacturing systems for productivity and efficiency improvements, smart ways of harnessing solar energy for power, water resources engineering and management, food science and processing, artificial intelligence, etc., as articulated in some of the case studies in Chap. 6 of this book. Despite these numerous activities and new technologies, only a few have been registered as patents to protect the intellectual property rights. However, researchers in Southern Africa were increasingly becoming aware of the importance to protect their innovations. Intellectual property rights (IPR) included patents for innovations or inventions, unique industrial designs, trademarks and copyright (Gadallah 2010). Legislation of this nature differed from country to country, but generally embraced the same principles. IPRs enabled the investment of time and capital set aside for research and development to be recovered through commercialisation of the research output and royalties by protecting the innovators’ intellect from copying and plagiarism and thereby encouraging more innovations by academics and their institutions. The IPR systems are useful to tertiary institutions as databases of information from which further knowledge and technology can be created and developed for further research. For instance, in the case of the enactment of the Education 5.0 by the Government of Zimbabwe, IPR in this regard should be viewed as the source for products and services when they are commercialised or used for economic gain. Intellectual property rights are not only used to protect the institutions’ and academics’ intellect, but also to enhance the development of regional and domestic industries through education and the creation and transfer of knowledge. In this regard, tertiary institutions around the world, regardless of where they are domiciled, encouraged the registration of patents through legislation and policies that were suited to ensure proper ownership of work done by their academics. The registrations of patents and possibly agreements entered into with business incubators

11.4 Intellectual Property Rights in Academia Research

237

must clearly spell out the ownership, although this can sometimes be problematic and create further obstacles to investments by industry. The complications arise from cases where the academics and students were in different categories such as full time, undergraduate or graduate. While the registration of patents to protect IPR were mainly for economic value and thus business and profit oriented, academics engaged in research and development and wishing to pursue this route should always bear in mind, the core business of tertiary institutions, which was to disseminate knowledge and information as well as to develop the human resources required to drive industry (Karjala and Kiskis 2011). The Education 5.0 policy for the Government of Zimbabwe placed emphasis on innovation and industrialisation through the provision of goods and services, but this should be done within the framework of the core business of teaching and research. However, in so doing, the tertiary institutions must also recognise and reward academics for generating commercially viable ideas and IPR through promotions and supporting the ideas for commercialisation as an incentive for innovation and creativity as well as the universities’ global rankings and future research. All these processes and particularly the registration of patents and IPR can be done through dedicated Technology Transfer Offices (TTO) within the institutions. Apart from enabling commercialisation of research output on behalf of academics who are normally busy with the institutions’ core business, TTOs were used as vehicles for empowering institutions and academics to realise benefits from academia generated intellectual property. In the long-term and in order to reduce costs, consolidated TTOs for several institutions in a partnership (Karjala and Kiskis 2011) such as SAE2Net may be more beneficial and the long-term desire for managing IPR regionally. The quantum of spin-offs or start-ups that tertiary institutions may generate and their effectiveness thereof is related to the IPR protection costs, capacity for business development of TTOs and the tertiary institutions’ legislation and IPR policies. Previous research in industrialised countries demonstrated the need for pooling resources in partnerships as well as the development of technology transfer agents with capabilities of properly marketing goods and services that can be generated by university spin-offs or start-ups (Mascarenhas et  al. 2017). This required tertiary institutions and decision makers to ensure that such offices were manned by experienced personnel or training should be provided to develop technology transfer staff with business skills and experiences for driving and protecting such ventures. This can be accomplished by engaging industry, even as surrogate entrepreneurs and not necessarily as business incubators. This will encourage a business approach that will enable tertiary institutions to manage internal research and innovations including patents, IPR, start-ups and spin-offs while enhancing the institutions’ growth and expansion in the creation of wealth and broad-based contributions to transfer of knowledge (Guerrero et al. 2016). Although revenue from university research primarily came from start-ups and spin-offs as well as licensing of patents to established companies, the success and quantum of business generated from such ventures was dependent on where the tertiary institutions were domiciled as well as the type of industries in the neighbourhood, hence the need for such collaborations as SAE2Net to mix the blend of institutions and industries in the region.

238

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

11.5  Support Infrastructure The successful commercialisation of start-ups and spin-offs by tertiary institutions require well-established support infrastructure to nourish them to growth, wealth creation and appropriate knowledge transfer. The development of such business ventures, domiciled at or owned by universities was a multi-faceted concept that was driven by several social, legal and technical issues (Pazos et al. 2012). These factors revolved around capabilities and capacities derived from institutional resources, human capital, financial resources, business incubators and commercial and marketing potentials. According to research carried out by Pazos et al. (2012) on a resource-based view of university spin-off activities in Spain, a number of hypothesis were made and the conclusions drawn from them can also be useful to spin-off activities in industrialising regions such as Southern Africa. Previous successful spin-offs at a tertiary institution form the foundation for the development and growth of future spin-offs, providing a reference and the basic support foundation for successful start-ups. With the rapid and dynamic developments in technology, spin-offs with greater potential to grow were those that were technology driven such as artificial intelligence, machine learning and modern engineering and manufacturing processes. As such, there was bound to be widespread development of such tools and technologies around the globe. It was therefore imperative to have the right technical support in terms of capacity to utilise or develop technologies in tandem with developments in the fourth Industrial Revolution. While it may be desirable to support or promote any innovations be it in humanities and social sciences or life and applied sciences, the degree of success was dependent on the potential that each innovation brought or the demand that the solution had on the market. Generally, those in the latter group have broader chances of succeeding and attracting business incubators, as these were evidently ‘low-hanging fruits’. Innovations and inventions can be created by any enterprising academic. However, for the purposes of attracting attention from investors, the profiles of the academic staff involved in the innovation also mattered substantially, where business incubators would generally trust to sacrifice their investments to high-quality research and academics. It may therefore be worthwhile to associate appropriate high-level academics such as professors with each spin-off that an institution developed. Financial resources were also key to the development and incubation of innovations through commercialisation. Usually inadequate budgets from either the university authorities or from central governments can be a strain and many spin-off ventures have failed to take off the ground for that reason. Apart from appropriate packaging to attract support from industry, partnerships of institutions within the same region, such as SAE2Net, may be useful to apply for external funding as a consortium rather than individual institutions. Support from industry, in the form of business incubation and appropriate investments, was instrumental in the creation and growth of university spin-offs and start-­ ups. Such support was vital and a ‘win-win’ situation for both parties as academia realised income to enable them to create more ventures and sustain activities while

11.6  Entrepreneurship Models and Mechanisms

239

industry had the opportunity to earn dividends or royalties from the ventures or better still profit generated from the spin-offs in the case where the spin-off was transferred through some licence agreement for production in industry. The presence of appropriate expertise within an institution’s TTO boosted the growth and potential of spinoffs. In the event that the university did not have appropriate skills and human capital in this regard, either training of existing staff to acquire the required business skills or simply employing the slightly more expensive route of surrogate entrepreneurial models where external expertise was hired specifically to drive the development and commercialisation of the innovations. The establishment of innovation hubs and industrial parks by institutions in the SAE2Net partnership, as alluded to earlier, has provided the basic foundation and support infrastructure for nurturing and incubating innovations and that provided an attractive platform for industry to invest. Roig-Tierno et al. (2015) analysed the use of infrastructures to support innovative entrepreneurship and business growth from which it was established that it was necessary for governments to establish policy mixes that combined infrastructure and the users, where business growth was observed from the combination of the two. However, to achieve the positive outcome of employment creation and business growth required policymakers to persuade industry to invest as firm support infrastructure in terms of business incubation and industrial parks for the benefit and success of entrepreneurship support services. It was in the best interest of policymakers and governments to provide all the necessary support services to ensure that most innovations were developed beyond the innovation hubs and into the industrial parks and finally commercialisation by way of employment creation and ultimately taxes that were remitted by industry. The development of new ventures and businesses was best shaped by the level of resources and access to those resources, coupled with the culture for entrepreneurship (Roig-Tierno et  al. 2015). Tertiary institutions’ thrust to develop supportive infrastructures was supposed to promote commercial activities within the institutions, bearing in mind the core business of these institutions. Although the income generated from such activities was useful to sustain future innovations and spin-offs, the effectiveness needed to be quantified to justify sustaining the activities (Williams 2013). In order to increase the number of innovations and the activities thereof within an institution, it was imperative for the authorities to magnify communication links between new and existing spin-off companies to provide a base over which benchmarking can be carried out. Their demands and requirements will then constitute policy and overall strategy for the institution’s spin-off and start-up business ventures, which can be used by future innovators as reference and standard.

11.6  Entrepreneurship Models and Mechanisms Several studies have been carried out to analyse different options and models for start-ups and spin-offs that can be used as a foundation for entrepreneurships by engineering academics (Guerrero et al. 2016). Most of these have focussed on how entrepreneurships by academia can help to generate income to sustain activities of

240

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

tertiary institutions and these have demonstrated that business incubation and investment by industry positively contributed to academia entrepreneurships (Shanker 2017). This was also illustrated and demonstrated by the initiatives by institutions under SAE2Net. These included the agro-industrial park established by the University of Zimbabwe to process agricultural foods, the Food Science and Technology centre under Universidade Eduardo Mondlane in Mozambique for the development of new technologies to reduce post-harvest losses, especially at the level of small farmers, the Centre for Renewable Energy and Energy Efficiency in Namibia for developing and implementing competitive and innovative strategies for harnessing the abundant energy from the sun and various other initiatives from the partner institutions. Academia entrepreneurship has the potential to boost and facilitate knowledge economies for the countries and regions where they are domiciled. The partnerships of the institutions in Southern Africa under SAE2Net was also premised on this objective to improve the regional economy through various initiatives, one of which was the establishment, nurturing or improving centres of excellence within the region in order to be competitive on the global market. Although the provision of financial resources by national governments was key to the success of academia entrepreneurship, there were other requirements such as regional teamwork and sharing of the little resources that may be available, expertise and talent available, infrastructure and the desire and spirit to work towards creating and inculcating a culture for entrepreneurship among engineering academics. Many renowned universities across the globe have adopted entrepreneurship for academia as a necessary tool for successful commercialisation. The examples of centres outlined earlier and detailed in Chap. 10 have established Technology Transfer Offices (TTOs) within their innovation hubs or industrial parks as the central point and intermediary between theory (academia) and practice (industry). The main responsibility for the TTOs would be to identify academia spin-off opportunities while carrying out other tasks such as establishing databases of innovations and research outputs, patents, inventions by academics, registering patents to protect IPR for those promising innovations, testing the market and exploring the potential of innovations for commercialisation as well as identifying potential business incubators to support promising start-ups and spin-offs. Legislation by most countries allowed academia to own patents for research supported and funded by government, thus benefitting from the royalties of successful commercialisation. However, for start-ups supported by business incubators or the private sector, specific agreements should be drawn up prior to registering the patents, clearly specifying how much parties will own from the IPR. Such legislations and agreements encouraged academics and paved the way to successful commercialisation and entrepreneurships. This chapter focusses on creating a platform for availing the different avenues to analyse knowledge and technology transfer from academia to the market through commercialisation to entrepreneurship and the requisite mechanisms such as business incubators, industrial parks, startups and spin-­offs. This was done through identifying challenges within the specific initiatives that have been established in Southern Africa, especially in terms of

11.7  Academia Entrepreneurship in Southern Africa

241

capacities and the levels of support from governments and regional industry players in these ventures. Another avenue explored was analysing the commercialisation barriers and drivers, partnerships with industry to attract investment and promote commercialisation and entrepreneurship activities within the innovation hubs and industrial parks, how the innovation hubs were enabling the promotion of marketing innovations and success stories from the current activities. Literature on incubators, science, technology and industrial parks managed or owned by universities has demonstrated the importance and positive contributions to the mechanisms for promoting innovations to the market and the successes of spin-offs or start-ups (Jamil et al. 2015). Despite the challenges for capacity and support from governments and local industries, tertiary institutions in Southern Africa have sustained the operations of innovation hubs and industrial parks even from the meagre grants from their governments, following the realisation that such initiatives provided tangible outcomes demonstrated by the fact that commercialisation was an effective tool for knowledge and technology transfer from academia to industry to achieve growth, employment creation and sustainability.

11.7  Academia Entrepreneurship in Southern Africa Tremendous efforts have been made by all institutions in Southern Africa to embrace the move towards commercialisation of research output that naturally filtered to industrialisation and entrepreneurship. This has largely been driven by narrowing the gap between academia and industry through collaborated policies and partnerships. However, a lot still needed to be done as industries within the region still viewed tertiary institutions as centres for teaching and research only. In order to break this barrier and mindset, it was essential for universities to prove beyond doubt that their work went beyond teaching and research but can contribute significantly to the growth of industries and economies, hence the thrust by the Government of Zimbabwe for Education 5.0. One certain way of demonstrating this capability by academics would be to increase their presence in industry through secondments where they can use the opportunity to carry out improvements such as modelling and optimisation of production processes as the case studies detailed in Chap. 6, carry out consultancy work for industry or take the lecture room and students to industry for problem- and industry-based learning. The various innovation hubs and industrial parks established by the Government of Zimbabwe at tertiary institutions, the centres for renewable energy and various initiatives by the Government of Namibia, the foreign support for food science and technology in Mozambique, the establishment of the Institute for Intelligent Systems at the University of Johannesburg to lead in the fourth Industrial Revolution, among others, were a clear demonstration of the need and importance of commercialising research output by tertiary institutions, supported by their national governments. All these efforts were meant to support

242

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

research to focus on provision of appropriate solutions for local challenges, which can also be extended beyond the region where possible. Despite the progress and success in this direction to commercialisation, a lot still needed to be done by the institutions to address the issue of intellectual property rights, licences and patents as most of the institutions were aware of the need to protect their intellect but were not really practising it. Many of the researchers who were contacted, appeared to indicate that their main focus was to research and produce results while the rest, in terms of IPR, was assumed to be taken care of by their university administration. However, most of the institutions have also not yet established TTOs, presumably for lack of expertise in that regard. It could be useful to take a leaf from the industrialised world where formalised practice models and institutionalised mechanisms have been developed for commercialisation and entrepreneurship. Just as much as entrepreneurship has now been incorporated as part of the curricula for the institutions under SAE2Net, so should patenting, licensing and IPR education. Efforts have been made at some of the institutions such as the University of Zimbabwe and the University of Johannesburg, in line with the institutions’ strategic objectives, where new layers of positions were created, such as the executive director for research and innovation and various research manager positions to provide the administrative support required for such technology transfers. However, it might be necessary and important to establish an independent body for innovation and entrepreneurship that can operate outside the auspices of academia and industry to provide independent assessments and act as the intermediary between the two as well as boost the transfer of technology from academia for commercialisation. The agro-industrial park established at the University of Zimbabwe was officially opened and launched in 2020 with five production lines for food and agricultural produce processing such as the production of potato-based bread, chips and crisps. Although these may sound basic and not so innovative, but it is the potential and capacity that has provided a starting point for more. The centres and programmes for renewable energy established and managed by the Namibia University of Science and Technology, such as NEED, CREEE and PARTICIPA as detailed in Chap. 10, have attracted support from the Namibian government as well as regional bodies such as New Partnership for Africa’s Development (NEPAD) and foreign funding agents such as the European Development Fund (EDF), in collaboration with countries such as South Africa and Botswana. These centres were established with the objective of not only providing local and regional solutions for renewable but also to support and combine the various mini projects from medium to large initiatives with a view to commercialise them in order to provide services in renewable energy and the transfer of technology therein. The Food Science and Technology Centre at the Universidade Eduardo Mondlane in Mozambique has also attracted support from their government as well as from the Swedish International Development Cooperation Agency (Sida) not only for the research leading to PhD qualifications but also to focus on research and innovation on characterisation of food products, quality control, post-harvest food management to commercialisation in conjunction and partnership with the food industry in Mozambique.

11.8  Performance Measurement and Sustainability

243

The Harare Institute of Technology has been one of the pioneering institutions in the region to introduce technoprenuerial studies to all their students as they work closely with industry, particularly in production and processing through their Technoprenuerial Development Centre (TDC). The institution was one of the very few within the SAE2Net partnership that has developed technology transfer offices and functionality for licensing of patents to industry for the production of such goods as packaging bottles, drugs, sanitisers and other pharmacological products. The agro-industrial park established at the Chinhoyi University of Technology has witnessed potential growth and commercialisation of their artificial insemination to produce quality bulls for the farming communities within Zimbabwe, with a potential of exporting the innovation to the other SADC countries. With the requisite support from the Government of South Africa through the Department of Science and Technology (DST) and the National Research Foundation, universities in South Africa have successfully established technology transfer centres, such as the Institute for Intelligent Systems (IIS) at the University of Johannesburg, one of the institutions in the SAE2Net partnership. While IIT focusses on training of academics to higher degrees as well as offer CPDs to practising engineers in multi-disciplinary areas, their main focus was strategic partnerships and research and development with industry in the provision of solutions and leading in the drive and management of the fourth Industrial Revolution in South Africa. Their provision of solutions, using artificial intelligence, big data science and analytics, machine learning and IoT revolved around enterprise development, incubation and commercialisation of innovations through their well-established and dedicated TTO.

11.8  Performance Measurement and Sustainability The commercialisation of research output and innovations by academics through start-ups and spin-offs can be a very difficult process especially where no sufficient support was available. Where support was available, even from business incubators or grants from the institutions or national governments, it was imperative for innovators or those responsible for driving the commercialisation to ensure that the process yielded positive results, through constant monitoring, evaluation and performance measurement to satisfy the investors as well as sustain and grow the business venture beyond the innovation and start-up mode. Researchers have developed several monitoring and measurement tools for such business ventures, ranging from benchmarking and comparative analysis, importance-performance analysis and the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) (Sooreh et al. 2011). This section provides guidelines on how to employ some of these measurement tools in order to monitor and enhance the performance of university start-ups and spin-offs for sustainability and attraction of business incubators and investment from industry.

244

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

Apart from the general trend where some tertiary institutions such as polytechnics and technikons have been converted to universities in Southern Africa, institutions of higher learning have been in transition in recent years. The transition has not only seen the universities competing for research grants as well as the best students to improve their global rankings but focus has now been more on developing entrepreneurial institutions that were able to generate income to sustain their operations in view of the dwindling research grants from their national governments, especially for those that were wholly funded from the national fiscal allocations. Institutions with capacity to generate their own income through the commercialisation of their research output and innovations stood a much better chance of survival and sustainability than those that were purely for research and teaching, hence the need and importance to inculcate a culture of commercialisation, but more so, one that was measurable to improve performance. Although a lot of effort has been put by tertiary institutions to engage with industry in various forms, the need for entrepreneurial universities went beyond just engaging with industry through secondment of academics and attachment of students. More of these interactions between industry and academia should include commercially oriented activities to generate wealth and thus be in proper sync with industry’s main objective of generating profit (Sooreh et al. 2011; Goldratt and Cox 2014). The gap between academia’s implicit knowledge and market needs should be considered as crucial to resolve to become relevant and recognisable by potential business incubators (industry). The principal context in doing so would be to present an entrepreneurial university that has the capabilities of generating income to sustain operations.

11.8.1  Importance-Performance Analysis Importance-performance analysis (IPA) is a methodology that enabled researchers to prioritise the characteristics of an issue or resource to determine the one that should receive attention (Warner et al. 2016). Issues that should be placed at the top priority were assigned to elements that were either the potential market’s main concerns, thus regarded highly. This methodology was for applications across the board as long as there was provision of some kind of goods or services to some customers. The importance of each issue can be evaluated and then weighted on a relative scale by benchmarking with the performance of a system in order to analyse and establish the applicability of each issue using appropriate charts, to ultimately make decisions and/or adjust policies. This was the basis on which researchers have used TOPSIS to prioritise issues in such models. Originally, IPA was used to examine customer satisfaction by establishing what was important and how it functioned. A typical IPA is shown in Fig. 11.2 with four quadrants into which each issue (dimension) and its elements can be placed into any of the four quadrants depending on their relative weightings.

Fig. 11.2  A typical importance-performance analysis. (Source: Warner et al. 2016)

Importance

11.8  Performance Measurement and Sustainability

245

A

Focus for Improvement

B

Maintain Good Performance

C

D

Minimal Priority

Rare Occurrence: Minimal Priority

Performance

Those in quadrant A were usually the ones to focus on or allocate more resources for improvement as these were crucial but may not be satisfying clients, while those in B were matching both the high importance and high performance and by all means must be kept that way. Any lack of attention to elements in quadrant A could endanger the success of any entrepreneurial activities within an institution. Ideally, this was what an IPA measurement strived to achieve. A closer analysis of the elements in this quadrant can possibly be used as a benchmark in order to achieve the status where all elements were in that quadrant. Elements in D were rare as this was a demonstration of very satisfied customers but of relative low importance, the same applied to C where both importance and satisfaction were low. Policy and decision makers should thus allocate less or not much resources to those elements in quadrants C and D. However, the mere fact that they were there, even though they had low importance and low satisfaction to customers, they should not be neglected but instead thrive to move them towards quadrant B.

11.8.2  Analysis of Inputs and Outputs The inputs for an entrepreneurial university’s innovation hub or incubation centre where there were some commercialisation activity can be broadly classified as formal, informal and internal (Sooreh et al. 2011). Formal and informal inputs were factors that were external to the institution such as the country’s legislation and entrepreneurial culture, whereas internal inputs referred to components which were directly related to the tertiary institution such as the students and academics available. The three categories on inputs can be further characterised into segments such as policies, missions and objectives, entrepreneurial programmes in the curricula, support systems available, communication channels. Other dimensions to assess the performance and potential of an entrepreneurial university were the potential students and staff. Internal inputs were the ones that measured the university’s well-­ being such as its capabilities and financial resources which can be used to consolidate the institutions’ standing.

246

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

The outputs of an entrepreneurial university can also be measured and categorised as formal, informal and internal. The formal and informal variables were those that influenced the outputs of a tertiary institution, while internal ones were also those that were related to the entrepreneurial university. Formal outputs included effectiveness of the entrepreneurial networking systems, the number of partnerships or strategic alliances generated as well commercialisation systems, conventions and policies established. Informal outputs included customised role models or entrepreneurial culture cultivated within the institution. Internal outputs of the commercialised unit of a tertiary institution were critical as these were the ones that largely measured and evaluated the performance of the institution. These ranged from commercial centres established such as innovation hubs, incubators, science and industrial parks. In addition, the networks established, available human resources such as professors, dedicated researchers and level of students, innovations and inventions created, start-ups and spin-offs generated and successful as well as appropriate and scalable research to address local or regional needs. Figure 11.3 shows an importance-performance analysis for SAE2Net institutions derived from information obtained from interactions with personnel from the institutions and then averaged out to see the common trends. The implications of this graphical display are that most of the institutions have established networks, systems and conventions for commercialisation and the performance of these has been fairly decent. However, the number of original inventions and innovations still remained relative low in terms of performance and yet those are the major drivers for successful commercialisation. This called for the authorities to prioritise and set aside funds to encourage more promising innovations. Another significant challenge faced by most of the institutions under SAE2Net was the level of qualifications for their researchers. This also required authorities to prioritise higher degree training, possibly through DTCs. Key: Formal 1: Networking Systems Formal 2: Systems and Conventions Formal 3: Strategic Alliances Informal 1: Role Models Informal 2: Entrepreneurial culture Internal 1: Appropriate Research Internal 2: Innovation Hubs/Centres Internal 3: Entrepreneurial Networks Internal 4: Innovations and Inventions Internal 5: Human Resources

Fig. 11.3  Importance-performance analysis for SAE2Net institutions

11.9  Drivers and Barriers to Academia Entrepreneurship

247

11.9  Drivers and Barriers to Academia Entrepreneurship Despite the interest generally exhibited by students and academics and the enthusiasm to prove that their innovations really worked and their desire to propel these to businesses through start-ups or spin-offs, the majority of the innovations were usually dumped at project level with a few finding their way to business ventures (Smith et  al. 2020). Several reasons have been attributed to these successes or failures lumped into drivers and barriers to commercialisation by academia. While the enthusiasm was quite evident during the execution of the research or projects, the entrepreneurial spirit sometimes faded down on completion or graduation. It was therefore imperative to provide guidelines on what made good ideas fail to reach commercialisation and also what stimulated and motivated innovators to carry forward their ideas beyond conception and execution to commercialisation and entrepreneurships. This section explored all the stimulants and obstacles with reference to some of the case studies under the SAE2Net partnership and also provided guidelines on packaging proposals or start-ups to attract support and funding from industry. Understanding these drivers and barriers not only helped to prepare winning proposals, but also assisted in benchmarking against those that would have either been successful or failed in the past. As tertiary institutions transformed to entrepreneurial universities, there was increased competition for the limited research grants from governments and equally stiff competition for the same from industry, hence the importance for appropriate packaging.

11.9.1  Stimulants for Academia Entrepreneurship The stimulating factors to drive academia to commercialise their research output and eventually into fully fledged entrepreneurships have been classified by researchers into push and pull factors (Smith et  al. 2020). Pull factors were those that attracted academics to devote their time, intellect and expertise to the innovation from beginning to end and these included independence and minimal interference from authorities, the satisfaction derived from applying one’s knowledge to solving a particular problem or simply providing a service and the quest for greater things and contributions to knowledge. Pull factors generally worked to encourage researchers to become entrepreneurs and employers, apart from incentivising innovators through awards or prizes for achievement. This would also include recognition among peers, that in itself inculcating a culture for entrepreneurship and also worked as a motivator for future generations. The push factors included the fear for unemployment, possible redundancy from the current employment and to some extent the dislike to be employed and commanded by other professionals. The unemployment rates in SADC countries varied from country to country and were directly related to the gross domestic products for

248

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

the countries. The higher the GDP, the lower the unemployment rate. Since the global financial crisis of 2008, most countries in the SADC region were negatively affected, albeit at different scales. The semi-industrialised South Africa, diamond-­ rich Botswana and Namibia, which is in the Common Monetary Area (CMA), formerly the Rand Monetary Union, were the least affected, while the rest, within SAE2Net were heavily affected. These included Zimbabwe and Mozambique, implying that the chances for employment after graduation in these countries were much lower, hence the greater need to consider commercialising innovations in these countries in order to create employment. For Namibian and South African institutions, the challenge could just be redundancy due to downscaling of companies or just the desire for one to be independent.

11.9.2  Obstacles to Academia Entrepreneurship Most marketable innovations at tertiary institutions were developed by students or academics in the science and technology disciplines (Pazos et al. 2012). However, traditionally these were the same groups that ordinarily did not pursue entrepreneurial courses at university, a preserve of mostly social sciences and commerce students. As such, these students lacked general business appreciation and knowledge of finance and entrepreneurship as well as the absence of appropriate mentors in the same disciplines. Gradually and in recent years, most engineering institutions have now incorporated business courses, such as professional and industrial studies, engineering management and entrepreneurial skills at the University of Zimbabwe, in order to develop business-minded students capable of starting and managing business. Researchers such as Pazos et al. (2012) and Smith et al. (2020) identified the fear of failure and lack of confidence as other barriers in the case of Spanish and British academic entrepreneurs. The interactions with innovators under the SAE2Net collaboration established the fear for uncertainties in the market, particularly for those in Zimbabwe and Mozambique, indicating some form of link between the country’s performance and prospects for successful entrepreneurship. Access to finance was also identified as a barrier to commercialisation particularly for most of the institutions in the SAE2Net partnership. Following the global financial crisis of 2008, most companies in Southern Africa downsized and have mainly been focussing on core businesses, leaving meagre allocations for research and development. Some of these barriers have been overcome in several ways such as the introduction of business courses to all students, co-supervision and co-mentoring of students and potential entrepreneurs by business partners from industry and access to social capital through networking such as the SAE2Net collaboration.

11.9  Drivers and Barriers to Academia Entrepreneurship

249

11.9.3  P  ackaging a Winning Start-Up to Attract Business Incubators In view of the stiff competition for dwindling research grants from governments or industry, it was imperative for academia to properly package their proposals for start-ups in order to attract investment from industry, governments or foreign aid agencies. Generally, guidelines for writing business proposals would have been covered in business courses at university. This section presents a summary of six key steps to pay particular attention to, in addition to the general requirements for business proposals. These steps will help to make a difference between any other proposal and a winning proposal. This principle was based on the two adages ‘If I had an hour to solve a problem and my life was dependent on it, I would use the first 55 minutes determining the proper questions to ask’ attributed to Albert Einstein and ‘Give me six hours to chop down a tree and I will spend the first four sharpening the axe’ attributed to Abraham Lincoln. These sayings were a clear demonstration of the importance of planning and packaging processes in order to succeed in carrying out a task. Having developed a viable innovation that was fit and mature to be commercialised, the next logical step would be to package it in a business proposal, a document that should be convincing enough to attract investment. Before preparing the proposal, it is vital for the researchers to bear in mind that, even though it might be a novel idea, there were numerous other researchers who may be preparing similar proposals for other innovations to attract investment from the same business incubators, hence the need to prepare one that stood out to win attraction from would-be investors. No matter how novel an innovation was, the way it was packaged and presented made a lot of difference. Quite often, industry may solicit for specific proposals that included guidelines but this guide is for unsolicited proposals, which are usually more difficult to package. Over and above the general contents of a business proposal, the following are guidelines to make a proposal stand out. Unless an innovation was developed in response to a request by a company, in which case it was solicited, most business proposals for innovations are unsolicited and should therefore save as a way of introducing or marketing the product or service. Solicited business proposals were not only easier to prepare but had a higher chance of being accepted because the company would have already specified the need for them. However, these would obviously have stiffer competition, similar to tendering for provision of goods and services. Unsolicited proposals were like a ‘shot in the dark’, hence the need to pay particular attention on how best to package them. The basic business proposal should contain the following information in general: summary detailing the proposal, identification and acknowledgement of an existing problem, proposed solution and a clear methodology for solving it, deliverables, timelines and costing, information about the researcher or company, references for previous work successfully

250

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

accomplished as well as terms and conditions. In preparing the business proposal, it must be clearly distinguished from a business plan, though a proposal draws information from a plan. The focus for the business proposal should be on the potential investor, whereas a business plan focusses on the researcher or innovator. Before preparing or submitting a business proposal, it is imperative that all the information is available and accurately presented in such a way that a potential investor was not left with any questions. At this stage it might be useful to pretend as if the researcher was the investor, and therefore, probe what sort of questions may be asked. This can be done through brainstorming and involving colleagues who may assist to ask the right questions so that the proposal was comprehensive. The process of developing the business proposal can also be treated as a looping mechanism where one jumped to the next stage, but if an additional question came up, then they revisited the stages. The second step would be to clearly specify the business scope to address the work that needs to be done in order to satisfy a client, more like the repackaged aims and objectives. This should be straightforward for researchers because they will already have an appreciation of their work and its execution. Understanding and knowledge of what needs to be done provides an accurate assessment of the costs, related to who will do the work, how long it will take, what materials and expertise were required, etc. Probably the most difficult stage is the computation of costs to provide an accurate budget for investors. The help of a cost or management accountant at this stage may be necessary especially if the researcher is not very conversant with finance or cost accounting. However, it is important to be all-inclusive of the costs to carry out the task, hence the need to walk the accountant throughout all the stages. Sufficient contingencies must be allowed for because once the investment was agreed, it might be difficult to reverse and at the worst, end up in litigation. The contingency should be part of the cost, after which the profit margin can be worked out. The profit margins can be variable depending on the type of business, hence the need for cost-accounting advice. The fourth stage would be to write and package the proposal. Articulate presentation of the proposal was essential, right from the cover page to the end. Even if all the information was there, it must be presented in a chronological order and not to allow the investor to request for clarification. The inclusion of pictures or other graphical presentations will be an added advantage but not too many to make the proposal bulky and difficult to follow. Most people including investors place a lot of value in the design and packaging of proposals, which they easily use to translate how trustworthy a business would be. Appropriate language and tone should also be used without over or under marketing one-self. If there are any useful references, it is best to include those instead of providing self praises within a proposal. Virtually, everything within the proposal can be supported by graphical presentations to make it easier for potential investors to understand. This is what usually stands out between a winning proposal and any other proposal. However, the presentations must be free from any errors that can easily be picked up. Usually investors analyse the proposals as teams of different expertise and professions and thus accountants will look out for faults in the figures, engineers will consider the

11.10 Conclusion

251

technical feasibility of the solution and so on. The fifth stage would be to proofread and edit to make sure that there are no grammatical or spelling errors that may put off investors. At this stage, it may be useful to get the assistance of expert proofreaders to ensure that the document was free of mistakes. Colleagues in different professions can also assist in checking for errors in figures, equations, drawings, etc. The last stage after proofreading is to submit the proposal. While it is normal practice to submit proposals electronically, it would be useful to carry out some background checks on the potential investors to find out what their preference would be. Some still prefer to receive the hardcopy submission, while others have gone paperless and prefer the electronic submissions. Whichever mode of submission, it is also imperative for researchers or innovators to ensure that the submission is of adequate length, contained clear figures, tables, pictures, etc. For hardcopy submissions, it is important to make sure that it is colour printed on an acceptable type of paper. Most modern investment companies or foreign aid agencies have developed submission portals on their websites to make it easier for applicants to submit their proposals. It is vital to follow the instructions diligently as some companies and organisations also use this as a way for screening and shortlisting applicants. Unless the submission has not been acknowledged, researchers can follow-up by e-mail, but unnecessary pressure on the potential investors should be avoided and allow them time to evaluate the proposal.

11.10  Conclusion Tertiary institutions around the world have not only been transforming in response to the demands for rapid and dynamic changes in technology brought on by the fourth Industrial Revolution, but have also gradually turned into entrepreneurial universities. This has been largely due to the dwindling resources for research grants from governments, industry and foreign aid agencies as well as global competition, thus the need to generate income within the institutions in order to sustain activities. The general trend by most institutions was to make use of established models such as the triple helix to attract funding from government and industry for incubating promising innovations to ultimately commercialise and in the process industrialise and create employment through start-ups and spin-offs. Researchers at universities were only willing to prove their worth through knowledge and technology transfer to industry and production through entrepreneurships. This chapter provided guidelines and tools to successfully commercialise research output by way of providing guidance for patenting to protect intellectual property rights as well as to appropriately package business proposals in order to attract funding from industry. The guidance was based on case studies drawn from the eight tertiary institutions offering engineering education from Mozambique, Namibia, South Africa and Zimbabwe under the Southern Africa Engineering Education Network (SAE2Net). All eight institutions under this partnership have established innovation centres in the form of innovation hubs, industrial parks and specialised centres of excellence

252

11  Commercialisation and Industrialisation: Research Prognosis for Academia…

that provide specialist services in different areas of engineering. Using interactive interviews and observations as well as the importance-performance analysis, the major challenges observed towards successful commercialisation and industrialisation in the region included lack of sufficient support from industry, hence these guidelines, and how to prepare winning proposals, high vacancy rates and low academic profiles, hence the emphasis for the partnerships and pooling of resources for development of staff to higher levels through doctoral training centres. Despite the proliferation of innovation hubs and specialist centres within the region, the number of original inventions and innovations still remained low and yet that remained one of the major drivers for commercialisation, hence the need for authorities to prioritise resources as well as creating policies that were not only conducive to attract financial support from industry and other sources, but also encouraged close relationship and collaboration of academia with industry.

References Gadallah, Y. (2010). Intellectual property policy for universities and research institutes and economic development – The Egyptian Case. International Review of Intellectual Property and Competition Law, 41(4). Goldratt, E. M., & Cox, J. (2014). The goal: A process of ongoing improvement (4th revised ed.). North River Press. ISBN-13: 9781622313945. Government of Zimbabwe. (2018). Transitional Stabilisation Program Reforms Agenda: October 2018-December 2020, Towards a prosperous and empowered upper midle income society by 2030. Harare: Government of Zimbabwe Printers. Available: https://www.tralac.org/documents/resources/by-­country/zimbabwe/2347-­zimbabwe-­transitional-­stabilisation-­programme-­ abridged-­version-­5-­october-­2018/file.html. Accessed 14 Dec 2020. Government of Zimbabwe. (2020). National Development Strategy 1: Towards a prosperous and empowered upper midle income society by 2030. Harare: Government of Zimbabwe Printers, Available: http://www.zimtreasury.gov.zw/index.php?option=com_phocadownload& view=category&download=335:national-­development-­strategy-­1-­2021-­2025&id=64:national-­ development-­strategy-­1&Itemid=789. Accessed 14 Dec 2020. Guerrero, M., Urbano, D., Alain, F., Klofsten, M., & Mian, S. (2016). Entrepreneurial universities: Emerging models in the new social and economic landscape. Small Business Economics, 47, 551–563. Jamil, F., Ismail, K., & Mahmood, N. (2015). A review of commercialization tools: University incubators and technology parks. International Journal of Economics and Financial Issues, 5(Special Issue), 223–228. Karjala, D., & Kiskis, M. (2011). Intellectual property within the university: The Lituanian and US Examples. Intellectual Economics, 1(9), 65–84. Katila, R., Chen, E. L., & Piezunka, H. (2012). All the right moves: How entrepreneurial firms compete effectively. Strategic Entrepreneurship, 6(2), 116–132. Lee, C., Lee, D., & Sho, M. (2020). Effect of efficient triple-helix collaboration on organizations based on their stage of growth. Journal of Engineering and Technology Management, 58(2020), 101604. Mascarenhas, C., Marques, C. S., Galvão, A. R., & Santos, G. (2017). Entrepreneurial university: Towards a better understanding of past trends and future directions. Journal of Enterprising Communities: People and Places in the Global Economy, 11(03), 316–338.

References

253

Muzira, D. R., & Bondai, B. M. (2020). Perception of Educators towards the Adoption of Education 5.0: A Case of a State University in Zimbabwe. East African Journal of Education and Social Sciences, 1(2), 43–53. Nuvolari, A. (2019). Understanding successive industrial revolutions: A “development block” approach. Environmental Innovation and Societal Transitions, 32(2019), 33–44. Pazos, D. R., López, S. F., González, L. O., & Sandiás, A. R. (2012). A resource-based view of university spin-off activity: New evidence from the Spanish case. European Journal of Business Management and Economics, 21(2012), 255–265. Roig-Tierno, N., Alcázar, J., & Ribeiro-Navarrete, S. (2015). Use of infrastructures to support innovative entrepreneurship and business growth. Journal of Business Research, 68(2015), 2290–2294. Sætre, A., Wiggins, J., Atkinson, O. T., & Atkinson, B. K. E. (2009). University Spin-OFFS as technology transfer: A comparative study among Norway, the United States, and Sweden. Comparative Technology Transfer and Society, 7(2), 115–145. Shanker, D. (2017). Academic entrepreneurship in India. Journal of Entrepreneurship and Management, 6(2), 9–19. Smith, S., Hamilton, M., & Fabian, K. (2020). Entrepreneurial drivers, barriers and enablers of computing students: Gendered perspectives from an Australian and UK university. Studies in Higher Education, 45(9), 1892–1905. Sooreh, L. K., Salamzadeh, A., Safarzadeh, H., & Salamzadeh, Y. (2011). Defining and measuring entrepreneurial universities: A study in Iranian context using importance-performance analysis and TOPSIS technique. Global Business and Management Research, 3(2), 182–199. UJ (University of Johannesburg). (2020). Institute for intelligent systems. University of Johannesburg. Available: https://www.uj.ac.za/faculties/febe/iis. Accessed: 16 Dec 2020. Warner, A. L., Chaudhary, A. K., & Lamm, A. J. (2016). Using importance-performance analysis to guide extension needsa ssessment. Journal of Extension, 54(6), Available: https://joe.org/ joe/2016december/pdf/JOE_v54_6a1.pdf. Accessed 20 Dec 2020. Williams, D. (2013). Chapter 10: Building a support infrastructure for technology-based businesses: What can emerging economies learn from the western experience? In R.  Oake, A. Groen, G. Cook, & P. van der Sijde (Eds.), New technology-based firms in the new millennium. Bingley: Emeral Group Publishing, ISBN: 978-1-78190-315-5.

Chapter 12

Modelling the ‘Bridge’: Research Verification and Validation

Abstract  Despite rapid and dynamic changes in technology and the disruptive but necessary innovations orchestrated by the fourth Industrial Revolution that required the production of goods and services in industry to be driven by technology and knowledge transfer from tertiary institutions, the gap between academia and industry remained wide. This has been attributed to several reasons including the shortages and mismatch of skills between those produced by universities and those required by industry. This book focuses on research carried out in Southern Africa to address these challenges using systems thinking modelling as detailed in the previous chapters. This is the penultimate chapter that integrates the various submodels to universally model the bridge between academia and industry under the broad categories of technology, training and policies. The case studies used in the book and indeed this chapter were derived from institutions and industries collaborating under the Southern Africa Engineering Education Network (SAE2Net). The various avenues proposed in the book were verified and validated for their usefulness and the impact they had on bringing industry closer to academia. Keywords  Bridge · Control and experimentation · Engineering skills development · Looping feedback · Sub-model · Systems integration · Systems thinking modelling · Technology transfer · UST model · Model validation · Model verification

12.1  Introduction The effective integration and bridging of the gap between academia and industry to cope with the demands for the fourth Industrial Revolution and preparation for the future Digital Ecosystem that has been predicted as the fifth Industrial Revolution © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_12

255

256

12  Modelling the ‘Bridge’: Research Verification and Validation

from 2030 are dependent on a number of factors, broadly categorised as technology, training and policies (Garbie 2017). Even though most industrialising economies are still battling to transition from the third to the fourth Industrial Revolutions, the world economies have become globalised to the extent that no country can afford to be left behind due to the intertwined relationships as well as the global competitiveness in terms of production of goods and services. Southern Africa is made up of mostly industrialising countries but these depended to a large extent on trade as well as marketing of their goods and services, not only for the domestic and regional markets but for the international markets as well. As such, it was imperative for them to keep in tandem with developments around the world in terms of provision and consumption of engineering services and technology. Although the factors for effectively bringing industry closer to academia were broadly classified as technology, training and policies for this research, there were several other factors such as the environment, political stability, geographical locations of the tertiary institutions and industry, as well as general macro-economic conditions. Effort was made to directly and indirectly link these peripheral factors, with good reason and justification, to the broad categories. These broad factors were derived from and based on years of research spanning from around 2011 to 2020 in Southern Africa, comprising nine institutions of higher learning and eleven industrial companies as well as selected professional and regulatory bodies, government ministries of higher education as policy-makers and foreign aid agencies. The general hypothesis for this research as outlined in the introduction to the book and the objective to narrow the gap between industry and academia were based on and derived from observations and interactive interviews with personnel from academia and industry as well as work done by other researchers in the past, and these were formulated as follows: H1  (Technology) Machine tools, the technologies driving them and methods of production played a vital role in ensuring that production was not interrupted by machine breakdowns and downtimes. The use of conventional machine tools and technologies have contributed negatively to efficiencies of operations, productivity and capacity utilisation, hence the need to modernise and migrate to the true fourth Industrial Revolution in order to cope with the demands for global competition (Paton et al. 2012). H2  (Training) Appropriate engineering skills and relevant training to cope with and meet the demands for the rapid and dynamic changes in technology were essential for the effective collaboration of industry and academia. Productivity, throughput and capacity utilisation in industry, coupled with competitiveness in the provision of goods and services, can only be enhanced by matching the skills that tertiary institutions produced to those required by industry (McGrath and Powell 2015). Shortages and mismatch of engineering skills were two of the major challenges in Southern Africa. H3  (Policies) Appropriate company policies and government statutory instruments towards professional development of human resources were critical for the survival

12.1 Introduction

257

of companies and improved tax revenues. Governments operated and survived largely from taxes generated from industry and industry’s continued operation was dependent on profits generated from production and provision of goods and services. As such, it was in the best interest of governments to provide sufficient support for human resources development and training for future drivers of industry in order to realise maximised tax revenues (Aviso et al. 2018). In the same vein, industry also needed to have appropriate policies that allowed not only for the development of their own personnel to drive their companies in order to generate profit but should also plough back to tertiary institutions to improve the future development of human resources. As outlined in the previous chapters, these three drivers and classifications cannot operate in isolation. Focussing on improving one without considering and improving the other two would not adequately address the challenges systematically, hence the need for an integrated systems thinking approach. This was the basis on which the previous chapters covered the findings from the nine tertiary institutions including the available training and skills developed, eleven industrial companies including their business operations and challenges, government ministries and departments including their policies and interventions in human resources development, professional engineering and regulatory bodies including their roles in professional ethics and accreditation of engineering curricula as well as research institutions and their roles in nurturing talent and proposition of innovations to commercialisation and entrepreneurship. The collaborations between academia and industry were consolidated and analysed under the Southern Africa Engineering Education Network (SAE2Net) case study. Chapter 2 provided an overview of the transformations that industry has experienced and how these have impacted the development of skills at tertiary institutions and their applications in industry followed by outlining the theory behind systems thinking in Chap. 3 and the foundation for the development of the systems thinking sub-models that were integrated in this chapter to build the bridge between academia and industry. Chapters 4 and 5 focused on the collaborations between academia and industry in Southern Africa, their outcomes and impact, as well as the now popularised secondment of engineering academics to industry and the demonstration of the importance of problem- and industry-based learning, coupled with responses by academia to the sustainable development goals. Chapter 6 provided five case studies in the form of mini-projects carried out by academics on secondment in manufacturing, mining and mineral processing, foundry and general engineering. These case studies included the methodologies and results as a demonstration of the usefulness of academia input in the provision of solutions to industry challenges and improving industrial operations. The findings up to Chap. 6 culminated in the input to Chaps. 7, 8, 9, 10 and 11 on how capacity can be built and enhanced for sustainability, in both industry and academia, how the secondments to industry were used by academics to access modern equipment and technology, thereby improving the matching of skills required by industry. The partnership of the nine institutions under SAE2Net provided a

258

12  Modelling the ‘Bridge’: Research Verification and Validation

platform for cooperation in sharing resources and industrial engagements while they were expected to compete against each other for the purposes of research grants, students and global rankings, thus coopetition, mostly virtual as a result of the travel restrictions due to the COVID-19 pandemic. The link between industry and academia was also emphasised in academia business incubations, commercialisation and ultimately industrialisation and entrepreneurship. This chapter provides a consolidation of these various avenues to narrow the gap between industry and academia. Approaches such as the Triple Helix model have been adopted by many countries to enhance the interactions among academia, industry and governments (Lee et al. 2020). While this has been a useful strategy, it has been limited to specific relationships among the three, whereas the previous chapters have identified various other peripheral factors and gaps that would probably be best accomplished by a holistic approach that integrated all stakeholders, their purposes and functions using systems thinking methodology. The gaps from the Triple Helix model, as identified and utilised in this research, included professional institutions for engineers, regulatory bodies for quality control and accreditation of qualifications, research and scientific organisations that may be privately owned or parastatals of governments. The systems thinking methodology employed the theory of reductionism from each broad category through the different identified gaps, leading to the Universal Systems Thinking (UST) model followed by verification and validation of the models. The list of symbols and nomenclature used in the models developed in this chapter and their meanings are provided in the List of Symbols and Nomenclature. For all three sub-models, the mapping and grouping of elements were verified, validated, tested, controlled and adjusted using a looping mechanism of the interventions for improvements and sustainability.

12.2  Equipment and Technology The rapid and dynamic changes in the fourth Industrial Revolution that included artificial intelligence (AI), computer numerical control (CNC), machine learning and robotics have brought a new world order to engineering and manufacturing. Machine tools have become increasingly complex and so have engineering, production and processing methods, all driven by engineers. This has no doubt made equipment and technology the most critical of the three categories. As outlined in Chap. 8, industry has been forced to move in tandem with changes in technology, not only for the need to cope with the rapid changes but that old and conventional machines have also been rapidly phased out by industry. This has impacted academia, in that the skills developed at tertiary institutions needed to match those required by industry. Unfortunately, due to limited grants from governments, the equipment used in the training of future engineers to drive industry, have not been replenished in tandem with what is available in industry, resulting in the mismatch of skills and the

12.2  Equipment and Technology

259

costly requirement of retraining by industry. Industry had no choice in this regard because they required appropriately skilled engineers to drive industry and generate the much-needed profit, hence the need for close ties with academia. This can be accomplished in a number of ways; industry support for the acquisition or access to modern equipment by academia and engineering students, secondments and attachments, smart procurement use and maintenance of equipment through the phenomenon of Build-Operate-Transfer etc. Even with the ready access to local industries, another challenge was that most of the companies, particularly in Southern Africa had also not moved in tandem with the dynamic changes in technology where those still using old and conventional equipment faced the challenge of accessing spares for the equipment as Original Equipment Manufacturers (OEMs) no longer supported the phased out equipment in terms of spares and the software technology that may be required to drive them. Except for the platinum mining and processing company in Zimbabwe, which was adequately capitalised and fully automated with modern comminution and flotation, drying and smelting equipment and technology, the rest of the companies relied on old and conventional equipment. This implied that companies within the same environment could in fact have these disparities, hence the need for the future engineers to be appropriately trained for the equipment and technologies they were expected to use in industry. The platinum mining and processing company was presumably well capitalised because of its links with sister and parent companies in South Africa and Australia, hence the further need for regional and international collaborations of both industry and academia. The rest of the companies relied heavily on equipment that was at least 10 years old which frequently broke down, resulting in unacceptable downtimes. A few cases such as the foundry and general engineering company installed a CNC continuous casting machine (CCM). Obviously, with such isolated developments, it also meant that the training and access to these machine tools by academics and students had to be done in a similar fashion to avoid over- or underskilling. Except for the semi-industrialised South Africa, the machine tools used by institutions under SAE2Net were on average above 15 years old, much older than the average age of the equipment used by most industries. In developing the systems thinking sub-model for Equipment and Technology (ET), the data and information were mainly derived from the case studies outlined in Chap. 6 that included modelling, simulation and optimisation as well as redesign and control of backtracking in process flows at the selected companies in manufacturing, mining and mineral processing, as well as foundry and general engineering. In addition, information was also derived from Chap. 8 on the access to industry and appropriate equipment by academics on secondment, the interventions by industry in the provision of vital equipment for engineering laboratories and the smart procurement, use and maintenance of engineering and laboratory equipment for tertiary institutions using the BOT principle. The systems thinking elements used in the ET model included the techniques employed, such as the use of machine distance matrices derived from group technology and the redesign and layout of the processing plants and process flows for efficient processing and manufacturing in

260

Foundry/General Engineering Mining/Mineral Processing Manufacturing

12  Modelling the ‘Bridge’: Research Verification and Validation Planning Scheduling Modelling

Foundry Casting & Fettling, Machining Comminution & Flotation, Furniture Production,

Production

Automation, CNC, AI & Robots Flexible Manufacturing, CAD/CAM/CIM, Lean Production

Manufacture

Design

Machine Distance Matrices, Functional Grouping, Process Mapping, Technology Transfer, Optimisation, BOT, PPP, Smart Procurement

Control and Experimentat ion

Outdated Technology Breakdowns Downtimes/Delays in Production Backtracking Power outages

Minimal Waste Enhanced Productivity, Efficiency & Throughput Maximised Capacity Utilisation

Simulation

Conclusions, Decision Making, Recommendations

Fig. 12.1  Equipment and technology (ET) systems thinking sub-model

the process of developing appropriate solutions, while the constraints were those challenges encountered which had to be controlled regularly in order to achieve the desired outcome. The function and output of the ET sub-model were the results obtained such as productivity, efficiency and capacity utilisation. A representation of the ET systems thinking sub-model is shown in Fig. 12.1. The various elements of the model were taken as the manufacturing, mining and mineral processing, foundry and general engineering businesses of the case studies as provided in Chap. 6, but the systems thinking elements utilised for this research and for this ET sub-model were the specific processes such as comminution and flotation in mineral processing, casting and fettling, furniture production and general machining. These activities and processes can be achieved efficiently through the use of appropriate tools and methods of production such as flexible manufacturing systems, group technology, automation, automated guided vehicles (AGVs), robots, machine learning and AI. The various machines and processes can also be driven by appropriate software and technology such as computer-aided engineering tools: CIM, CAD and CAM with appropriate software such as AutoCAD, MasterCAM. In addition, simulation packages such as Arena and Limn Flowsheet Processor that were used in the comminution and flotation of platinum case study were used to model and optimise the processes electronically in order to predict performance or detect bottlenecks in the process flows. All these were meant to achieve efficient operations, lean production and appropriate waste management techniques such as in fettling. The results obtained using Arena and Limn Flowsheet Processor simulations confirmed the challenges faced by the companies such as frequent machine

12.2  Equipment and Technology

261

breakdowns which resulted in production delays and thus increased lead times and reduced throughput. Crisscrossing of process paths and backtracking contributed to increased operational costs and power consumption. Power outages and load shedding experienced by most countries in Southern Africa also contributed negatively resulting in loss of production or employees forced to work night shifts when power was available. Capacity utilisation was also not only affected by the frequent breakdowns but also the lack of appropriate expertise and skills which in some cases led to the underutilisation of equipment and failure to maintain the equipment appropriately, worsened by the shortages of spare parts. Apart from the failure to acquire modern equipment, the challenges were resolved to some extent by employing modelling, simulation and optimisation as shown in Fig.  12.1 to improve the efficiency of operations through the control and experimentation feedback loops that continually improved processes. In the manufacturing and production of furniture, machine distance matrices were utilised to reorganise the plant layouts and positions of workstations based on the group technology theory in order to maintain one-directional flow of raw materials, parts and sub-assemblies in order to reduce backtracking of process paths. Group technology was employed for mapping processes to position workstations according to the functions they performed in such a way that parts and sub-­ assemblies followed a uniform path from stores through the various stages of processing to sales ready for dispatch to customers. For the platinum mining and processing company, alternative comminution and flotation circuits were compared using Arena and Limn Flowsheet Processor in order to derive the most optimal configuration, even though the company was fully automated in almost all departments in terms of power consumption and value for money in processing. Thus, the use HPGR and bigger rougher cells resulted in maximised throughput, improved mineral recovery and reduced energy consumption in platinum production. The optimised configurations for comminution and flotation in platinum processing, reorganised plant layouts and process flows and automated fettling etc. at the case study companies resulted in improved waste management, enhanced productivity and throughput, as well as maximised capacity utilisation. These positive results were a clear demonstration of the usefulness of the academia input to provision of services and solutions to industry challenges. In addition, the secondments of academics to industry and attachment of students enabled access to modern or appropriate equipment in industry for training and thus developing appropriate skills to drive industry in future. While there were disparities between the countries and industries within the partnership, in terms of coping with the demands for the fourth Industrial Revolution and level of technologies in the machine tools available, the collaborations were useful to draw on synergies and benchmark operations, albeit virtually. Part of the agreement for SAE2Net called for the virtual access to technology and equipment in order to empower academics in terms of transfer of technology and knowledge from academia to industry as well as among the collaborating tertiary institutions.

262

12  Modelling the ‘Bridge’: Research Verification and Validation

12.3  Skills Development and Training Evidently, from the ET systems thinking sub-model, the words, skills and training were mentioned several times, making them an essential aspect of the UST model, hence the development of the systems thinking sub-model for Skills Development and Training (SDT). As hypothesised earlier (H2), without the appropriate skills and training, machine tools cannot be appropriately and gainfully operated, let alone cope with the demands for new technologies for industry to produce and generate profit competitively. The lack of appropriate skills and requisite expertise to drive systems in industry was identified as one of the major challenges and in fact, the shortages and mismatch of skills between what tertiary institutions produced and what industry needed, were the major motivation for this research and the desire to bridge the gap between academia and industry in order to reduce the mismatches and shortages. The mismatches of skills were a result of the mismatches of equipment used in training and equipment and technology in industry. This forced industry to invest in the training of fresh graduate engineers to cope with the type of equipment and technology they had. The development of the SDT systems thinking sub-model was derived from information outlined in Chaps. 4, 5 and 7 on collaborations with industry through attachments and secondments, problem- and industry-based learning as well as capacity building for both academia and industry. In addition, data was also derived from seminars and continuous professional development courses organised by the tertiary institutions for practising engineers in industry. The systems thinking elements for the SDT sub-model were derived from the specific training disciplines for engineering education but for the purposes of this study and the ultimate development of the UST model, the following disciplines were used as they had a direct influence on the foregone ET sub-model: Process, Design, Industrial, Mechanical and Production or Manufacturing Engineering. The specific elements thus included the ability to design, schedule or plan production using appropriate high-tech tools such as CAD, CAM and simulation. The systems thinking elements for representation in the SDT model included modelling, simulation, software tools such as Arena, Limn Flowsheet Processor, MasterCAM, SolidWorks and AutoCAD, R&D projects in line with expected skills and expertise. The major common challenges observed and extracted from the interactions through knowledge-sharing workshops with the regional tertiary institutions included obsolete and outdated equipment and technology in most of the institutions’ engineering laboratories as outlined in Chap. 8. The mismatch of skills and failure to access modern equipment and technology not only resulted in tertiary institutions producing unemployable graduates due to the inadequacies in training but also meant additional costs for industry to retrain the graduates. Through control and experimentation of different alternatives as shown on the SDT systems thinking sub-model in Fig. 12.2, several strategies which produced positive results were adopted. Secondments of engineering academics throughout

263

12.3 Skills Development and Training

Mechanical, Process, Design, Industrial or Production Manufacturing Engineering

Engineering Education

Designing, Production Scheduling, Planning, Tools and Techniques, Industrial & Systems Engineering & Analysis

Specialised Training: coE

Modelling, Simulation, R&D projects, Software Development, CAD/CAM/CIM Expertise, Product Development, Business Incubation PBL & IBL Projects

Feedback

Feedback Industrial Attachments and Secondments, Professorial Chairs, Adjunct Professors. Various CPDs and Doctoral Training Centres (DTC) Innovations

Control and Experimentat Mismatch and ion shortage of Skills, Lack of Access to Modern Technology for Training, Inadequate Experience High Staff Turnover

Entrepreneurship, R&D Projects, Expertise, Access to Modern Technology, Consultancy, Capacity Building, Spin-off Companies

Simulation

Conclusions, Decision Making, Recommendations

Fig. 12.2  Skills Development and Training (SDT) systems thinking sub-model

the region and attachment of students to industry have become part and parcel of the routine and curricula, respectively, for tertiary institutions. Both interventions were established to empower engineering academics through access to modern equipment and technology or at the least, whatever equipment was available in industry so that appropriate and relevant skills were imparted to engineering students, the future drivers for industry. In addition, most of the institutions had very low levels of highly qualified academics, hence this was also an opportunity to upskill the academics and instil some confidence in their delivery of lecturing duties. Engineering students who were fortunate enough to be attached to industry were probably the biggest beneficiaries of this intervention, in that the exposure to industrial operations not only enhanced their understanding of theory but it also allowed them the opportunity to identify industry challenges that they then used as their projects through problem- and industry-based learning. Such attachments created opportunities for employment for these students, as long as they demonstrated their worth during the attachments. On the other hand, the secondments also created consultancy opportunities for engineering academics. The resultant collaborations created platforms for business incubations of promising innovations, entrepreneurships, appropriate expertise, capacities as well as possibilities for spin-off companies, thereby strengthening the links between academia and industry. Regional collaborations can be enhanced through Doctoral Training Centres and Centres of Excellence for specialised training and pooling of resources as detailed in Chap. 7.

264

12  Modelling the ‘Bridge’: Research Verification and Validation

12.4  Professional Development Policies Equally important in the systems integration were the company and statutory policies that made the foregone interventions of ET and SDT possible, hence the need to amalgamate them as hypothesised in the introduction and earlier in this chapter that in the absence of appropriate legislation or company and statutory policies, ET and SDT remained pipedreams (H3). This was the basis on which the Professional Development Policies (PDP) systems thinking sub-model was developed. Human resources policies that span from professional development of academics at tertiary institutions, provision of adequate support and grants by governments for human resources development and sustenance of operations at tertiary institutions, as well as continuous professional development and other industry policies in this regard, were all critical and closely linked to ET and SDT. The continued operation of organisations, whether industry or academia, and their sustainability largely depended on how much importance, priorities and emphasis were placed on the development of their human resources (Perez-Foguet et al. 2018). Although the training and development of human resources of a country rested directly with tertiary institutions, they did not have resources of their own to be able to sustain the activities around the various training programmes. Most tertiary institutions in Southern Africa are owned 100% by their governments who in turn provided the support required to fund the institutions in order to develop the human resources required. The grants from governments to tertiary institutions were from fiscal allocations derived from taxes. Before the global financial crisis of 2008 that led to recession in most parts of Southern Africa, most governments provided enough support for all students in terms of upkeep and tuition fees. However, in recent years, the amounts allocated for higher education have been dwindling and yet the number of students have been increasing steadily. This has forced most governments to ask students to provide for their own upkeep and tuition, leading to endless demonstrations in the region, such as the one dubbed ‘Fees must fall’ in South Africa. While, industry has provided their contributions through the normal taxation as well as the specific manpower development levies, a lot could still be done as they are the biggest beneficiaries of well-developed human resources. Hence, the responsibility for developing human resources and ensuring that adequate and appropriate skills were churned out to industry became a triple helix format: tertiary institutions providing the direct development, government and industry providing the financial support. None of the three can operate without the input from the other two. Such legislation and statutory instruments such as the Zimbabwe Manpower Development Act (Government of Zimbabwe 1995), university statutes and company policies for CPDs were essential and formed the systems thinking elements for the PDP sub-­ model as shown in Fig. 12.3. The implementation of these policies and legislation can be achieved through various instruments such as industrial attachments for students and secondments of engineering academics to expose them to industrial operations, equipment and

12.4  Professional Development Policies Continuous Professional Development, Company and Statutory Policies

Implementation

Feedback

265 Industrial Attachments & Secondments, Manpower Development Act, Engineers’ Legislation, Registration & Accreditation, Enforcement of Legislation

Control and Experimentation Inadequate Regional Funding, Minimal Collaborations, Government Industry-Academia Support, Failure Links, Cooperation to honour Training Partners, Levies, Migration Enforcement of Levies of Engineers, Coopetition Shortage of SAE2Net Expertise Self-sustenance, Capacity Building, Commercialisation, Entrepreneurship, Industrialisation, Innovations R&D Projects, Expertise, Sustainability, Scholarly Publications

Simulation on

Conclusions, Decision Making, Recommendations

Fig. 12.3  Professional development policies (PDP) systems thinking sub-model

technologies, legislation such as the manpower development acts, annual registration and accreditation of engineers for ease of mobility within the region as well as the enforcement of such legislation or levies to develop human resources. The major challenges established from the research as outline in earlier chapters was the inadequate support in terms of grants from governments, although these differed from country to country in Southern Africa. While it was evident that the skills deficit in engineering was above 90% for Zimbabwe, in the worst standing, naturally this called for increasing the number of students at tertiary institutions. However, this was not possible without adequate infrastructure. Other challenges included the mismanagement of the manpower development levies in Zimbabwe, South Africa and Mauritius, as outlined in Chap. 7. This had the negative effect of influencing industry to stop contributions to the development levies. The shortages of skills and expertise continued in most of the countries as skilled engineers preferred to seek employment abroad because of better opportunities and remuneration. There was also noticeable migration of engineers within the region, moving away from the poorly performing economies to those that were doing well. Although such mobility of engineers was encouraged for the smooth transfer of knowledge and technology, in Southern Africa, the migration was tilted towards countries such as South Africa, Botswana and Namibia. This further strained industries in countries that were left void but the general effect on all the countries was high staff turnover, not conducive for continuity of research and innovations in academia. Through this research and the regional collaborations of institutions and industry under SAE2Net, a number of initiatives were adopted and policy-makers were also persuaded to intervene. The agreement by nine institutions to establish a network in

266

12  Modelling the ‘Bridge’: Research Verification and Validation

engineering education was a deliberate move to address these challenges through Doctoral Training Centres (DTC) and Centres of Excellence (CoE) for specialised training and sharing and pooling of human and material resources, a coordinated secondment programme for engineering academics within the region in order to add value to their skills through experiencing industrial operations in different environments. The other main objective for SAE2Net was to satisfy the requirements for successful academics in the ability to innovate, research and produce scholarly publications apart from teaching. This was accomplished through regional research and collaborations, leading to joint publications. While acknowledging that the support from governments for research grants continued to decline, it was imperative for engineering academics to attract funding from industry or other sources through applications for commercialisation or research grants. In view of the low uptake of such initiatives by regional industries, it left the option to apply for grants from foreign aid agencies such as the several grants that supported this research from Sida’s NUSESA and the Royal Academy of Engineering’s EEEP and HEP SSA. These grants have enhanced the development of the engineering profession in Southern Africa, in terms of quality of graduates and programmes as well as building capacity for self-sustenance. Essentially, such grants should be used as seed funds to generate more through commercialisation of innovative projects or royalties from services provided.

12.5  Integrated Universal Systems Thinking Model The challenges identified for Southern Africa throughout the research and isolated in each of the sub-models that have just been developed included: outdated technology, frequent machine breakdowns in industry, downtimes and delays in production leading to long lead times, backtracking and crisscrossing of process paths and frequent power outages under the ET sub-model, mismatch and shortage of skills, lack of access to modern technology and equipment for Training, inadequate experience and high staff turnover under the SDT sub-model and inadequate funding, minimal government support, failure to honour human resources development levies, migration of engineers and shortage of expertise under the PDP sub-model. Several solutions were proposed for the isolated islands of systems thinking sub-models through a looping feedback, control and experimentation of the proposed interventions, most of which have benefitted the institutions. However, resolving these issues in the isolated manner would not produce the desired long-term results, suggesting that a more comprehensive and holistic approach was necessary to realise a complete bridging of the gap between academia and industry using a systems thinking integration of the ET, SDT and PDP sub-models. The systems thinking integration was derived from the three hypothesis as outlined earlier and based on the conundrums that a fresh engineering graduate without relevant skills as well as exposure to appropriate industrial operations and equipment was unemployable unless further training was administered and skills acquired,

267

12.5  Integrated Universal Systems Thinking Model

Skills

Government

+

Legislations

+ Coopetiti on Centres of Excellence

Research Institutions

Doctoral Training Centres

SDT

+

-

PDP R

Equipment

Grants

CPD Policies

ET

+

Academia +

Regulatory Bodies

BOT Agreements

R Knowledge Transfer

& Levies

-

Industry

B Problem and Industry Based Learning

Knowledge Transfer

R

+

Accreditation Professional & Ethics Bodies

+

Standards +

R Research

+ Grants

Fig. 12.4  Conceptualised universal systems thinking (UST) model of the ‘Bridge’

while a fully capitalised and automated industrial operation without the required engineering skills and expertise to drive the operations or lack of appropriate human resources development policies would likely suffer from reduced productivity and low capacity utilisation. Furthermore, well-documented statutory instruments, legislation and company policies for CPDs and human resources development without appropriately skilled engineers and support base would not sustain competitive operations and meet the demands for today’s competitive and dynamic globalised societies. Figure 12.4 shows the consolidation of the integration of the three sub-models, ET, SDT and PDP through various avenues, anchored by the systems thinking elements and the key stakeholders necessary for bridging the gap between academia and industry, that is, Governments, Industry and Academia in a structure similar to the Triple Helix format, strengthened by Research Institutions, Professional and Regulatory Bodies for the ultimate development of quality graduates with appropriate skills to drive industry. Unlike the previous systems thinking models developed in earlier chapters or the three sub-models developed earlier in this chapter, the UST model consisted of

268

12  Modelling the ‘Bridge’: Research Verification and Validation

flexible or loose links among the three primary sub-models. The flexible interconnections were an indication that these were not permanent connections but were optional in the three sub-models, ET, SDT and PDP, which can still remain functional and operate in isolation, although it would be more ideal for the connections to remain loosely connected. These can be visualised like cogs in a gearwheel, where if one of the cogs broke, the gearwheel continued to run, albeit at reduced performance from one that has all its cogs. The links were thus formulated to ensure that if something went wrong in one of the sub-models, the entire model or system still continued to function reasonably in such a way that it did not affect the rest of the system. The interconnections of the three sub-models, coupled with the control and experimentation as outlined in the individual sub-models, were thus expected to produce a robust model with enhanced output. The flexible links were also premised out of ramifications and learning based on the results of secondments of engineering academics to industry, collaborations among the tertiary institutions and the overall interactions with industry. The flexible link between ET (techniques such as production planning, scheduling and modelling) and that of SDT (specialised training including CPDs) represented the direct interchange between academia and industry, exemplified by the simulation models developed by academics from their lecture room experience to provide solutions that improved productivity, capacity utilisation and efficiencies of operations. On the other hand, the interchange between SDT and PDP (legislations, manpower development acts and licencing of engineers) represented the involvement of both industry and government in the development of human resources, including the adoption of industrial attachments and secondments of academics to industry as well as occasional involvement of practising engineers to offer specialised training at tertiary institutions, as Adjunct Professors. The control, experimentation and adjustment of the outcomes were enhanced by the various strategies that were adopted in each of the models through a cocktail of novel techniques that included machine distance matrices, product development, incubation of promising innovations as well as regional collaborations and joint research. As shown in Fig.  12.4, most of the links between various stakeholders were understandably positive reinforcing loops as the interactions between these stakeholders were reinforced in either directions, for instance, the more support provided by industry in terms of equipment and grants, the more knowledge and technology can be transferred to industry. Likewise, the more governments supported tertiary institutions through required grants, the more skills were developed and knowledge transferred through the government-controlled research institutions. However, there was a negative balancing loop between industry and academia, in that the support from industry such as Professorial Chair was balanced by the provision of services to industry by academia. The outcomes of the UST model were a combinations of control, experimentation and adjustments for improvements in the three sub-models, ET, SDT and PDP, through the interconnections and exchanges which also created opportunities for academics to generate problem- and industry-based projects for students, further enhancing the relevance and appropriateness of the training and subsequent skills

12.6  Model Verification and Validation

269

imparted to students. In addition, these secondments and provision of solutions to industry also created opportunities for consultancy projects for the engineering academics, not necessarily at the same companies but at other industrial operations with the same business objectives and operations. In doing so, the engineering academics also accessed the modern or appropriate equipment in industry to enhance their exposure in order to boost their confidence in lecturing as well as boosting their own experience as most institutions in Southern Africa were manned by young and inexperienced academics. Opportunities for start-ups, spin-offs and entrepreneurships were created to boost the academics’ portfolios as well as enhancing their institutions’ wealth and competitiveness.

12.6  Model Verification and Validation Several models, both simulation and systems thinking, were generated during the course of this research. These were individually verified to determine that the model representation and the associated information represented the conceptual descriptions and specifications accurately from the data used, as detailed in the previous chapters. In addition, the models, based on the information and data used, were also validated to determine the level to which they were an accurate representation of the real systems through the case studies and collaboration of tertiary institutions and industry in Sothern Africa. The models developed throughout the research culminated in the UST conceptual model. The verification process, answering whether the models built were right (Kim et al. 2015), focused on the iterative comparison of the systems thinking elements with what they were supposed to perform and achieve. On the other hand, the validation process probed whether the right models were built and this focused on the matching of the observed behaviour of the systems thinking elements with the corresponding elements of the developed models of the system and establishing whether the differences were acceptable in view of the functions designed for the models to perform. Where the desired output was not achieved, the looping feedback was employed, to control, adjust and further experiment until the output matched with the desired outcome or behaviour of the actual system. Since qualitative analysis was employed in most of the cases, the behaviour of the models was benchmarked against those for tertiary institutions from the industrialised world such as the University of Leicester, the UK partner in the SAE2Net partnership and academia – industry collaborations from that part of world. While the validation and verification of the models developed at the various companies was an ongoing process as detailed in the case studies in Chap. 6 and the other systems thinking models contained in the other chapters, this section focusses on the qualitative verification and validation of the ET, SDT and PDP sub-models, as well as the UST conceptual model. The verification process involved the testing of specific attributes developed for each of the sub-models, influenced by the aims and objectives to narrow the gap between academia and industry. The validation

270

12  Modelling the ‘Bridge’: Research Verification and Validation

process was aimed at demonstrating that the three sub-models were reasonable replicas of the real systems that existed between academia and industry in Southern Africa, through determining whether it produced the behaviour with enough accuracy to satisfy the objectives of bridging the gap between industry and academia. The validation was hinged on the hypothetical conundrums as outlined earlier in this chapter. The combination of input parameter values and the outcomes and conclusions from the performance were the systems thinking elements as shown in Figs. 12.1 to 12.4. The constraints and challenges that were employed to test, control and adjust performance of the models were extracted from interactive observations, interviews, as well as the performance of the initiatives under the schemes such as NUSESA, EEEP and HEP SSA. These were shown in red in the three sub-­ models. The verification of the models was aimed at ensuring that the ET, SDT and PDP sub-models and the eventual UST conceptual model performed as expected by closely observing and monitoring specific measurements such as throughput, productivity, capacity utilisation, efficiency, relevance of skills produced, level of support from industry and governments, as well as level of dependence on foreign aid. Initially, validation of the sub-models focussed on the outputs for each model such as machine distance matrices and functional groups to address the issues of low productivity and capacity utilisation in industry (ET sub-model on Fig. 12.1), secondment of academics and attachment of students to industry in order to access appropriate/modern equipment in industry for the purposes of imparting appropriate skills to students, thus resolving the mismatch of skills challenge (SDT submodel on Fig. 12.2). The sharing of equipment through collaborations with other institutions, as well as with industry, was meant to address the issues of scarcity of funding from industry and the dwindling grants from governments (PDP sub-model on Fig. 12.3). These processes also required expert intuition as well as the impact measured and derived throughout the research. The research was thus a combination of quantitative analysis (modelling, simulation and optimisation of industry processes) as well as qualitative analysis (systems thinking integration of the ET, SDT and PDP models). However, it was largely inductive, in which case the validity of the models meant that they were guided by specific expectations and outcomes in terms of the performance measurements, as well as the supporting evidence in terms of the actual results obtained and the contributions and impact of these models for the real systems. The qualitative aspect and validity of these models were also dependent upon and based on the strength of the results obtained and the impact of the models in real practice such as the groundwater enterprise model detailed in the next chapter as a possible spin-off. The research also employed an innovative and novel approach to verify, validate and test the sub-models and the eventual UST model through mapping and grouping of the systems thinking elements, while controlling and adjusting them where necessary by utilising innovative techniques such as machine distance matrices, functional groups, secondments, regional integration and collaborations, as well as pooling and sharing of resources among the tertiary institutions, also expected to be in coopetition with each other. The flexible links introduced in the

References

271

integration of the sub-models and the eventual development of the UST model enhanced the flexibility with which the sub-models can actually perform in isolation but ideally in unison.

12.7  Conclusion The demands for the rapid and dynamic changes in technology required close links and collaborations between academia and industry. While several initiatives have been employed to narrow the gap between the two, in response to the demands of the fourth Industrial Revolution and in preparation for the Digital Ecosystem in the provision of goods and services, engineers played a critical role in driving the technologies and transfer of knowledge and technology from academia to industry. This has largely been achieved in the industrialised world, but a lot still needed to be done in industrialising countries such as those in Sub-Saharan Africa. This chapter was the penultimate modelling and integration of the technology, training and policies sub-models developed throughout the book to the conceptual UST model, based on the case studies, data and information gathered over the years in Sub-­ Saharan Africa under the Southern Africa Engineering Education Network (SAE2Net). While solutions were obtained from the sub-models, verified and validated, these could not be left to operate in isolation but in unison by way of introducing flexible links within the integrated UST model. The smooth functioning of the UST model depended on the provision of adequate resources from regional governments and industry while foreign aid agencies played a supporting role in providing seed funds for the initiatives. The UST model, a reasonable representation of the real system, was premised on the need to resolve the challenges hypothesised that for industry to operate sustainably, their systems must be driven by appropriate skills, a shared responsibility among tertiary institutions, industry and governments with support from research institutions, professional and regulatory bodies, using systems thinking. The models were verified and validated through a looping feedback to control and adjust the system elements for desirable outcomes to bridge the gap between industry and academia.

References Aviso, K. B., Mayol, A. P., Promentilla, M. A. B., Santos, J. R., Tan, R. R., Ubando, A. T., & Yu, K.  D. S. (2018). Allocating human resources in organizations operating under crisis conditions: A fuzzy input-output optimization modeling framework. Resources Conservation and Recycling, 128(2018), 250–258. Garbie, I. (2017). Identifying challenges facing manufacturing enterprises toward implementing sustainability in newly industrialized countries. Journal of Manufacturing Technology Management, 28(7), 928–960.

272

12  Modelling the ‘Bridge’: Research Verification and Validation

Government of Zimbabwe. (1995). Manpower Planning and Development Act Chapter 28:02. Harare: Government of Zimbabwe Printers https://zimlii.org/zw/legislation/num-­act/1994/24/ Manpower%20Planning%20and%20Development%20Act.pdf. Accessed 24 Dec 2020. Kim, J.  H., Jeong, S., Oh, S., & Jang, Y.  J. (2015). Verification, Validation, and Accreditation (VV&A) considering military and defense characteristics. Industrial Engineering & Management Systems, 14(1), 88–93. Lee, C., Lee, D., & Sho, M. (2020). Effect of efficient triple-helix collaboration on organizations based on their stage of growth. Journal of Engineering and Technology Management, 58(2020), 101604. McGrath, S., & Powell, L. (2015). Skills for sustainable development: Transforming vocational education and training beyond 2015. International Journal of Educational Development, 50(2016), 12–19. Paton, R. A., Wagner, R., & MacIntosh, R. (2012). Engineering education and performance: The German machinery and equipment sector. International Journal of Operations & Production Management, 32(7), 796–828. Perez-Foguet, A., Lazzarini, B., Gine, R., Velo, E., Boni, A., Sierra, M., Zolezzi, G., & Trimingham, R. (2018). Promoting sustainable human development in engineering: Assessment of online courses within continuing professional development strategies. Journal of Cleaner Production, 172(2018), 4286–4302.

Chapter 13

Challenges and Opportunities: Discussion and Predictions from Research Findings

Abstract  The research on bridging the gap between academia and industry in Southern Africa in collaboration with UK institutions was executed during the decade spanning from 2010 to 2020, a period in which many challenges such as the aftermath of the global financial crisis and the COVID-19 pandemic were witnessed. This was coupled with rapid changes in technology in line with the fourth Industrial Revolution. This research focused on addressing shortages and mismatches of engineering skills in the region. The engineering profession was probably the most affected by these world pandemics as well as the need to develop appropriate technologies and generate solutions for industry in tandem with the rest of the world. This chapter focusses on how these challenges were resolved and at best turned into opportunities based on the research findings, dictations and predictions for the future stability and sustainability of the links between industry and academia, as well as the limitations of the proposed solutions. Keywords  Challenges · Community service · Constraints · Control and experimentation enterprise model · Limitations · Opportunities · Pracademics · Predictions · Spin-off activities

13.1  Introduction A story has been told that many people were forced to work from home in quarantine because of the Bubonic plague of 1665. This included the famous scientist and physicist, Sir Isaac Newton who is believed to have referred to this period as ‘the most productive period of his time’ that saw him develop theories on calculus, optics and gravity (Ott 2020). This was probably one of the best examples of how challenges were turned into opportunities. The COVID-19 pandemic has similarly © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_13

273

274

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

ravaged throughout the world and has affected millions of people, especially in 2020, with reported mutations of the virus and the emergence of a virus variant (Ray and Srivastava 2020; World Bank 2020). While this pandemic has created many challenges, it has also opened up opportunities for engineers to create technologies to cope with the pandemic through the new normal such as online learning and virtual laboratories and collaborations, as the adage goes, ‘Crisis breeds opportunity’. The effects of the global financial crisis of 2008 continue to be felt around the world. Although this was not expected to significantly affect industrialising regions such as Southern Africa, because of the limited trade with the industrialised world, it turned out that the region was probably one of the worst affected due to their heavy reliance and dependence on foreign aid (Bakrania and Lucas 2009). Adjusting to the new normal and routines of doing business differently has not been easy but it has certainly created opportunities to the more enterprising and innovative inventors, software developers, technologists and engineers. With increased global competition, implementation of the fourth Industrial Revolution, preparation for the Digital Ecosystem and the ravaging pandemic, people ought to organise their daily routines differently by thinking outside the box and change their paradigms. While vaccines have been developed and are being administered to people in the developed world, this may take some time before the same medications were availed to the developing regions such as Southern Africa, let alone to prove that the vaccines are indeed effective. The routine of going to the offices, social gatherings, etc. has to change in the short term and the time saved from these events or routines can be utilised for other more important and rewarding tasks such as what Sir Isaac Newton did. Many universities around the world including those in the SAE2Net collaboration have already adjusted their mode of teaching to online and virtual sessions. The biggest challenge in this regard was for scientists and engineers to develop technologies that can help to cope with these changes, but more challenging is the need to carry out practical sessions and laboratory work. One of the major observations during this research in Southern Africa in comparison to the UK was not only the lack of access to modern equipment and technology by engineering academics but the capacity to use and maintain what was available. Further, it was also observed that the major obstacle in procurement, use and maintenance of engineering equipment at tertiary institutions was mostly administrative, technical or financial. As detailed in Chap. 8, the lack of documentation and flexibility in policies and guidelines created unnecessary bureaucracies in the procurement and maintenance of critical laboratory equipment used in the training of engineering students. The quality of engineering education was severely affected by the lack of expertise required to operate specialised laboratory equipment, even in cases where the equipment had been donated (World Bank 2014). This effect was also felt in industry as it was naturally passed on from tertiary institutions and it invariably and negatively affected capacity utilisation and in some cases obsolescence of equipment even before fully realising the return on capital invested in purchasing the equipment. The heavy reliance on foreign aid also contributed to this mishap where tertiary institutions and industry within the region needed to collaborate in order to overcome such obstacles. Previous chapters looked

13.2  Practices and Shortfalls in Academia and Industry

275

at various avenues in which the ties between industry and academia can be strengthened, with a special purpose methodology of systems thinking. These avenues included impact of the industrial transformations on academia and industry, collaborations between academia and industry through secondments and attachments to enhance problem and industry-based learning and solutions, case studies to improve efficiencies, productivity, access to modern equipment and technology, incubations and commercialisations of research by academics, culminating in the integrated Universal Systems Thinking (UST) model to cement the ties between academia and industry.

13.2  Practices and Shortfalls in Academia and Industry Due to the nature of the fourth Industrial Revolution, technology and equipment used in training and industrial operations have changed rapidly and dynamically, and so have the methods of production. This research revealed that industry and tertiary institutions in Southern Africa, in particular under the SAE2Net collaboration, have struggled to cope with the demands, primarily due to lack of capacities to match those in the industrialised world. While some of the institutions under SAE2Net, such as University of Johannesburg and Namibia University of Science and Technology had managed to procure equipment that was commensurate with practices in their local industries, the rest of the institutions still relied heavily on conventional machine tools for training. Unfortunately, the same machines were also driven by outdated software and spare parts which Original Equipment Manufacturers were no longer able to support. In addition, the global financial crisis of 2008 and the aftermath saw some companies in the region either scaling down operations or merging and at the worst liquidated due to operational challenges that included lack of appropriate engineering skills. The general trend observed from the research as detailed statistically in Chap. 8 was that engineering or laboratory equipment at most of the institutions were underutilised, outdated or in poor state due to lack of skills or expertise to use them, let alone maintain them. Several studies as detailed in previous chapters also revealed the persistent shortages and mismatch of engineering skills between those produced by tertiary institutions and those required by local industries, mostly because of the type of equipment available for training as well as the capacities and skills for engineering academics to confidently deliver appropriate lectures and impart relevant skills. The shortages in industry were mainly due to the flight of staff and turnover that resulted in many professional engineers seeking employment in better performing economies in the region or abroad. These inadequacies in the training of future engineers to drive industry in the region and the flight of professional engineers in search of greener pastures adversely affected industrial operations leading to declines in productivity and capacity utilisation. Some of the movements of these engineers were from one country to another within the same region, creating disparities in the spread of engineers and skills.

276

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

Such shortages of both practising engineers in industry and engineering academics created some serious operational challenges for both, but according to research and literature, this also created opportunities for ‘pracademics’, a scheme that has been successfully adopted by the industrialised world where practising engineers provided lecturing through Adjunct Professorships (USA) or Visiting Professorships (UK) while academics also provided industrial solutions through secondments. The same principles such as the Adjunct or Visiting Professorships as well as secondment of engineering academics to industry have been adopted by all the institutions under the SAE2Net collaboration, with interesting results such as the fully funded Professorial Chair in Mining Engineering at the University of Zimbabwe. This was an opportunity created out of the improved ties with industry and it was expected that as the SAE2Net collaboration grew, especially after the full establishment of the Doctoral Training Centres  (DTC), that each DTC will have its own Professorial Chair funded by industry. However, the limitation to this scheme in Southern Africa is that the few practising engineers available in industry were already overstretched to the extent that they may not be able to spare time to contribute to the training of engineering students. Nevertheless, this was a temporary setback in the interim but as the collaboration and network grows, capacity can be built through the other avenues proposed in this book in order to augment this scheme. Industry and Governments in Southern Africa have played their part in supporting the development of human resources in all spheres of their economies. This has been achieved through the enactment of legislation such as the Manpower Development Act in Zimbabwe and the Company Concession Tax System in South Africa to boost the development of human resources for industry through levies and taxes. While these were noble initiatives, challenges observed during the research included mismanagement of the funds which forced some industry players to be reluctant in contributing. However, some countries have turned this challenge into an opportunity where industry has been encouraged to contribute directly to tertiary institutions through Professorial Chairs or provision of services through Adjunct and Visiting Professorships. In addition, development partners and foreign aid agencies have also come to the rescue through research and project grants such as NUSESA, EEEP and HEP SSA, all meant to enhance the quality of engineering education and the resulting engineering graduates. However, such schemes could only be sustained within the funding period, hence the establishment of the Southern Africa Engineering Education Network (SAE2Net) to carry forward the initiatives for continuity and sustainability. The shortfalls that ranged from inadequacies in training, shortages and mismatch of engineering skills, declines in productivity and capacity utilisation in industry, flight of staff and migration of engineers from one country to another within the region, mismanagement of funds and dwindling research grants from industry and governments were to a large extent converted to opportunities through the SAE2Net collaboration. These included the promotion and strengthening of ties between industry and academia through secondments to expose academics to relevant industrial operations and the provision of solutions through modelling and optimisations,

13.3  Capacity Utilisation and Productivity in Industry

277

joint research and publications by participating institutions to ‘level the playing field’ and thus reduced flight of staff, culminating in the improved mobilisation of support from international partners.

13.3  Capacity Utilisation and Productivity in Industry In almost all the industry partners under the SAE2Net collaboration, engineering academics seconded to these companies identified several challenges such as the crisscrossing and backtracking of process flows and paths, which resulted in unnecessarily long distances traversed by parts and raw materials in production, thereby delaying production, increasing lead times and reduced throughput. As detailed in Chap. 6, techniques such as machine distance matrices and group technology were employed to reorganise the workstations using functional groups to achieve one-­ directional flow of parts and sub-assemblies. This particularly applied to the foundry and general engineering as well as the furniture manufacturing companies. Modelling and simulation were also employed in the same companies to identify bottlenecks and thereby optimising the process flows. Arena simulations and analysis were also useful to assist the companies and advising them to put additional machine tools, especially where bottlenecks were identified. The additional machines were well worth the investment, as experimentations with Arena simulations showed a potential reduction of operational costs by as much as 48% in furniture manufacturing. When the recommended models were adopted, the company’s gangways were freed even with the additional machine tools, resulting in safe working environments. The reductions in operating costs and waiting times resulted in reduced lead times and the production of competitive goods and services. Specifically, for the furniture manufacturing company, modelling and simulation with Arena were used to optimise the process flows using the company’s most popular products, bunk beds, industrial pallets and baby tenders, the results of which validated the proposed and adopted layout. Generic simulation models developed for these products, in terms of flows, organisation and grouping of machine tools, as well as additional machine tools to clear bottlenecks, resulted in the reduction of transportation distances of up to 50% and also 26% reduction in lead times. This resolved the company’s main challenge identified at the inception of the research, that is, failure to meet customer demands which sometimes resulted in cancellation of orders and customers preferring to order elsewhere or importing. Although there were no significant changes proposed for the foundry process flows, except for the relocation of the weighbridge close to the bailing area, Arena simulations and experimentations were also carried out which identified bottlenecks in bailing and fettling, following which an additional machine each was recommended for the two processes, resulting in the smooth flow of processes with minimal bottlenecks. Despite the various workstations that the company had such as, induction, arc and cupola furnaces of variable capacities, which were not utilised at all times, the

278

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

company still failed to meet the demands for grinding balls from the mining industry. This was mainly due to power outages that forced the company to run night shifts, but the introduction of the additional bailing machine improved the lead times. The average transportation distances from bailing through the weighbridge to the furnaces, fettling and finally dispatch to customers were reduced from 25 m to 15 m while the times were reduced from 1 min to 36 s following Arena simulations and experimentations, coupled with the additional bailing and fettling machines as well as the relocation of the weighbridge. The technology that the company employed for casting the grinding balls was also optimised by way of redesigning the gating systems which resulted in the reduction of waste during the processes of casting and fettling from 37 to 24%. Despite the well-capitalised and fully automated platinum processing company, they were also affected by the frequent power outages, which in turn negatively affected capacity utilisation and productivity of the energy-intensive processes. Modelling and simulation using both Arena and Limn Flowsheet Processor were employed and alternative configurations for comminution and flotation were experimented on in order to improve productivity. The simulations and experimentations recommended the now-adopted high-pressure grinding rolls for milling, as they had the potential to reduce the power required by almost 50% from 4475 to 2240 kW for the SAG mill. Cleaner scavenger cells were also recommended for the flotation circuit, as they had the potential to increase residence time, thus allowing slow floating Platinum Group Metals (PGM) to be captured before disposal to the tailings dam. The reconfiguration recommended and adopted after the modelling, simulation and experimentation resulted in marginal gains in PGM metal recovery of 0.67%. The combined reconfigurations of the comminution and flotation circuits resulted in 2.97% increase in mineral recovery and 4 g per tonne in productivity. However, this was only up to the granulation matte which was exported for further refining in South Africa due to the lack of expertise and base metal refinery (BMR) and precious metal refinery (PMR) equipment in Zimbabwe. The challenge for lack of beneficiation in Zimbabwe could be turned into an opportunity through the SAE2Net collaboration where expertise and skills can be availed from one country to another. These achievements were a demonstration of the usefulness of the input from academia to improve industrial operations, with minimal financial input. The challenge for shortages of skills in industry, as well as the expensive hiring of expertise from outside the region, was turned into opportunities where academics provided the required solutions while accessing relevant equipment, technology and industrial operations in order to enhance the delivery of their teaching and production of relevant graduates to drive industry. Furthermore, this was also a demonstration that improvements in industrial operations did not necessarily require recapitalisation but simply reorganisation of workstations. Engineering expertise and skills to realise the full benefits of mineral processing can be availed through the regional collaboration to enable the installation of BMRs and PMRs at source to avoid exporting raw minerals.

13.4  Capacity Building and Sustainability

279

13.4  Capacity Building and Sustainability The supports received from various foreign aid agencies to Southern Africa such as Sida’s support for NUSESA and the Royal Academy of Engineering support for EEEP and HEP SSA were all meant to improve the quality of engineering education and the resultant graduates in order to improve the delivery of service in academia and the quality of engineering practice in industry. These initiatives were varied where NUSESA focussed on appropriate use and maintenance of scientific equipment, EEEP focussed on establishing links between industry and academia through secondments of engineering academics to industry to expose them to relevant industrial practices and HEP SSA focussed on enhancing EEEP through scaled-up activities that helped to strengthen the ties between industry and academia. These initiatives were based on the outcome of several studies carried out in Sub-Saharan Africa which concluded that, ‘The key to building engineering capacity in Southern Africa must be the improvement of tertiary engineering education’ (Matthews et al. 2012) and that ‘Engineering skills were key to achieving self-sustenance for capacity building and sustainability, thus less dependence on foreign aid’ (Nyemba 2017). The capacity-building initiatives for engineering academics were not only centred on secondments to industry but the support also provided for professional development and training on the use of specialised techniques and equipment such as computer numerically controlled (CNC) machines as well as periodical seminars and workshops to share knowledge with counterparts and colleagues from the other collaborating institutions within the region. These activities not only helped to boost engineering academics’ confidence in lecturing as derived from the students’ mid-­ semester evaluations but also created opportunities for the academics to generate practical and industry-based projects for students which exemplified and created platforms for problem-based learning. The initiatives were also evaluated by independent assessors, confirming the enthusiasm and interest in both students and staff, an indication that the lack of access to relevant equipment and technology in industry was converted to an opportunity to build capacity and confidence through the engagements with industry. Motivational workshops were also held throughout the different projects and these attracted engineering practitioners from industry to engage with students periodically, to outline challenges and successes in industry in order to boost academia’s appreciation of industrial operations, as well as to encourage them to continue churning out the required expertise and skills to drive industry. The knowledge-sharing workshops were also used as platforms by the engineering academics to showcase their research and innovations as a way of demonstrating their potential and usefulness to industry. These interactions were useful to convince cooperating partners to scale up their support and expand the initiatives, hence EEEP to HEP SSA. The interactions and knowledge-sharing workshops between industry and academia as well as among tertiary institutions were also used as platforms and opportunities to coerce industry to buy into these noble initiatives in order to take part-ownership and provide support for the building of capacity, research and

280

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

innovations, as well as to encourage them to invest in start-ups and spin-offs created by academics through business incubations. Since the first initiative, NUSESA in the 1990s, there has been gradual but growing interest from industry to be directly involved in the development of human resources, not only through the provision of levies for manpower development but also through the provision of expertise for specialised training. The gradual nature of the buy-in from industry was understandable, in that most companies were heavily affected by the global financial crisis of 2008 that forced some of them to scale down operations, leaving very little to invest in capacity building. The challenge faced by most tertiary institutions at the time was also the inability to sufficiently mentor and administer relevant skills to future engineers as a result of lack of experience by the mostly young engineering academics as well as the conventional equipment that was used in training. As detailed in earlier chapters, less than 25% of engineering academics from the institutions under SAE2Net partnership held PhD qualifications, let alone being Professors. The availability of Professors at these institutions invariably helped to provide academic guidance and expertise as well as boosting an institution’s chances of securing grants for research. As such, one of the objectives for these capacity-building initiatives was to convince industry to provide support in order to attract highly skilled engineers at the professorial level from around the world. This was modelled around the framework where the incumbents would not only provide service to academia but also provide expert advice and consultancy to industry. Through this initiative and research, as well as growing interest from industry, the platinum mining and processing company provided a package for a fully funded Professorial Chair in Mining Engineering at the University of Zimbabwe in 2012. It was not until 2016 that the position was eventually filled by a Professor of Materials and Mining Engineering from Penn State University in the USA. Despite the advertisement having been publicised as soon as the package was offered, the delay in securing the appointment was due to several reasons such as professionals from the industrialised world shunning to work in the region because of recession and political instabilities. With the assistance from colleagues at Penn State University, the incumbent has provided mentorship and guidance to young metallurgical and mining engineering academics and students, as well as provided guidance and expert advice to the platinum mining and processing company. Typically, such opportunities were expected to be spread in all the institutions under SAE2Net, focussed on at least one such Professorial Chair at each of the Doctoral Training Centres proposed and detailed in Chaps. 7 and 9.

13.5  B  uild-Operate-Transfer: Smart Procurement of Equipment This research established that the biggest challenge faced by tertiary institutions in Southern Africa as far as the quality of engineering education was concerned, was the mismatch of skills between those produced by universities and what industry

13.5  Build-Operate-Transfer: Smart Procurement of Equipment

281

actually required. This varied from country to country depending on how well capitalised the laboratories were in each institution. The situation in the semi-­ industrialised South Africa and Namibia where the equipment in their laboratories were up to date and matched with those in their local industries was different from the rest of the institutions under the SAE2Net collaboration. These institutions relied heavily on old and outdated conventional equipment which were still largely analogue, whereas the equipment in their local industries had been digitalised. This resulted in the development of skills that were not appropriate for industry. This challenge was resolved by creating opportunities for academics to access modern or relevant equipment in industry through secondments. The evaluation carried out after the NUSESA project revealed that the average age of equipment in the engineering laboratories in the region was over 15 years. Despite the fact that most of this equipment was still functional and used for training, the technology to drive the machines was outdated and could no longer be supported by Original Equipment Manufacturers (OEMs) in terms of software and spares. Not only did this result in frequent breakdowns of machine tools that could not be repaired anymore but also created graduates with old technology skills, a worrisome occurrence for institutions mandated to develop the skills to drive industry in this rapid and dynamically changing environment in the fourth Industrial Revolution. As detailed and analysed statistically in Chap. 8, this research also established that the newer departments and institutions also had newer equipment, most of which were supplied by OEMs domiciled in the countries that helped to establish those departments or institutions, but with no local or regional companies to provide back-up support for maintenance. It was also established that a significant chunk of the equipment in most of the institutions was either obsolete or not functional. This was attributed to the low staffing levels in the departments exacerbated by the lack of PhD holders or experienced researchers such as Professors. This observation implied that obsolescence was partly as a result of underutilisation or lack of skills to use the equipment, a reflection of the equipment categorised as functional but not being used. The lack of highly qualified academics actively involved in R&D projects and expertise to use the equipment also meant that the utilisation was concentrated in teaching but very little for research and consultancy services, clear opportunities for publications and generation of income, respectively. The challenges as far as equipment was concerned can be summed up as underutilised, outdated technology or simply poor state due to lack of maintenance. The information used in Chap. 8 was derived not only directly from the institutions but also through knowledge-sharing workshops and interactions. As part of the critical systems thinking elements in the UST model, the Equipment and Technology (ET) sub-model was regarded as the most critical of the other sub-models due to the practical and technology nature of the engineering profession, hence the need for academics to have access to relevant and at best modern equipment, not only for their experience but to boost their confidence in delivery of lectures. However, it was also noted that the ET sub-model was capital intensive, as the proposed interventions required financial support from governments, which was also reported to be dwindling in most of the countries. Relying exclusively on support from

282

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

international foreign aid agencies and cooperating partners was not sustainable, as most of this aid was finite and provided as seed funds. To maintain momentum and continuity of the noble initiatives supported by the international partners required commitments and buy-ins from stakeholders such as governments and industry. Thus, the Smart Procurement Partnerships (SPP) under the ET sub-model and the UST model were premised on collaborations within a regional network of universities and industry, giving birth to SAE2Net. This was modelled on the assumption of improved and strengthened ties between academia and industry. Although the concept of Build-Operate-Transfer (BOT) was more applicable and widely used in construction projects, this was the phenomenon adopted in this research and proposed for SPPs where industry can provide academia with grants to acquire equipment and in turn academia provided services to industry in order to pay back for the equipment, a situation where both parties benefitted. In this regard, governments can facilitate and guarantee such concessionary BOT agreements between academia and industry through appropriate legislation. Whether the equipment was acquired through SPPs or donated, if properly utilised and managed, can also be used for consultancy services to other industry players in order to recover the capital invested in a shorter period of time or use the funds to maintain the equipment. The SPP agreements were thus developed as tripartite models similar to the Triple Helix framework. As a result of these interactions, forced by challenges but turned into opportunities, modern equipment was procured for tertiary institutions as detailed in Chap. 8. In addition, some industry partners also agreed to share specialised and expensive equipment instead of duplicating and underutilising them, an example being the Atomic Absorption Spectrometer and hardness tester between the foundry and general engineering company and the metallurgical department at the University of Zimbabwe. The other laboratory equipment acquired during the research and as a result of the interactions between industry and academia is detailed in Chap. 8. Investments by industry for university equipment can be quite feasible, especially if academia demonstrated their potential and usefulness in the provision of solutions for industrial operations, thus strengthening the ties between the two.

13.6  Community Service and Spin-Off Activities The global financial crisis of 2008, particularly the aftermath and the political instability in Zimbabwe, resulted in record hyperinflation in the country while the other countries in region were also affected to some extent. Generally, this meant that some companies were downsized while government support was reduced and tertiary institutions that depended solely on government grants were heavily affected. This required some innovation and changing of the mindsets in order to create situations that enabled the generation of income to sustain operations. As evidenced by the general trend around the world, tertiary institutions have worked towards becoming entrepreneurial universities through commercialising research and innovations and in some instances, providing services that would ordinarily be outsourced.

13.6  Community Service and Spin-Off Activities

283

An example of such a venture, through the secondments and interactions with industry was the University of Zimbabwe groundwater project briefly mentioned in previous chapters. The downsizing of companies did not only affect industries but local authorities as well. For almost 5 years after the recession of 2008, the City of Harare had been failing in their mandate to provide sufficient and clean water to communities including the universities. For institutions like the University of Zimbabwe with student population of over 20,000 and 5,000 staff, the absence of clean water obviously posed a health hazard which forced the institution to suspend business on a number of occasions between 2008 and 2013. Using the skills derived from secondments and the principles from the UST model, the Faculty of Engineering’s different disciplines collaborated and developed an ambitious but successful groundwater project to abstract groundwater to supply the entire campus in order to solve the perennial shortages and erratic supplies of water to ensure uninterrupted business of the institution. The systems thinking elements in the groundwater enterprise model comprised project administration provided by the Dean’s office together with engineering academics and technicians from the departments of Civil, Electrical, Mechanical Engineering as well as Land Surveying, who had been seconded to different sectors of industry. The elements represented in the model included project management for overseeing the execution and implementation of the project. Academics and technicians from Civil Engineering dealt with the civil works that included construction of the sump, pump-house and storage tanks, as well as carrying out hydrogeological tests. Those from Mechanical Engineering sized and selected the required submersible and booster pumps as well as fabrication of pipework in the pump-­ house. The electrical engineers designed and developed the power supply and control systems for the water network, while the land surveyors developed the routes for the pipes including levelling. All this was done in consultation with the Zimbabwe National Water Authority and the university’s works department. Following hydrogeological tests to identify the most suitable sites, the project was successfully achieved by drilling 13 boreholes around the campus. Two storage tanks of combined capacities of 5000 m3 and one 500 m3 sump for collecting water from the 13 boreholes before boosting and pumping to the two storage tanks were constructed. Initially, two booster pumps were installed but following experimentations, an additional booster pump was installed. During the experimentation and testing of the system, a number of challenges were identified such as frequent breakdown of the equipment and inconsistences in the quality of water derived from the different boreholes. Additional challenges included frequent power outages that affected the pumps resulting in insufficient supplies. However, these were resolved through control and experimentation of the model through the installation of solar power for augmenting the power supply as well as installation of the purification plant within the pump-house, including regular tests and monitoring of the quality of water by technicians from the water section of the Department of Civil Engineering. The electrical installations were also revamped by protecting the network of pumps and other equipment using surge protectors and necessary controls to cut off the pumps when it was not necessary to pump. The two storage tanks were deliberately constructed on high ground to enable the distribution of water throughout the

284

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

Planning and Scheduling Problems? Erratic supply of water to UZ campus, Closure of campus for fear of diseases

Dean’s Office, Civil Engineering Electrical Engineering, Mechanical Engineering, Land Surveying Works Department

Design

Design and Modelling

Project Management, Construction, Hydrogeological Tests, Power and Control, Pump Selection and Sizing Fabrications of Pipe Network Routing, Levelling

Feedback Purification, Chlorination, Solar Pumping, Pump Resizing Surge Projection Control, Increase Experimentation, Boreholes & Improvements

Manufacture Breakdowns, Contaminated water, Insufficient supplies Power Outages

Uninterrupted Supply of Clean Water Uninterrupted University Programs Community Service Opportunity for Spin-Off Company

Simulation

Implementation

,

Fig. 13.1  Systems thinking groundwater enterprise model

campus by gravity to all amenities sufficient to cater for the population of over 25,000 during semesters. The system was commissioned in 2014 and has been operating with regular maintenance. The groundwater enterprise model as derived from the UST model, combining the principles of ET, SDT and PDP sub-models, is shown in Fig. 13.1. The total project costs were mainly materials and hired general labour for trenching and construction, amounting to USD 468,000. Had the project been outsourced by engaging professional engineers and land surveyors, it was estimated to have cost the institution approximately USD 1.5 million. As such, the community service and involvement of engineering academics and technicians following their successful stints on secondments saved the institution in professional fees for the design, development and implementation of this enterprise model in excess of USD one million (RAEng 2017). Although this project has not been carried forward to implement similar interventions at other organisations, it was typically the innovation that had the potential and created opportunities for a spin-off company to provide such a service to other institutions as a way of generating income for the institution. Similar interventions have also been implemented and adopted in such ventures as the solar lighting for the entire campus. The novel and systems thinking approach stood to benefit a wider community while providing income streams, growth and wealth creation. Figure  13.2 shows a collage of pictures for the different stages undertaken in the development and implementation of the UZ Groundwater Enterprise Project as depicted in the systems thinking model.

13.7  Constraints and Limitations

285

Fig. 13.2  Stages in the development and implementation of the groundwater enterprise

13.7  Constraints and Limitations While the models developed in this research were experimented on and produced results that persuaded industry to implement, there were constraints and limitations that should be paid attention to in the event that similar models and innovations were developed premised on these systems thinking principles. As outlined in previous chapters and alongside the different sub-models, assumptions were made. For the simulation models, the general assumption was that wherever the modelling and optimisations were being carried out, there would be at least one 8-h shift with minimal breakdowns and downtimes, otherwise the simulation results would not make much sense but reasonable enough to represent the real situation on the shop floor. Maintenance for the equipment in that regard was assumed to be carried out during the off-shift periods, but in reality, this may not be achievable hence the need for some kind of buffer to allow for maintenance during the shift period and thus corresponding adjustments in the models.

286

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

The orders at the various companies that were modelled, simulated and optimised were assumed to be received through a uniform and normally distributed pattern based on historical data for previous transactions. Documentation and data were not always available at some of these companies, hence the need for rigorous experimentation in order to verify and validate the information. In the case of the platinum mining and processing company, whose operations were slightly different from the other companies, the delivery of ore to the bunkers was assumed to be received at a constant rate of approximately 105 tons in 15 min and discrete event simulation was thus employed for modelling of the comminution and flotation circuits, taking into account reasonable delays or nominal residence times that were uniform or followed a defined mathematical distribution. Due to the volumes of ore that were handled periodically, the entity value of 1 was used in the Arena models to represent 100 tonnes in the plant. In terms of commercialisation of research and innovations, there were two possibilities, either open innovation in which inflows and outflows of knowledge were allowed to occur in order to accelerate internal innovations and expand growth and wealth creation and external markets for the innovations or closed innovation, typical of what the R&D departments in industry were involved in. A balance must be struck between the two in order to accelerate business incubations, especially if the ultimate objective would be to create successful start-ups and spin-offs. In any case, research has shown that industry can no longer afford to single-handedly carry out R&D activities particularly in view of the rapid and dynamic changes in technology that required not only the constant flow and transfer of knowledge from tertiary institutions but also the close collaboration between academia and industry in other spheres of work (Bubou et al. 2017). This has pushed industry to provide support through business incubation at tertiary institutions. The major constraints that affected both industry and academia in Southern Africa were the effects of the global financial crisis which left tertiary institutions with limited grants to pursue research and commercialise innovations a well as the declines in industrial activities due to the scaling down of operations and limited grants from industry for R&D. There could be numerous other factors such as the macro-economic environment, political stabilities of different states, corporate governance and the skill levels outside science, engineering and technology, but this research was limited to three aspects, namely technology, training and policies related to the development of human resources in engineering, broadly to enable and enhance the ties between academia and industry. The major limitation for adoption and implementation of the ET, SDT and PDP sub-models and the eventual integrated UST model would be the acceptance by authorities as some of the recommendations required capital injection. However, the general concepts including secondments, doctoral training centres, adjunct and visiting professorships and the establishment of the Southern Africa Engineering Education Network (SAE2Net) have been embraced and implemented by all institutions under this partnership, including industry buy-in. The interactive interviews, observations and surveys carried out by engineering academics on secondments revealed that the major challenges and limitations in

13.8  Regional Collaborations and Integration

287

adopting and implementing solutions provided by academia as well as sustainable strategies included lack of skills and capacities, staff ignorance of new technologies and the resistance to change, lack of knowledge and awareness and the disruptive nature of the demands for the fourth Industrial Revolution, obviously worsened by the scaled down operations in some companies. Despite these numerous challenges, the research also revealed that the challenges could be turned into opportunities through appropriate interactions between industry and academia, as well as relevant training and skilling of engineering students in preparation for driving industry in the future. While there were many possible ways to resolve these challenges and turn them into opportunities that may result in other positive outcomes, the proposed solutions and implementations required capital investment. However, for a start, the collaborations among tertiary institutions and between academia and industry stood to save such investments by way of sharing human resources and expert skills as well as the few available and capital-intensive equipment. In order to overcome the limitation on logistics and management of such initiatives would be the establishment of a legal instrument that operationalised the collaborations and this was done through the signing of the Memorandum of Agreement by the partners under SAE2Net in 2020. The adoption of the systems thinking sub-models as well as the UST model was also used as an avenue to address some of the logistical challenges that arose, through the emphasis of all stakeholder participation and involvement as well as buy-in in order to take part ownership of the network and its activities.

13.8  Regional Collaborations and Integration Most of the interventions proposed in this research required collaborations among tertiary institutions as well as between academia and industry for effective and positive outcomes. While it may be possible for single institutions to collaborate with particular industries for specific purposes, this may present challenges and limit the spread of support from industry as well as the provision of solutions to industry by academics. The ultimate expectation from the models developed in this book would be regional integration and the involvement of as many players as possible, in a strategic manner to realise the full potential of the systems thinking approach, premised on the principle that ‘the whole was greater than the sum of its parts’ (Bartolomeo et  al. 2015). However, the major obstacle in this regard and in the research in particular towards the end was the COVID-19 pandemic which restricted travel throughout the world. However, be that as it may, academia and industry have to adjust to the new normal such as the virtual and online collaborations under SAE2Net as detailed in previous chapters. The virtual collaborations adopted in the latter part of this research included the establishment of Doctoral Training Centres (DTCs) through the Centres of Excellence (CoE) at each of the tertiary institutions under the SAE2Net partnership. The regional collaboration and functioning of these DTCs and CoE were meant to

288

13  Challenges and Opportunities: Discussion and Predictions from Research Findings

provide specialist training in different fields of engineering up to PhD level as well as offering CPDs to practising engineers in industry. Training at such levels did not necessarily require the physical presence of the trainees, as these can be accomplished virtually as what happened during the year, 2020. The agreement signed by the participating institutions entailed the exchange of both students and staff, albeit virtually and possibly physically after the COVID-19 pandemic. Engineering academics under the SAE2Net regional collaboration have offered specialist courses to practising engineers focussing on the different areas such as renewable energy, water resources management, and power distribution and management. While tertiary institutions were also naturally expected to compete against each other in various spheres such as grants for research from industry and other sources, as well as for the best students from high school, collaborations through coopetitions provided the necessary platforms for institutions to improve their global rankings through joint scholarly research and international publications. This was demonstrated by the partnership under SAE2Net through 5 journal publications and 12 conference papers, jointly researched and authored by engineering academics within the region in a space of less than 2 years. The concept of secondments to industry under the regional collaborations has also produced positive outcomes, in that the scheme allowed engineering academics from one country to experience industrial operations in other countries within the region.

13.9  Conclusion The bridge between academia and industry still remained wide, particularly in Southern Africa. However, with the widespread adoption and implementation of the fourth Industrial Revolution and the preparation for the Digital Ecosystem, there have been growing calls to narrow the bridge, through strengthening the ties between industry and academia where academia was expected to avail the skills that industry required and in turn, industry provided the necessary support to make the training of engineers more relevant, facilitated by governments and other stakeholders such as professional engineering institutions, regulatory bodies and research institutions. However, this may be easier said than done as there were many challenges and limitations in adopting approaches proposed in this research, based on the systems thinking methodology. The most significant challenges included the effects and aftermath of the global final financial crisis of 2008 which left governments and industry unable to provide necessary grants for research or commercialisation of innovations. The COVID-19 pandemic resulted in restrictions to travel throughout the world, putting a damper on researchers in terms of conferences and showcasing of their research. This chapter focused on outlining the various challenges and limitations encountered in this research and how these were resolved and at best turned into opportunities based on the research findings, dictations and predictions for the future stability and sustainability of the ties between academia and industry as well as among

References

289

tertiary institutions. Some of the achievements and opportunities derived from the challenges included the provision of solutions to industry through modelling and simulation in order to optimise industrial operations and reorganise plants through group technology for productivity, efficiency and capacity utilisation. The failure to access relevant equipment and technology was resolved by seconding engineering academics to industry to boost capacity building, confidence and quality in engineering education. Such interactions with industry also resulted in a fully funded Professorial Chair in Mining Engineering at the University of Zimbabwe, creating further opportunities for mentoring young engineering academics. The positive results availed to industry also persuaded them to provide or share equipment with tertiary institutions. The systems thinking principles were also employed in the design, development and implementation of a groundwater enterprise project where engineering academics at the University of Zimbabwe used the skills acquired in industry to resolve a perennial shortage of water on campus. The project was commissioned in 2014 and has continued to provide safe, clean and adequate supplies of water to the entire campus.

References Bakrania, S., & Lucas, B. (2009). The impact of the financial crisis on conflict and state fragility in Sub-Saharan Africa. GSDRC Applied Knowledge Series. Available: http://www.gsdrc.org/go/ emerging-­issues#crisis. Accessed 24 Mar 2016. Bartolomeo, P., Vuilleumier, P., & Behrmann, M. (2015). The whole is greater than the sum of the parts: Distributed circuits in visual cognition. Cortecx, 72(2015), 1–4. Bubou, G. M., Offor, I. T., & Bappa, A. S. (2017). Why research-informed teaching in engineering education? A review of the evidence. European Journal of Engineering Education, 42(3), 323–335. Matthews, P., Ryan-Collins, L., Wells, J., Sillem, H., & Wright, H. (2012). Engineers for Africa: Identifying engineering capacity needs in Sub-Saharan Africa, analysis of stakeholder interviews. London: Royal Academy of Engineering. ISBN: 1-903496-91-8. Nyemba, W. R. (2017). Engineering skills are the key to achieving sustainable development and reducing foreign aid dependency. Huffington Post (UK) (2017). Available: http://www.huffingtonpost.co.uk/wilson-­nyemba/engineering-­skills-­are-­th_b_14135774.html. Accessed 6 June 2018. Ott, T. (2020). Isaac Newton changed the world while in quarantine from the plague. Biography. com. Available: https://www.biography.com/news/isaac-­newton-­quarantine-­plague-­ discoveries. Accessed 20 Dec 2020. RAEng (Royal Academy of Engineering). (2017). Enriching Engineering Education Programme (EEEP). Available: https://www.raeng.org.uk/publications/other/enriching-­engineering-­ education-­programme. Royal Academy of Engineering. Accessed 20 Mar 2018. Ray, S., & Srivastava, S. (2020). Virtualization of science education: A lesson from the COVID-19 pandemic. Journal of Proteins and Proteomics, 11, 77–80. World Bank. (2014). Improving the quality of engineering education and training in Africa. In Science, technology, and skills for Africa's development. Washington DC: World Bank Group. World Bank. (2020). COVID-19 Crisis: Through a migration lens. In Migration and development brief 32. Washington DC: World Bank Group.

Chapter 14

Conclusions: Consolidated Research Findings and Recommendations

Abstract  Over the years, there has been growing calls for academia to work closely with industry and several models have been developed such as the Triple Helix framework. Generally, such models were premised on the basis of close collaboration of academia, governments and industry in such a way that academia provided the tuition and development of human resources required by governments and industry, governments provided grants to operationalise tertiary institutions while industry produced goods and services as well as contributed in taxation as the largest source of income for governments. This chapter consolidates and summarises the key areas covered throughout the book focusing on going beyond the Triple Helix concept to incorporate other key stakeholders using the systems thinking methodology and developing models to enhance the quality of engineering education and practice in tertiary institutions and industries. This was based on research findings in Southern Africa and recommendations for further research to revamp and strengthen ties between academia and industry. Keywords  Consolidation · Further research · Internationalisation · Recommendations · Regionalisation · Smart partnerships · Systems integration · Systems modelling

14.1  Introduction The Triple Helix connection primarily comprised governments, academia and industry in which if one or more of the three underperformed, the rest were negatively affected, hence the need to ensure that each was functional and making positive contributions to the connection. The major shortfalls in this formation

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3_14

291

292

14  Conclusions: Consolidated Research Findings and Recommendations

were the unavailability of funding to produce high-quality engineering graduates with skills that matched those required by industry, inadequate equipment or skills to enable industry to be efficient and productive in order to remit enough taxes for the proper functioning of governments and provision of grants for research and running tertiary institutions. While this research embraced the Triple Helix model and its principles, it went beyond the concept and framework to identify and incorporate other key stakeholders, not directly part of the Triple Helix. These included professional engineering bodies that frequently played a role of mediation and bridge between academia and industry, regulatory bodies for ensuring that the right curricula were followed by all engineering institutions and for facilitating the accreditation of engineering programmes, nationally and regionally in line with international accords  as well as research institutions to promote and nurture innovations by academics. The accredited programmes enabled and facilitated the mobility of engineers to gain skills and experience from different parts of the region or internationally. Research institutions were also incorporated to facilitate the transfer of technology and knowledge from academia to industry through product development, incubations and industrial parks. All these were reasonably achieved and integrated throughout this research as articulated in the book, albeit with challenges and limitations, through a systems thinking methodology of reductionism, analysis and synthesis. Various systems thinking models were developed and culminated in the Equipment and Technology (ET), Skills Development and Training (SDT) and Professional Development and Policies (PDP) sub-models which were eventually integrated to form the Universal Systems Thinking (UST) model, proposed for the ultimate bridging of gap between academia and industry.

14.2  Industrial Transformations Industrial transformations from the first to the current fourth have not only resulted in the increased integration and multidisciplinary nature of industrial operations but have also impacted on the acquisition of appropriate skills and the need to cope with the demands for the rapid changes in the latter part of these transformations and the need to prepare for the Digital Ecosystem, anticipated to be the fifth Industrial Revolution. Various changes have been introduced to improve the quality of engineering education and practice in line with international accords, but it has not been easy for the industrialising world due to lack of financial capacities, hence the initiatives proposed in this book to strengthen the ties between academia and industry. The future for engineering education and practice depended on and required critical thinkers equipped with creative skills.

14.5 Regional Integration and Internationalisation

293

14.3  Academia and Industry Partnerships With the assistance of international partners, several initiatives have been developed to improve and operationalise the links between academia and industry. These ranged from secondments to business incubations for start-ups and commercialisation of research. Notable accomplishments included the establishment of adjunct professorships and support for professorial chairs to provide academic leadership and advice to industry as well as opportunities for problem-based learning, relevant and practical industry-based projects for engineering students. The interactions between academia and industry through these interventions as well as knowledge sharing workshops provided the foundation for the systems thinking methodology and various avenues in which the collaborations between academia and industry can be enhanced. Several case studies were carried out by academics to improve efficiency and productivity in industry, a clear demonstration of the usefulness of academia input and contribution to industrial operations at minimal cost or at best as an exchange for access to relevant technology.

14.4  Capacity Building and Sustainability Studies conducted in Sub-Saharan Africa have established the persistent shortages and mismatch of engineering skills, which required innovations to build capacity as well as sustain it within the region. Through close collaborations between academia and industry, academics in Southern Africa have been empowered to access modern technology and equipment in industry through secondments to enhance their experience and boost their confidence in lecturing. Gradually, regional industries have embraced the concepts by supporting tertiary institutions to build capacity through donations of equipment, Build-Operate-Transfer schemes and provision of professorial chairs and adjunct professors. Not only did this strengthen the ties between academia and industry but it also enabled sustainability of the capacity building initiatives by augmenting the support from international partners, which is usually finite and for fixed periods.

14.5  Regional Integration and Internationalisation The new pedagogies in engineering education required close collaborations with industry due to the globalisation of economies and competition, thus pushing for coopetition among tertiary institutions in order to pool and share complementary resources and expert skills. This was accomplished by establishing the Southern Africa Engineering Education Network (SAE2Net), comprising eight institutions in

294

14  Conclusions: Consolidated Research Findings and Recommendations

the region in partnership with a UK institution to leverage on expertise from the industrialised world. SAE2Net was established as a vehicle to manage the partnership through regional secondments, knowledge-sharing conferences and joint research and publications, as well as promotion of innovations and commercialisation among its members. Regional Centres of Excellence and Doctoral Training Centres, one at each of the institutions, were earmarked to be established to provide specialised training up to PhD as well as offering CPDs to practising engineers.

14.6  Commercialisation of Research and Wealth Creation The dwindling financial resources in grants for research from governments and industry prompted tertiary institutions to be innovative in wealth creation and generation of income from commercialisation of research and promotion of entrepreneurships and start-ups by academics. In response to these calls, governments in Southern Africa have made deliberate efforts to invest in establishing innovation hubs and industrial parks after the realisation of their potential and the gap that can be covered to fill the void left by insufficient grants from governments and industry. Despite the establishment of these hubs and industrial parks and their successful operations, a lot still needed to be done to entice industry to invest in these ventures in order to create the ‘Silicon Valleys’ of Africa, thus fully bridging the gap between academia and industry.

14.7  Systems Modelling and Integration The systems thinking methodology of reductionism, synthesis and analysis was chosen for this research, as it offered an all-encompassing alternative for resolving operational challenges to the more traditional and analytical methods that were often linear. This was premised on the principle that ‘the whole was more than the sum of its parts’, hence the incorporation of other stakeholders, in sub-models that were analysed and synthesised using systems mapping, modelling and integration. This research was also based on the hypothesis that, to adequately bridge the gap between academia and industry, there was need for engineering change management and the modelling of subsystems which were integrated into the UST, adopted for strengthening the ties between academia and industry. The model was verified and validated through looping feedbacks, experimentation, control and adjustment of system elements.

14.8  Contributions to Research and Knowledge Research has been carried out to improve technologies and methods of production in industry, enhancing the development of skills to drive industry as well as promulgating legislation and policies for human resources development through

14.10  Recommendations for Further Research

295

frameworks such as the Triple Helix model. However, these have been standalone initiatives, purportedly contributing to lack of continuity and sustainability of some of the schemes. This research proposed and developed a novel Universal Systems Thinking (UST) model through the integration of sub-models and incorporation of various other stakeholders, not just governments, industry and academia as in the Triple Helix. The UST model was verified, tested and validated through various activities including the groundwater enterprise model for the provision of sufficient and clean water to the University of Zimbabwe community.

14.9  Limitations, Challenges and Opportunities While it was desirable to bring industry closer to academia, there were challenges and limitations including funding to support the initiatives, academia access to relevant technology, industry operating below capacity due to downscaling, global competition, as well as pandemics such as COVID-19 that restricted physical networking. Such challenges could, however, be turned into opportunities as the UST model was developed, that is secondments to access to relevant technology but also solving industry challenges in productivity and capacity utilisation and boosting academics’ skills and confidence. The other opportunity was the development and implementation of a groundwater enterprise model to supply safe and clean water to solve a perennial water challenge, using the UST model principles. This could also be turned into a further opportunity to offer similar services to other institutions as a spin-off activity to generate income.

14.10  Recommendations for Further Research While the administrative structure for SAE2Net was established and has been functional since 2020, the outcomes have been wholly positive in every sense and the impact has been qualitatively good, but some of the outcomes were difficult to quantify or measure in the short term, as they required a longer time to mature and be measurable. These included the number of PhD graduates from the Doctoral Training Centres, the number of successful innovations that have been commercialised through start-ups and spin-offs, the impact of Continuous Professional Development (CPD) courses on engineering practice in industry, etc. Logically, further research on bridging the gap between academia and industry needs to be done in the context of how impactful the UST model would have been after a couple of years in the case of Doctoral Training Centres (DTCs) and business incubations while the measurement for CPDs can be carried out in both the short and long terms. The UST’s robustness can also be tested in a wider network of institutions and industry as further research especially with positive results in the initial collaborations  such as SAE2Net. This can be done by broadening the scope to cover

296

14  Conclusions: Consolidated Research Findings and Recommendations

neighbouring regions and industries and possibly expand international partners to include additional ones from outside the UK so that the network can leverage from experiences around the world. While some of the accomplishments included a fully funded professorial chair from one of the mining houses, it was imperative and prudent to explore further research on how best the other industries can be persuaded to provide at least one professorial chair at each of the established DTCs or even better for each discipline at each of the partner institutions.

Appendix

Appendix A7.1: Questionnaire and Survey on Engineering Practices and Challenges Modelling the Integration of Engineering Design and Manufacture for Capacity Building and Sustainability Questionnaire and Survey on Engineering Practices and Challenges on: • • • • •

Technologies Continuous Professional Development Policies Capacities Sustainability Wilson R. Nyemba October 2015 Department of Mechanical Engineering Science Faculty of Engineering and the Build Environment University of Johannesburg Auckland Park Campus P O Box 524 Auckland Park 2006 Johannesburg South Africa Email: [email protected] [email protected] Mobile: +263 772 345 441 +27 739 613 039 Skype: nyemba2

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3

297

298

Appendix

Dear Participant, I would like to thank you for accepting to participate in this survey as an expert in your area. This is a survey meant to collect information for a research that I am currently working on, entitled ‘Modelling the Integration of Engineering Design and Manufacture for Capacity Building and Sustainability’. I believe that the outcome and results will benefit you and your organisation, as it is expected that the research will bridge the gap between industry and academia in order to build capacity for sustainable operations, as well as improve capacity utilisation and enhance productivity in industry. I would like to assure you on behalf of my institution, the University of Johannesburg, that the information you provide will be treated with the strictest confidence and will not be divulged to third parties. We appreciate the confidentiality of company information and will strictly adhere to that. The information gathered from this survey will be solely used for research purposes, the results of which will be available to you for possible use in improving your company operations, as well as to enhance your own continuous professional development. How to Fill in the Questionnaire Answer all the questions to best of your knowledge, skills, and position within your organisation but please note that the questionnaire is not meant to assess people but rather to establish the extent to which the rapidly changing technology, associated training and policies, have been applied and their impact on resolving challenges encountered in engineering design and manufacture. The research also seeks to establish the current relationships between industry and training institutions with a view to bridge the gap between the two in order for the training institutions to produce relevant graduates required by industry. Each question has multiple-choice answers (tick one of the choices that best suits your organisation in line with your expertise). The nomenclature (key) to the answers is as follows: N/A Not applicable, if the question does not fit/apply to your organisation UN Unknown, if you cannot answer the question according to your knowledge, skills or position DA Do not agree with the statement AG Agree with the statement SA Strongly agree with the statement NIL Not at all LE Limited extent A Average HE High extent

I look forward to your responses Eng. Wilson R. Nyemba 

Appendix

299

1. General Information Name (optional) Organisation Business Position Date

2. Technologies Question N/A UN VL L A H VH 2.1 Do you utilise computer-assisted operations? 2.2 Do you frequently get support from original equipment manufacturers (OEM)? 2.3 Do you use computer-aided design, computer-aided manufacturing or flexible manufacturing systems? 2.4 Are your machine tools computer controlled? 2.5 Are your operations integrated and automated? 2.6 Are your machine tools less than 1 year old? 2.7 Are your machine tools more than 5 years old? 2.8 Are your design and manufacturing functions integrated? 2.9 Do you regard the operations as sufficiently efficient? 2.10 Are new techniques introduced frequently? Please add any comments on techniques and technologies employed at your company

3. Continuous Professional Development (CPD) Question N/A UN VL L A H VH 3.1 Does the company provide in-house training? 3.2 Does the company provide support for further training? 3.3 Are there periodic assessments of performance? 3.4 Are employees rewarded for developing themselves professionally? 3.5 Do you frequently interact with tertiary institutions? 3.6 Do you frequently engage students on industrial attachments? 3.7 Do you frequently get support from Original Equipment Manufacturers (OEMS)? 3.8 Does your company have a training centre? 3.9 Are Research and Development (R&D) projects carried out in-house or outsourced? 3.10 Has the efficiency of your unit been improved after continuous professional development? Please add any comments on continuous professional development courses at your company:

300

Appendix

4. Policies Question N/A UN VL L A H VH 4.1 Does the company have documented policies and procedures? 4.2 Does the company frequently update their documents and policies? 4.3 Does the company have policies for rewarding innovation and meeting set targets? 4.4 Does the company have an established business management system? 4.5 Is the company ISO certified? 4.6 Do the machine tools have operational manuals? 4.7 Does the company employ preventive maintenance? 4.8 Is the company compliant with the Zimbabwe Manpower Development Fund (ZIMDEF) in terms of remittances? 4.9 Are feasibility studies or sensitivity analyses carried out prior to introducing new products/services? 4.10 Is your level of position in the company involved in decision-making? Please add any comments regarding policies and their implementation at your company:

5. Capacities Question N/A UN VL L A H VH 5.1 Do the machine tools run with minimal breakdowns? 5.2 Are maintenance and repairs carried out outside working/ production hours? 5.3 Does your company receive uninterrupted supplies of power/energy? 5.4 Are the production and service operations sufficiently modernised? 5.5 Are your machine tools sufficient to meet customer demands? 5.6 Are there sufficient operators for all machine tools? 5.7 Does the company have sufficient mentors and trainers in all departments? 5.8 Are the operational challenges caused by the country’s economic crisis? 5.9 Would you employ techniques such as systems thinking to resolve operational problems? 5.10 Are all the machine tools operational and running during shifts? Please add any comments on capacities in terms of expertise and machine tools:

Appendix

301

6. Sustainability Question N/A UN VL L A H VH 6.1 Is your company business economically viable? 6.2 Does company always meet customer demands? 6.3 Have you ever been implicated or fined by the environmental management agency (EMA)? 6.4 Is your company involved in any corporate social responsibility with communities around you? 6.5 Does the local community contribute in any way to your company operations? 6.6 Does the company carry out periodic assessments of progress and performance? 6.7 Have you been in the company for more than 5 years? 6.8 Is the working environment safe? 6.9 Do you frequently engage with managers or support staff? 6.10 Does the company have sufficient prospects and orders to remain in business? Please add any comments on the sustainability of your company operations

References

Abdullah, M.  F. A., & Alias A.  J. (2005). University-industry smart partnership in enhancing aviation technology education. In: Proceedings of the 2005 regional conference on engineering education (pp.  437–439). Centre for Engineering Education, Universiti Teknologi Malaysia. Available: http://tree.utm.my/wp-­content/uploads/2013/02/PRT-­Mohd-­Fakhrulrazi-­ A-­Abdullah-­Ahmad-­Jais-­Alias_ok.pdf. Accessed 21 Nov 2020. Abu-Goukh, M. E., Ibraheem, G. M., & Goukh, H. M. E. A. (2013). Engineering education for sustainability and economic growth in developing countries (the Sudanese Case). Procedia – Social and Behavioral Sciences, 102(2013), 421–431. Adams, R. (2017). Former Polytechnics should lose University Status. Higher Education in The Guardian of 10 Oct 2017. Afonja, A. A., Sraku-Lartey, K., & Oni, A. A. (2005). Engineering education for industrial development. Case studies of Nigeria, Ghana and Zimbabwe. Nairobi: African Technology Policy Study Network. Ahmad, M.  F. B., & Rashid, K.  A. A. (2011). Lecturers’ industrial attachment programme to increase lecturers’ soft skill and technological competencies for global stability and security. Journal of Sustainable Development, 4(1), 281–283. Ahuja, I. P. S., & Khamba, J. S. (2008). Strategies and success factors for overcoming challenges in TPM implementation in Indian manufacturing industry. Journal of Quality in Maintenance Engineering, 14(2), 123–147. Aisen, A., & Veiga, F. J. (2013). How does political instability affect economic growth? European Journal of Political Economy, 29(2013), 151–167. Al-Kfairy, M., Khaddaj, S., & Mellor, R. B. (2020). Evaluating the effect of organizational architecture in developing science and technology parks under differing innovation environments. Simulation Modelling Practice and Theory, 100(2020), 102036. Allais, R., & Gobert, J. (2016). A multidisciplinary method for sustainability assessment of PSS: Challenges and developments. CIRP Journal of Manufacturing Science and Technology, 15, 56–64. Andersen, A. L., Brunoe, T. D., & Nielsen, K. (2019). Engineering education in changeable and reconfigurable manufacturing: Using problem based learning in learning factory environment. Procedia CIRP, 81(2019), 7–12. Antwerpen, C., & Curtis, N. J. (2016). A data collection and presentation methodology for decision support: A case study of hand-held mine detection devices. European Journal of Operational Research, 251(2016), 237–251.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3

303

304

References

Arnold, R.  D., & Wade, J.  P. (2015). A definition of systems thinking: A systems approach. Procedia Computer Science, 44(2015), 669–678. Asao, K., Miyamoto, T., Kato, H., & Diaz, C. E. D. (2013). Comparison of revenue guarantee programs in build-operation-transfer projects. Built Environment Project and Asset Management, 3(2), 214–227. Asbjörnsson, G. (2013). Modelling and simulation of dynamic behaviour in crushing plants. Master’s thesis. Göteborg: Chalmers University of Technology. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787–2805. Aviso, K. B., Mayol, A. P., Promentilla, M. A. B., Santos, J. R., Tan, R. R., Ubando, A. T., & Yu, K.  D. S. (2018). Allocating human resources in organizations operating under crisis conditions: A fuzzy input-output optimization modeling framework. Resources Conservation and Recycling, 128(2018), 250–258. Ayres, R. U. (1990). Technological trasformations and long waves. Technological Forecasting and Social Change, 37(1), 1–37. Bakrania, S., & Lucas, B. (2009). The impact of the financial crisis on conflict and state fragility in Sub-Saharan Africa. GSDRC Applied Knowledge Series. Available: http://www.gsdrc.org/go/ emerging-­issues#crisis. Accessed 24 Mar 2016. Baldwin, J. S., Allen, P. M., & Ridgway, K. (2010). An evolutionary complex systems decision support tool for the management of operations. International Journal of Operations & Production Management, 30(7), 700–720. Banchi, H., & Bell, R. (2008, Oct). The many levels of inquiry. Science and Children, 46(2), 26–29. Bartolomeo, P., Vuilleumier, P., & Behrmann, M. (2015). The whole is greater than the sum of the parts: Distributed circuits in visual cognition. Cortecx, 72(2015), 1–4. Basoglu, N., Daim, T., & Sofuoglu, E. (2009). A decision methodology for customizing software products. International Journal of Industrial and Systems Engineering, 4(5), 554–576. Behl, D. V., & Ferreira, S. (2014). Systems thinking: An analysis of key factors and relationships. Procedia Computer Science, 36(2014), 104–109. Belaud, J. P., Negny, S., Dupros, F., Micheá, D., & Vautrin, B. (2014). Collaborative simulation and scientific big data analysis: Illustration for sustainability in natural hazards management and chemical process engineering. Computers in Industry, 65(2014), 521–535. Bloomfield, R., Mazhari, E., Hawkins, J., & Son, Y.  J. (2012). Interoperability of manufacturing applications using the Core Manufacturing Simulation Data (CMSD) standard information model. Journal of Computers & Industrial Engineering, 62(2012), 1065–1079. Boothroyd, G., Dewhurst, P., & Knight, W. A. (2011). Product design and for manufacture and assembly. Boca Raton: Taylor & Francis Group. ISBN: 13-978-1-4200-8928-8. Borrego, M., & Bernhard, J. (2011). The emergence of engineering education research as an internationally connected field of inquiry. Journal of Engineering Education, 100(1), 14–47. Borrego, M., Foster, M. J., & Froyd, J. E. (2015). What is the state of the art of systematic review in Engineering Education? Journal of Engineering Education, 104(2), 212–242. Brandenburger, A.  M., & Nalebuff, B.  J. (1996). Co-opetition. New  York: Crown Publishing Group. ISBN: 978-0385479509. British Council. (2018). Building PhD capacity in Sub-Saharan Africa, International Higher Education. London: British Council. Available: https://www.britishcouncil.org/sites/default/ files/h233_07_synthesis_report_final_web.pdf. Accessed: 6 Nov 2020. Broadbent, O., & McCann, E. (2016). Effective industrial engagement in engineering education – A good practice guide, London: Royal Academy of Engineering. ISBN: 978-1-909327-14-6. Brown, P. R., McCord, R. E., Matusovich, H. M., & Kajfez, R. L. (2015). The use of motivation theory in engineering education research: A systematic review of literature. European Journal of Engineering Education, 40(2), 186–205. Brynjolfsson, E., McAfee, A., & Spence, M. (2014). New world order: Labor, capital, and ideas in the power law economy. Foreign Affairs Weekly Newsletter. Accessed 6 May 2020. Available: https://www.foreignaffairs.com/articles/united-­states/2014-­06-­04/new-­world-­order

References

305

Bu, X., Xie, G., Peng, Y., Ge, L., & Ni, C. (2017). Kinetics of flotation. Order of process, rate constant distributionand ultimate recovery. Physicochemical Problems of Mineral Processing, 53(1), 342–365. Bubou, G. M., Offor, I. T., & Bappa, A. S. (2017). Why research-informed teaching in engineering education? A review of the evidence. European Journal of Engineering Education, 42(3), 323–335. Bussiere, M., Saxena, S. C., & Tovar, C. E. (2012). Chronicle of currency collapses: Reexamining the effects on output. Journal of International Money and Finance, 31, 680–708. Byrne, E.  P., Desha, C.  J., Fitzpatrick, J.  J., & Hargroves, K. (2013). Exploring sustainability themes in engineering accreditation and curricula. International Journal of Sustainability in Higher Education, 14(4), 384–403. Cadavid, L.  R., Duque D.  F., Garay, J.  A., & Caicedo P.  F. (2010). Applying systems thinking and active learning strategies to a lean manufacturing program. In Production and Operation Management Society (POMS) 2010 conference. Vancouver, Canada. Cardin, M.  A., Kolfschoten, G.  L., Frey, D.  D., de Neufville, R., de Weck, O.  L., & Geltner, D. M. (2012). An experimental methodology to evaluate concept generation procedures based on quantitative lifecyle performance. In: Proceedings of the 22nd international symposium of INCOSE 2012 and the 8th Biennial EuSEC conference, Rome, July 2012, pp. 777–801. Carrasco, C., Keeney, L., Napier-Munn, T.  J., & Bode, P. (2017). Unlocking additional value by optimizing comminution strategies to process Grade Engineering streams. Minerals Engineering, 103–104, 2–10. Chamber of Mines of Zimbabwe. (2017). 2017 – Stae of the mining industry: Survey report. The Financial Gazette. Harare: Zimbabwe. Available: http://miningzimbabwe.com/wp-­content/ uploads/2017/12/The-­2017-­State-­of-­the-­Mining-­Industry-­Survey-­Report-­2.pdf. Accessed 12 May 2018. Chen, H.  T. (2016). Interfacing theories of program with theories of evaluation for advancing evaluation practice: Reductionism, systems thinking, and pragmatic synthesis. Evaluation and Program Planning, 59(2016), 109–118. Chiunya, N., Mhembwe, S., & Dube, E. (2017). Community Share ownership trusts in Zimbabwe: Prospects and challenges. International Journal of Education and Social Science Research, 1(1), 1–15. Cicek, K., Akyuz, E., & Celik, M. (2019). Future skills requirements analysis in maritime industry. Procedia Computer Science, 158(2019), 270–274. Clarkson, P. J. (2005). Engineering Design Centre, University of Cambridge. In Design process improvement. https://doi.org/10.1007/978-­1-­84628-­061-­0_22. Coelho, D. A. (2013). Advances in industrial design engineering. Croatia: InTech. Crawley, E., Malmqvist, J., Ostlund, S., Brodeur, D., & Edström, K. (2014). Chapter 8: Adapting and implementing a CDIO approach. In Rethining engineering education (pp. 181–207). Cygler, J., & Sroka, W. (2016). The boundaries of coopetition: A case study of polish companies operating in the high-tech sector. In J. Ateljevic & J. Trivic (Eds.), Economic development and entrepreneurship in transition economies: Issues, obstacles and perspectives (pp. 253–269). Cham: Springer. Cygler, J., Sroka, W., Solesvik, M., & Debkowska, K. (2018). Benefits and drawbacks of coopetition: The roles of scope and durability in coopetitive relationships. Sustainability, 2018(10), 2688. De Marco, A., Mangano, G., & Zou, X. Y. (2012). Factors influencing the equity share of build-­ operate transfer projects. Built Environment Project and Asset Management, 2(1), 70–85. de Oliveira, A.  L. R., & Tavares, L.  M. (2018). Modelling and simulation of continuous open circuit dry grinding in a pilot-scale ball mill using Austin’s and Nomura’s models. Powder Technology, 340, 77–87. Del-Soto, F., & Monticelli, J. M. (2017). Coopetition strategies in the brazilian higher education. Revista de Administração de Empresas, 57(1), 65–78. Duignan, B. (2019). Indsutrial revolution. In Encyclopedia Brittanica. Accessed 6 April 2020. Available: https://www.britannica.com/event/Industrial-­Revolution

306

References

El-Houssaine, A., Abdelhakim, K., & Le Tam, P. (2016). Optimizing production and imperfect preventive maintenance planning’s integration in failure-prone manufacturing systems. Reliability Engineering and System Safety, 145(2016), 190–198. El‐Khasawneh, B. S. (2012). Challenges and remedies of manufacturing enterprises in developing countries: Jordan as a case study. Journal of Manufacturing Technology Management, 23(3), 328–350. Engineering Council of Zimbabwe. (2012). Statutory Instrument 153 and Engineering Council of Zimbabwe Act CAP 27:22. Harare: Government of Zimbabwe Printers. Esayas, S. (2017). Competition in dissimilarity: Lessons in privacy from the Facebook/WhatsApp Merger. CPI Antitrust Chronicle, 1, 57–64. Faure, D., & Joly, D. (2016). Chapter 2: Technological revolutions: Possibilities and limitations. In Insight on environmental genomics (pp. 21 – 25). Fengu, M. (2020). University students in a panic as UJ phases out course. City Press. Available: https://city-­p ress.news24.com/News/university-­s tudents-­i n-­a -­p anic-­a s-­u j-­p hases-­o ut-­ course-­20200203. Accessed 1 June 2020. Fleming, J., Iyer, R., Shortis, M., Vuthaluru, H., Xing, K., & Moulton, B. (2010). Employers’ perceptions regarding graduates of engineering dual degrees. World Transactions on Engineering and Technology Education, 8, 277–282. Fomunyam, K.  G. (2019). Education and the fourth industrial revolution: Challenges and possibilities for engineering education. International Journal of Mechanical Engineering and Technology (IJMET), 10(8), 271–284. Frank, M. (2012). Engineering systems thinking: Cognitive competencies of successful systems engineers. Procedia Computer Science, 8(2012), 273–278. Gadallah, Y. (2010). Intellectual property policy for universities and research institutes and economic development – The Egyptian Case. International Review of Intellectual Property and Competition Law, 41(4). Gadzikwa, E. C. (2013). The future of the manufacturing sector in Zimbabwe. Institute of Chartered Accountants of Zimbabwe Congress, 18–20 July 2013, Victoria Falls. Available: https://www. icaz.org.zw/iMISDocs/manufacture.pdf. Accessed 8 April 2017. Gandhi, M. M. (2014). Industry-academia collaboration in India: Recent initiatives, issues, challenges, opportunities and strategies. The Business & Management Review, 5(2), 45–67. Garbie, I. (2017). Identifying challenges facing manufacturing enterprises toward implementing sustainability in newly industrialized countries. Journal of Manufacturing Technology Management, 28(7), 928–960. Garg, A., & Deshmukh, S. G. (2010). Engineering support issues for flexibility in maintenance. Asia Pacific Journal of Marketing and Logistics, 22(2), 247–270. Gedye, S., Fender, E., & Chalkley, E. (2004). Students’ undergraduate expectations and post‐ graduation experiences of the value of a degree. Journal of Geography in Higher Education, 28(3), 381–396. Gero, A. (2017). Students’ attitudes towards interdisciplinary education: A course on interdisciplinary aspects of science and engineering education. European Journal of Engineering Education, 42(3), 260–270. Global Manufacturing. (2014). 6 Challenges facing the global manufacturing sector in 2015. Available: http://www.manufacturingglobal.com/leadership/6-­challenges-­facing-­global-­ manufacturing-­sector-­2015. Accessed 5 Feb 2015. Goldratt, E. M., & Cox, J. (2014). The goal: A process of ongoing improvement (4th revised ed.). North River Press. ISBN-13: 9781622313945. Goodsir, S., Murray, M., Jowitt, P. (2009). Engineering capability in Rwanda. Final project report. Edinburgh: Scottish Institute of Sustainable Technology (SISTECH) & UNESCO. Government of Zimbabwe. (1995). Manpower Planning and Development Act Chapter 28:02. Harare: Government of Zimbabwe Printers https://zimlii.org/zw/legislation/num-­act/1994/24/ Manpower%20Planning%20and%20Development%20Act.pdf. Accessed 24 Dec 2020. Government of Zimbabwe. (2018). National Critical Skills Audit report. Harare: Government of Zimbabwe Printers. 2018. Available: https://safrap.files.wordpress.com/2018/12/2018-­ zimbabwe-­nationalcritical-­skills-­audit-­report.pdf. Accessed 22 Oct 2019.

References

307

Government of Zimbabwe. (2018b). Transitional Stabilisation Program Reforms Agenda: October 2018-December 2020, Towards a prosperous and empowered upper midle income society by 2030. Harare: Government of Zimbabwe Printers. Available: https://www.tralac.org/documents/resources/by-­country/zimbabwe/2347-­zimbabwe-­transitional-­stabilisation-­programme-­ abridged-­version-­5-­october-­2018/file.html. Accessed 14 Dec 2020. Government of Zimbabwe. (2020). National Development Strategy 1: Towards a prosperous and empowered upper midle income society by 2030. Harare: Government of Zimbabwe Printers, Available: http://www.zimtreasury.gov.zw/index.php?option=com_phocadownload& view=category&download=335:national-­development-­strategy-­1-­2021-­2025&id=64:national-­ development-­strategy-­1&Itemid=789. Accessed 14 Dec 2020. Grisham, T. (2009). The Delphi technique: A method for testing complex and multifaceted topics. International Journal of Managing Projects in Business, 2(1), 112–130. Guadix, J., Carrillo-Castrillo, J., Onieva, L., & Navascués, J. (2016). Success variables in science and technology parks. Journal of Business Research, 69(2016), 4870–4875. Guerrero, M., Urbano, D., Alain, F., Klofsten, M., & Mian, S. (2016). Entrepreneurial universities: Emerging models in the new social and economic landscape. Small Business Economics, 47, 551–563. Gupta, R., & Gupta, V. (2017). Constructivist approach in teaching. International Journal of Humanities and Social Sciences, 6(5), 77–88. Harish, V. S. K. V., & Kumar, A. (2016). A review on modeling and simulation of building energy systems. Journal of Renewable and Sustainable Energy Reviews, 56(2016), 1272–1292. Harrison, M. (2012). Jobs and growth: The importance of engineering skills to the UK economy. London: Royal Academy of Engineering. ISBN: 1-903496-92-6, Available: http://www.raeng. org.uk/publications/reports/jobs-­and-­growth. Accessed: 18 July 2016. Hausberg, J. P., & Korreck, S. (2020). Business incubators and accelerators: A co-citation analysis-­ based, systematic literature review. Journal of Technology Transfer, 45, 151–176. Hemelrijk, C. K., Wantia, J., & Gygax, L. (2005). The construction of dominance order: Comparing performance of five methods using an individual-based model. Behaviour, 142, 1037–1058. HIT (Harare Institute of Technology). (2020). School of industrial sciences and technology. Available: https://www.hit.ac.zw/industrial-­sciences-­and-­technology.html. Accessed 1 June 2020. Hong, J., Yeom, S., Eoh, J. H., Lee, T. H., & Jeong, J. Y. (2017). Heat transfer performance test of PDHRS heat exchangers of PGSFR using STELLA-1 facility. Nuclear Engineering and Design, 313(2017), 73–83. Hove, M. (2012). The debates and impact of sanctions: The Zimbabwean experience. International Journal of Business and Social Science, 3(5), 72–84. ICE (Institution of Civil Engineers) and GDC (Global Development Consultancy). (2002a). Report on the development of the engineering profession in Malawi. London: ICE and GDC. ICE (Institution of Civil Engineers) and GDC (Global Development Consultancy). (2002b). Report on the Development of the Engineering Profession in Mozambique. London: ICE and GDC. ICE (Institution of Civil Engineers) and GDC (Global Development Consultancy). (2002c). Report on the Development of the Engineering Profession in Tanzania. London: ICE and GDC. Ilyas, I.  P., & Semiawan, T. (2017). Industrial-Based Learning (IBL): Promoting excellence on polytechnics and vocational higher education. Journal Vokasi Indonesia, 5(1), 45–52. Inbound Logistics. (2016). Consumer products logistics: Driving shoppers to the mall. Available: http://www.inboundlogistics.com/cms/article/consumer-­products-­logistics-­driving-­shoppers-­ to-­the-­mall/. Accessed 25 Mar 2016. Iung, B., & Levrat, E. (2014). Advanced maintenance services for promoting sustainability. Procedia CIRP, 22, 15–22. Jamil, F., Ismail, K., & Mahmood, N. (2015). A review of commercialization tools: University incubators and technology parks. International Journal of Economics and Financial Issues, 5(Special Issue), 223–228. Jerome, N. (2013). Application of the Maslow’s hierarchy of need theory; impacts and implications on organizational culture, human resource and employee’s performance. International Journal of Business and Management Invention, 2(3), 39–45.

308

References

Johansson, A. (2009). Modelling and simulation of cone crushers. In 2009 IFAC Mining, Minerals and Metal Processing (IFAC MMM) conference, IFAC proceedings volumes (Vol. 42, No. 23, pp. 13–18). Ju, H. (2012). Design a training and maintenance system based on code identification. IERI Procedia, 1(2012), 155–159. Kádárová, J., Kalafusová, L., & Durkácová, M. (2014). Holistic system thinking as an educational tool using key indicators. Procedia – Social and Behavioral Sciences, 143(2014), 180–184. Kamaruddin, S., Khan, Z. A., Siddiquee, A. N., & Wong, Y. S. (2013). The impact of variety of orders and different number of workers on production scheduling performance: A simulation approach. Journal of Manufacturing Technology Management, 24(8), 1123–1142. Kanyarusoke, K.  E. (2016). Teaching engineering in Sub-Saharan Africa: The need for ‘Pracademics’. In Proceedings of the 6th African Engineering Education Association 2016 (AEEA2016) conference, Bloemfontein, South Africa, September 2016, pp. 153–159. Karjala, D., & Kiskis, M. (2011). Intellectual property within the university: The Lituanian and US Examples. Intellectual Economics, 1(9), 65–84. Karlsson, M., Nilsson, T., & Pichler, S. (2013). The impact of the 1918 Spanish Flu epidemic on economic performance in Sweden. Working Paper Series 911. Research Institute of Industrial Economics. Available: http://ideas.repec.org/p/hhs/iuiwop/0911.html. Accessed 30 April 2020. Katila, R., Chen, E. L., & Piezunka, H. (2012). All the right moves: How entrepreneurial firms compete effectively. Strategic Entrepreneurship, 6(2), 116–132. Kelly, T. J. C., & Firestone, R. S. (2016). How tech hubs are helping to drive economic growth in Africa. World Development Report Background Papers. Washington, DC: World Bank Group. Khalaf, A. B., Hamam, Y., Alayli, Y., & Djouani, K. (2013). The effect of maintenance on the survival of medical equipment. Journal of Engineering, Design and Technology, 11(2), 142–157. Khayut, B., Fabri, L., & Avikhana, M. (2014). Modeling of intelligent system thinking in complex adaptive systems. Procedia Computer Science, 36(2014), 93–100. Kim, J.  H., Jeong, S., Oh, S., & Jang, Y.  J. (2015). Verification, Validation, and Accreditation (VV&A) considering military and defense characteristics. Industrial Engineering & Management Systems, 14(1), 88–93. Kluczek, A. (2017). An overall multi-criteria approach to sustainability assessment of manufacturing processes. Procedia Manufacturing, 8(2017), 136–143. Koc, T., & Teker, S. (2019). Industrial revolutions and its effects on quality of life. PressAcademia Procedia (PAP), 9, 304–311. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development (Vol. I). Englewood Cliffs: Prentice-Hall. Koral-Kordova, S., & Frank, M. (2012). Improving capacity for engineering systems thinking (CEST) among industrial engineering students. In IEEE international conference on industrial engineering and engineering management (pp. 1378–1380). Hong Kong, Dec 2012. Kramarenko, V., Engstrom, L., Verdier, G., Fernandez, G., Oppers, S. E., Hughes, R., McHugh, J., & Coats, W., (2010). Zimbabwe: challenges and policy options after hyperinflation. Washington: International Monetary Fund. ISBN 978-1-58906-997-8. Kunze, O., Wulfhorst, G., & Minner, S. (2016). Applying systems thinking to city logistics: A qualitative (and quantitative) approach to model interdependencies of decisions by various stakeholders and their impact on city logistics. Transportation Research Procedia, 12(2016), 692–706. Lasrado, V., Sivo, S., Ford, C., O’Neal, T., & Garibay, I. (2016). Do graduated university incubator firms benefit from their relationship with university incubators? Journal of Technology Transfer, 41(2), 205–219. Lawless, A. (2007). Numbers and needs in  local government: Civil engineering  – The critical profession for service delivery. Johannesburg: South African Institute of Civil Engineering (SAICE). Lawless, A., (2017). Numbers and needs in  local government: Where are we now? Civil Engineering, South African Institute of Civil Engineering (SAICE), 2016, 15–26.

References

309

Lee, C., Lee, D., & Sho, M. (2020). Effect of efficient triple-helix collaboration on organizations based on their stage of growth. Journal of Engineering and Technology Management, 58(2020), 101604. Lim, M. A. (2018). The building of weak expertise: The work of global university rankers. High Educ, 75, 415–430. Lindgren, E.  S. (2001). Sida’s support to Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA) Final Evaluation Report. Stockholm, Sweden: Swedish International Development Cooperation Agency (Sida). ISBN: 91-586-8824-2. Liotta, G., Kaihara, T., & Stecca, G. (2016). Optimization and simulation of collaborative networks for sustainable production and transportation. IEEE Transactions on Industrial Informatics, 12(1), 417–424. Loosemore, M., & Cheung, E. (2015). Implementing systems thinking to manage risk in public private partnership projects. International Journal of Project Management, 33(2015), 1325–1334. Lwakabamba, S. (2011). Initiative to build capacity in research and postgraduate training. World Journal of Science, Technology and Sustainable Development, 8(2/3), 241–249. Macauhub. (2013). Mozambique is 2nd largest recipient of public aid from Portugal. Available: http://www.macauhub.com.mo/en/2013/01/17/mozambique-­i s-­2 nd-­l argest-­r ecipient-­o f-­ public-­aidfrom-­portugal/. Accessed 23 April 2020. Madke, P. B., & Jaybhaye, M. D. (2016). Application of Pugh selection matrix for fuel level sensing technology selection. International Journal of Engineering Research, 5(2), 368–370. Makochekanwa, A. (2016). Zimbabwe to introduce Zimbabwe Bond Notes: reactions and perceptions of economic agents within the first seven days after the announcement. Munich Personal RePEc Archive, MPRA paper no. 71695, Munich. Available: https://mpra.ub.uni-­muenchen. de/71695/. Accessed 8 April 2017. Mangudya, J. (2016). Measures to deal with cash shortages and simultaneously stabilizing and stimulating the economy. Reserve Bank of Zimbabwe Policy Statement, Harare. Available: http://www.rbz.co.zw/assets/press-­s tatement%2D%2D-­m easures-­t o-­d eal-­w ith-­c ash-­ shortages%2D%2D-­04-­may-­2016.pdf. Accessed 7 April 2017. Marques, A. F., Alves, A. C., & Sousa, J. P. (2013). An approach for integrated design of flexible production systems. Procedia CIRP, 7(2013), 586–591. Martinez, V., Bastl, M., Kingston, J., & Evans, S. (2010). Challenges in transforming manufacturing organizations into product-service providers. Journal of Manufacturing Technology Management, 21(4), 449–469. Mascarenhas, C., Marques, C. S., Galvão, A. R., & Santos, G. (2017). Entrepreneurial university: Towards a better understanding of past trends and future directions. Journal of Enterprising Communities: People and Places in the Global Economy, 11(03), 316–338. Matthews, P., Ryan-Collins, L., Wells, J., Sillem, H., & Wright, H. (2012). Engineers for Africa: Identifying engineering capacity needs in Sub-Saharan Africa, analysis of stakeholder interviews. London: Royal Academy of Engineering. ISBN: 1-903496-91-8. McGrath, S., & Powell, L. (2015). Skills for sustainable development: Transforming vocational education and training beyond 2015. International Journal of Educational Development, 50(2016), 12–19. Meadows, D.  H. (2008). Thinking in systems. Chelsea Green Publishing, USA.  ISBN: 978-1-60358-055-7. Meybodi, M.  Z. (2013). The links between lean manufacturing practices and concurrent engineering method of new product development. Benchmarking: An International Journal, 20(3), 362–376. Mohajan, H. K. (2020). The second industrial revolution has brought modern social and economic developments. Journal of Social Sciences and Humanities, 6(1), 1–14. Mohamedbhai, G. (2017). The importance of polytechnics for Africa’s development. International Higher Education, 30, 30–31. Mohammed, Y. S., Mustafa, M. W., & Bashir, N. (2013). Status of renewable energy consumption and developmental challenges in Sub-Saharan Africa. Renewable and Sustainable Energy Reviews, 27(2013), 453–463.

310

References

Monyau, M.  M., & Bandara, A. (2017). Zimbabwe 2017. African Economic Outlook. Abidjan, African Development Bank. Available: www.africaneconomicoutlook.org. Accessed 4 Feb 2018. Munangagwa, C. L. (2011). The economic collapse of Zimbabwe. Gettysburg Economic Review, 3(1), 110–129. Munyoro, G., Nyandoro, Z. F., & Musekiwa, M. (2016). An evaluation of the student industrial attachment programme in Zimbabwe: A case study for Chinhoyi University of Technology. International Journal of Research in Business Management, 4(8), 1–16. Murangwa, S. I., & Njaya, T. (2016). The effects of Statutory Instrument 64 of 2016 on clearing agents based at Beitbridge Border Post in Zimbabwe. International Journal of Business and Management Invention, 5(11), 45–49. Murangwa, S.  I., & Njaya, T. (2017). An evaluation of the effects of Statutory Instrument 64 of 2016 on Zimbabwe’s neighbours. International Journal of Management and Commerce Innovations, 5(1), 1–9. Muzira, D. R., & Bondai, B. M. (2020). Perception of Educators towards the Adoption of Education 5.0: A Case of a State University in Zimbabwe. East African Journal of Education and Social Sciences, 1(2), 43–53. Mwamila, B. L. M., & Thulstrup, E. W. (Eds). (2001). Engineering and technology for sustainable development – Research, education and development. In Proceedings of a Regional Meeting, Bagamoyo, Tanzania, October 17–21. Mwanga, A., Parian, M., Lamberg, P., & Rosenkranz, J. (2017). Comminution modelling using mineralogical properties of iron ores. Minerals Engineering, 111, 182–197. Nahavandi, S. (2019). Industry 5.0 – A human centric solution. Sustainability, 11, 1–13. Narasimha, M., Mainza, A.  N., Holtham, P.  N., Powell, M.  S., & Brennan, M.  S. (2014). A semi-mechanistic model of hydrocyclones – Developed from industrial data and inputs from CFD. International Journal of Mineral Processing, 133, 1–12. Negahban, A., & Smith, J. S. (2014). Simulation for manufacturing system design and operation: Literature review and analysis. Journal of Manufacturing Systems, 33(2014), 241–261. Nguyen, D. Q., & Pudlowski, Z. J. (2007). Issues and challenges in engineering education and the future outlook of the engineering profession in Australia. Global Journal of Engineering Education, 11(2), 107–116. Nimbulkar, S. L., & Dalu, R. S. (2016). Design optimization of gating and feeding system through simulation technique for sand casting of wear plate. Perspectives in Science, 8(2016), 39–42. Nuvolari, A. (2019). Understanding successive industrial revolutions: A “development block” approach. Environmental Innovation and Societal Transitions, 32(2019), 33–44. Nyanga, T., Mpala, C., & Chifamba, E. (2012). Brain drain: implications for sustainable development in Zimbabwe. Journal of Sustainable Development in Africa, 14(8), 141–153. Nyemba, W. R. (2017). Engineering skills are the key to achieving sustainable development and reducing foreign aid dependency. Huffington Post (UK) (2017). Available: http://www.huffingtonpost.co.uk/wilson-­nyemba/engineering-­skills-­are-­th_b_14135774.html. Accessed 6 June 2018. Nyemba, W.  R. (2018). Modelling the integration of engineering design and manufacture for capacity building and sustainability. Doctor of Engineering (D.Eng.) Thesis (Mechanical Engineering), University of Johannesburg, Available on UJ Institutional Repository. https:// ujcontent.uj.ac.za/vital/access/manager/Repository/uj:31939 using the object handler: http:// hdl.handle.net/10210/293682 Nyemba, W. R., & Mbohwa, C. (2018). Smart and strategic procurement, use and maintenance partnerships in engineering equipment for sustainable development and training in Sub-­ Saharan Africa using a systems thinking approach. In Proceedings: ACRID 2017 European Alliance for Innovation (EAI) International conference for research, innovation and development for Africa, 20–21 June 2017, Victoria Falls, Zimbabwe, pp. 149–158. European Alliance for Innovation. ISBN: 978-1-63190-160-7. https://doi.org/10.4108/eai.20-­6-­2017.2270632.

References

311

Nyemba, W. R., Mashamba, A., & Mbohwa, C. (2017). Equipment maintenance challenges and solutions for capacity building and sustainability in the training of engineers: the case for the University of Zimbabwe. Procedia Manufacturing, 7(2017), 303–308. Nyemba, W. R., Carter, K. F., Mbohwa, C., & Chinguwa, S. (2019). A systems thinking approach to collaborations for capacity building and sustainability in engineering education. Procedia Manufacturing, 33(2019), 732–739. Nyemba, W.  R., Chikuku, T., Chiroodza, J.  R., Dube, B., Carter, K.  F., Ityokhumbul, M.  T., & Magombo, L. (2020). Industrial design thinking and innovations propelled by the Royal Academy of Engineering in Sub-Saharan Africa for capacity building. Procedia CIRP, 91(2020), 770–775. OECD (Organisation for Economic Co-operation and Development). (2016). Evaluation systems in development co-operation: 2016 review. Paris: OECD Publishing. ISBN: 978-92-64-26205-8. Okrent, M.  D., & Vokurka, R.  J. (2004). Process mapping in successful ERP implementations. Journal of Industrial Management & Data Systems, 104(8), 637–643. Oliver, J., Vesty, G., & Brooks, A. (2016). Conceptualising integrated thinking in practice. Managerial Auditing Journal, 31(2), 228–248. Ott, T. (2020). Isaac Newton changed the world while in quarantine from the plague. Biography. com. Available: https://www.biography.com/news/isaac-­newton-­quarantine-­plague-­ discoveries. Accessed 20 Dec 2020. Palaima, T., & Skarzauskiene, A. (2010). Systems thinking as a platform for leadership performance in a complex world. Baltic Journal of Management, 5(3), 330–355. Pana, X., Valerdi, R., & Kang, R. (2013). Systems thinking: A comparison between Chinese and western approaches. Procedia Computer Science, 16(2013), 1027–1035. Patil, A. M., & Kudte, S. S. (2017). Teaching learning with constructivist approach. International Journal of Engineering Development and Research, 5(4), 308–312. Paton, R. A., Wagner, R., & MacIntosh, R. (2012). Engineering education and performance: The German machinery and equipment sector. International Journal of Operations & Production Management, 32(7), 796–828. Pazos, D. R., López, S. F., González, L. O., & Sandiás, A. R. (2012). A resource-based view of university spin-off activity: New evidence from the Spanish case. European Journal of Business Management and Economics, 21(2012), 255–265. Penprase, B.  E. (2018). Chapter 9: The fourth industrial revolution and higher education. In N.  W. Gleason (Ed.), Higher education in the era of the fourth industrial revolution (pp. 207–228). Singapore: Springer. Perez-Foguet, A., Lazzarini, B., Gine, R., Velo, E., Boni, A., Sierra, M., Zolezzi, G., & Trimingham, R. (2018). Promoting sustainable human development in engineering: Assessment of online courses within continuing professional development strategies. Journal of Cleaner Production, 172(2018), 4286–4302. Peters, M. A. (2017). Technological unemployment: Educating for the fourth industrial revolution. Journal of Self-Governance and Management Economics, 5(1), 25–33. Phan, P. H., Siegel, D. S., & Wright, M. (2005). Science parks and incubators: Observations, synthesis and future research. Journal of Business Venturing, 20(2005), 165–182. Qiu, Y., He, Y. L., Wu, M., & Zheng, Z. J. (2016). A comprehensive model for optical and thermal characterization of a linear Fresnel solar reflector with a trapezoidal cavity receiver. Renewable Energy, 97(2016), 129–144. RAEng (Royal Academy of Engineering). (2017a). Enriching Engineering Education Programme (EEEP). Available: https://www.raeng.org.uk/publications/other/enriching-­engineering-­ education-­programme. Royal Academy of Engineering. Accessed 20 Mar 2018. RAEng (Royal Academy of Engineering). (2017b). Higher Education Partnerships for Sub Saharan Africa (HEP SSA). London: Royal Academy of Engineering. Available: https://www. raeng.org.uk/RAE/media/Grantapplications-­and-­guidelines/HEP%20SSA/Higher-­Education-­ Partnershipin-­sub-­Saharan-­Africa-­(HEP-­SSA)-­Guidance-­Notes.pdf. Accessed 20 Oct 2019.

312

References

Rahani, A. R., & Muhammad, A. A. (2012). Production flow analysis through value stream mapping: A lean manufacturing process case study. Procedia Engineering, 41, 1727–1734. Rao, R. V., Kalyankar, V. D., & Waghmare, G. (2014). Parameters optimization of selected casting processes using teaching–learning-based optimization algorithm. Applied Mathematical Modelling, 38(2014), 5592–5608. Ray, S., & Srivastava, S. (2020). Virtualization of science education: A lesson from the COVID-19 pandemic. Journal of Proteins and Proteomics, 11, 77–80. Raza-Ullah, T., Bengtsson, M., & Kock, S. (2014). The coopetition paradox and tension in coopetition at multiple levels. Industrial Marketing Management, 43(2014), 189–198. Ritala, P., Golnam, A., & Wegmann, A. (2014). Coopetition-based business models: The case of Amazon.com. Industrial Marketing Management, 43(2014), 236–249. Rolón, M., & Martínez, E. (2012). Agent-based modeling and simulation of an autonomic manufacturing execution system. Journal of Computers in Industry, 63(2012), 53–78. Runhaar, P., & Sanders, K. (2015). Promoting teachers’ knowledge sharing. The fostering roles of occupational self-efficacy and human resources management. Educational Management Administration & Leadership, 44(5), 794–813. Rybicka, J., Tiwari, A., Campo, P. A. D., & Howarth, J. (2015). Capturing composites manufacturing waste flows through process mapping. Journal of Cleaner Production, 91(2015), 251–261. Saadatian, O., Tahir, O. M., & Dola, K. (2010). Identifying challenges in implementing sustainable practices in a developing nation. Journal of Sustainable Development, 3(2), 107–116. SADC. (2014). Integrated paper on recent economic developments in the Southern African Development Community. Central Bank of Lesotho. Available, https://www.sadcbankers. org/Lists/News%20and%20Publications/Attachments/195/Integrated%20Paper%20-­%20 Aug%202014%20Final.pdf. Accessed 8 Mar 2017. Sætre, A., Wiggins, J., Atkinson, O. T., & Atkinson, B. K. E. (2009). University Spin-OFFS as technology transfer: A comparative study among Norway, the United States, and Sweden. Comparative Technology Transfer and Society, 7(2), 115–145. Sagawa, J. K., & Nagano, M. S. (2015). Modelling the dynamics of a multi-product manufacturing system: A real case application. European Journal of Operational Research, 244(2015), 624–636. Sajjad, M., & Rasul, M. G. (2015). Simulation and optimization of solar desalination plant using ASPEN plus simulation software. Procedia Engineering, 105(2015), 739–750. Saurin, T.  A. (2016). Safety inspections in construction sites: A systems thinking perspective. Accident Analysis & Prevention, 93(2016), 240–250. Schiuma, G., Sole, F., & Carlucci, D. (2012). Applying a systems thinking framework to assess knowledge assets dynamics for business performance improvement. Expert Systems with Applications, 39(9), 8044–8050. Schwab, K. (2016). The fourth industrial revolution: What it means, how to respond. World Economic Forum 2016. Davos: WEF.  Available: https://www.weforum.org/agenda/2016/01/ the-­fourth-­industrial-­revolution-­what-­it-­means-­and-­how-­to-­respond/. Accessed 2 May 2020. Senge, P. (2006). The fifth discipline: The art and practice of the learning organization. London: Random House Business Books. ISBN: 9781905211203. Shanker, D. (2017). Academic entrepreneurship in India. Journal of Entrepreneurship and Management, 6(2), 9–19. Singh, R. K., Choudhury, A. K., Tiwari, M. K., & Maull, R. S. (2006). An integrated fuzzy-based decision support system for the selection of lean tools: a case study from the steel industry. Proceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture, 220(10), 1735–1749. Smith, S., Hamilton, M., & Fabian, K. (2020). Entrepreneurial drivers, barriers and enablers of computing students: Gendered perspectives from an Australian and UK university. Studies in Higher Education, 45(9), 1892–1905. Sooreh, L. K., Salamzadeh, A., Safarzadeh, H., & Salamzadeh, Y. (2011). Defining and measuring entrepreneurial universities: A study in Iranian context using importance-performance analysis and TOPSIS technique. Global Business and Management Research, 3(2), 182–199.

References

313

Sreeram, T. R., & Thondiyath, A. (2015). Combining Lean and Six Sigma in the context of systems engineering design. International Journal of Lean Six Sigma, 6(4), 290–312. Staniskis, J. K., & Katiliute, E. (2016). Complex evaluation of sustainability in engineering education: case & analysis. Journal of Cleaner Production, 120(2016), 13–20. Steruska, J., Simkova, N., & Pitner, T. (2019). Do science and technology parks improve technology transfer? Technology in Society, 59(2019), 101127. Steyn, C. W., & Brooks, K. S. (2017). De-bottlenecking of the Anglo platinum converting process utilizing advanced process control. IFAC-Papers Online, 50–2, 1–6. Teferra, D. (2013). Funding higher education in Africa: State, trends and perspectives. Journal of Higher Education in Africa, 11(1–2), 19–51. Tengende, K., Mushiri, T., & Garikayi, T. (2014). Finite element analysis of the RoM Silo subjected to 5000 tons monotonic loads at an anonymous mine in Zimbabwe. In Proceedings of the International conference on challenges in IT, Engineering and Technology (ICCIET’2014), July 17–18, Phuket, Thailand, pp. 79–84. Times Higher Education. (2010). World university rankings subject tables: Robust, transparent and sophisticated. Available: https://www.timeshighereducation.com/world-­university-­ rankings/2010-­11/world-­ranking/analysis/methodology. Accessed 27 Nov 2020. Tvrdon, L., & Juraskova, K. (2015). Teaching simulation in logistics using WITNESS and captivate software. Procedia – Social and Behavioral Sciences, 174, 4083–4089. Uhly, K. M., Visser, L. M., & Zippel, K. S. (2017). Gendered patterns in international research collaborations in academia. Studies in Higher Education, 42(4), 760–782. UJ (University of Johannesburg). (2020). Institute for intelligent systems. University of Johannesburg. Available: https://www.uj.ac.za/faculties/febe/iis. Accessed: 16 Dec 2020. UNESCO. (2010). Engineering: Issues, challenges and opportunities for development. Paris: UNESCO Publishing. ISBN: 978-92-3-104156-3. University of Warwick. (2017). Ministers announce £4.25 Million funding for battery and autonomous vehicle research at WMG. Warwick News and Events. University of Warwick. Available: https:// warwick.ac.uk/newsandevents/pressreleases/ministers_announce_163425/?fbclid=IwAR300 GlPpUppRAcwl0jaU0qiob3DhKGAVfduoB8s9ZCvPrNSRAPHUZwGI4c. Accessed 4 Dec 2020. UZ (University of Zimbabwe), (2013), University of Zimbabwe 2013 Annual Report. Harare: University of Zimbabwe Publications Vamanan, M., Wang, Q., Batta, R., & Szczerba, R.  J. (2004). Integration of COTS software products ARENA & CPLEX for an inventory/logistics problem. Computers & Operations Research, 31(2004), 533–547. Van Horenbeek, A., Bure, J., Cattrysse, D., Pintelon, L., & Vansteenwegen, P. (2013). Joint maintenance and inventory optimization systems: A review. International Journal of Production Economics, 143(2013), 499–508. Vanderstraeten, J., van Witteloostuijnb, A., Matthyssens, P., & Andreassi, T. (2016). Being flexible through customization. The impact of incubator focus and customization strategies on incubatee survival and growth. Journal of Engineering Technology Management, 41(2016), 45–64. Vasanthi, S., & Basariya, S.  R. (2019). On the job training implementation and its benefits. International Journal of Research and Analytical Reviews, 6(1), 210–215. Vinodh, S., Arvind, K.  R., & Somanaathan, M. (2010). Application of value stream mapping in an Indian camshaft manufacturing organization. Journal of Manufacturing Technology Management, 21(7), 888–900. Wang, J., Chang, Q., Xiao, G., Wang, N., & Li, S. (2011). Data driven production modelling and simulation of complex automobile general assembly plant. Computers in Industry, 62(2011), 765–775. Wang, W., Liu, W., & Mingers, J. (2015). A systemic method for organisational stakeholder identification and analysis using Soft Systems Methodology (SSM). European Journal of Operational Research, 246(2), 562–574.

314

References

Warner, A. L., Chaudhary, A. K., & Lamm, A. J. (2016). Using importance-performance analysis to guide extension needsa ssessment. Journal of Extension, 54(6), Available: https://joe.org/ joe/2016december/pdf/JOE_v54_6a1.pdf. Accessed 20 Dec 2020. Warren, T. (2020). Why the 5G coronavirus conspiracy theories don’t make sense. The Verge. Available: https://www.theverge.com/2020/4/9/21214750/5g-­coronavirus-­conspiracy-­ theories-­radio-­waves-­virus-­internet. Accessed 6 May 2020. Weiblen, T., & Chesbrough, H. W. (2015). Engaging with startups to enhance corporate innovation. California Management Review, 57(2), 66–90. Williams, D. (2013). Chapter 10: Building a support infrastructure for technology-based businesses: What can emerging economies learn from the western experience? In R.  Oake, A. Groen, G. Cook, & P. van der Sijde (Eds.), New technology-based firms in the new millennium. Bingley: Emeral Group Publishing, ISBN: 978-1-78190-315-5. Williams, D. T., Beasley, R., & Gibbons, P. M. (2013). Combining hard and soft system thinking: the development of a value improvement model for a complex linear friction welding repetitive process (lfw-VIM). Procedia Computer Science, 16(2013), 1007–1016. Wood, A. E., Wood, C. D., & Mattson, C. A. (2014). Application and modification of design for manufacture and assembly principles for the developing world. In Proceedings of IEEE Global humanitarian technology conference, pp. 451–457. World Bank. (2002). Financing vocational training to meet policy objectives: Sub-Saharan Africa. Africa region human development working paper series. Washington DC: World Bank Group. World Bank. (2010). Reform and regional integration of professional services in East Africa: Time for Action. World bank report No. 57672-AFR.  Washington: World Bank. Available: http://siteresources.worldbank.org/INTAFRREGTOPTRADE/Resources/ NEWReformProfessionaServicesEAC Report.pdf World Bank. (2014). Improving the quality of engineering education and training in Africa. In Science, technology, and skills for Africa's development. Washington DC: World Bank Group. World Bank. (2020). COVID-19 Crisis: Through a migration lens. In Migration and development brief 32. Washington DC: World Bank Group. Yang, J. B., Yang, C. C., & Kao, C. K. (2010). Evaluating schedule delay causes for private participating public construction works under the Build-Operate-Transfer model. International Journal of Project Management, 28(2010), 569–579. Yeh, C.  W., Li, D.  D., & Zhang, Y.  R. (2012). Estimation of a data-collection maturity model to detect manufacturing change. Journal of Expert Systems with Applications, 39(2012), 7093–7101. Yianatos, J., Carrasco, C., Bergh, L., Vinnett, L., & Torres, C. (2012). Modelling and simulation of rougher flotation circuits. International Journal of Mineral Processing, 112–113, 63–70. Zhang, Q., Kang, N., & Barnes, R. (2016). A systematic literature review of funding for higher education institutions in developed countries. Frontiers of Education in China, 11(4), 519–542. Zimbabwe Institution of Engineers. (2015). The Zimbabwe Engineer. Vol. 77, No. 1. Available: http://www.wfeo.org/wp-­content/uploads/stc-­anticorruption/The_Zimbabwe_Engineer_-­_ December_2015.pdf. Accessed 12 May 2020. Zimbabwe Revenue Authority (ZIMRA). (2017). Statutory Instrument 64. In Value Added Tax Chapter 23:12, pp. 447–448. Harare, Zimbabwe Government Printers. Zimstat. (2014). Balance of payment and national accounts. In Facts and Figures 2014, pp 10–12. Harare, Zimbabwe: Zimbabwe National Statistics Agency (Zimstat) Accessed 16 June 2017. http://www.zimstat.co.zw/sites/default/files/img/publications/Other/FACT_2014.pdf Zinyemba, R. (Ed.). (2010). Academia and the dynamics of transformative leadership: The experience of the University of Zimbabwe in the first decade after Zimbabwe’s Independence (1981-1992). Harare: University of Zimbabwe Publications. Zunino, C., Valenzano, A., Obermaisser, R., & Petersen, S. (2020). Factory communications at the dawn of the fourth industrial revolution. Computer Standards & Interfaces, 71(2020), 103433.

Index

A Academia–industry partnerships academics, 58 collaborations, 58–60 (see also Collaborations in SA) CPD, 58, 72–73 engineering profession, 58 financial capacity, 58 industrial secondments, 68–70 interactions with captains of industry, 76, 78 international backstopping, 75–76 project resources and equipment, 74–75 Academia transformations, 29 Digital Revolution, 29 economic landscape, 22 engineering education and training, 27 Europe and USA, 19 innovations and inventions, 21 IR stages, 23 manufacturing technology, 22 polytechnics, 31 resultant effect, 22 technological, 21 Academics, 112 Acceptable international practice, 33 Accreditation, 33 Accredited programmes, 292 Acquisition of Skills loop (Balancing – B), 50 Adjunct appointments adjunct/visiting professorships, 159, 160 engineering academics, 158 human resources development, 165 Mauritius, 158

professorial chairs, 159 Southern Africa governments, 158 industrial training board, 158 Adjunct/visiting professorships, 159, 160 Africa-UK Partnership for Development, 4 Agro-industrial park, 242, 243 Analog process control simulator, 169 Appropriate skills, 146, 162 Architectural modelling, 108 Arena, 42 and Limn Flowsheet Processor, 112 model, 127 Arena Simulation Software, 138 Attachments, 69 Attributes, 71, 72 AutoCAD 2012, 126 Automated guided vehicles (AGVs), 260 Automation, 20, 29, 34, 36, 37 B Backstopping, 75 Balancing feedback, 55 Balancing feedback loops, 44 Base metal refinery (BMR), 278 Binary Dominance Matrix (BDM), 85 Bridge ET, 258–261 integrated UST model, 266–269 model verification and validation, 269–271 PDP systems thinking sub-model, 264–266 skills development and training, 262–264

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 W. R. Nyemba et al., Bridging the Academia Industry Divide, EAI/Springer Innovations in Communication and Computing, https://doi.org/10.1007/978-3-030-70493-3

315

316 Build-Operate-Transfer (BOT), 75, 178, 259, 280–282, 293 BOT scheme, 178 engineers and industry, 179 national government, 178 PPPs, 179 public and private entities, 178 situational analysis, 179 useful information, 179 Business acceleration, 211, 214, 216 Business enterprise, 107 Business incubation, 212, 214–216, 223, 226 business incubators and accelerators, 214 classification, incubators, 215 description, 212 entrepreneurships and spin-off companies, 213 HEIs and research institutions, 213 incubation performance and impacts, 217 incubation process and selection, 216 investors, 212 variable parameters, 212 viability and feasibility, 212 Business management system (BMS), 149 Business operations, 108 Business proposals, 249–251 C Capacities, 300 Capacity building, engineering education automation, 152 company vs. tertiary institutions, 151 implementation plan, 150 industry vs. higher education institutions, 150, 151 institutional training policies, 150 joint and industry-based projects and shared resources, 152 maintenance and occasional improvements, 151 operations level, 152 platinum mining and processing company, 151 scaled-down operations, 151 shared mentorship, students, 153 Southern Africa, 150 tertiary institutions, 150 Capacity building and sustainability, 279–280 Capacity building initiatives, 293 Capacity utilisation, industry appropriate skills, 146 automation, 149

Index base metal refinery, 149 boilermaking company, 148 corporate social responsibility schemes, 149 economic recession, 149 factors, 148 foreign ownership, 149 hazardous waste, 150 materials, 148 productivity, 150 respondent categories, 149 staffing levels, 147 transportation distances, 149 Capital investment, 214, 223, 226 Captains of industry, 77 Case study companies, 12 Causal loop flow diagrams, 49–51 Centre for Minerals Research (CMR), 219, 220 Centres of excellence, 153, 158, 165, 210 Challenges, 274, 276, 278, 280, 281, 283, 286–288 Chinhoyi University of Technology, 96, 97 Civil and Mechanical Engineering, 176 Collaborating institutions, 11 Collaborations, 4, 9, 60, 205 COVID-19 pandemic, 193 in higher education, 190, 193 virtual laboratories, 193 Collaborations in SA assessments, 62 ‘brain drain’ and migration, 62 challenges, 62 industrial attachments, 60 industrialised/industrialising, 60 key resolutions and drivers, 66, 67 knowledge-sharing workshops, 62–64 mismatch of skills, 61 NUSESA, 60 semi-industrialised, 62 sharing of resources under distress, 64–65 statistics, 61 tertiary institutions, 60 University of Zimbabwe engineering graduation, 61 Commercialisation, 210, 213, 214, 223, 228 and industrialisation, 230–231 knowledge and technology transfer, 233, 234 spin-offs, 235 start-ups, 235 support infrastructure, 238, 239 triple helix, 230

Index Community service, 282–285 Competences, 72 Complexities, 34, 36, 37 Computer numerically controlled (CNC) machines, 73, 176, 258, 259, 279 Conceptual frameworks, 54 Conceptualise-Design-Implement-Operate (CDIO), 31, 37, 94 Connecting activities, 72 Constraints, 285, 286 Continuity of donor-funded projects, 163, 164 Continuous casting machine (CCM), 259 Continuous Professional Development (CPD), 58, 72, 73, 199, 295, 299 Control and experimentation, 261, 262, 266, 268, 283 Conventional machine tools, 256 Coopetitions, 189, 191, 192, 194, 204–206 benefits and performance, 195 concept, 194 models, 190 tertiary institutions, 194 use, 194 COVID-19 pandemic, 185, 192, 206, 258, 273, 288 Critical thinking, 85 Customisation, 225 business incubation, 226 flexibility challenges, 226 and optimisation, 226 and segmentation, 226 of services, 226 D Decision-making, 205 Department for International Development (DFID), 4 Design for Manufacture and Assembly (DFMA), 10 Digital Ecosystem, 103, 202, 255, 292 Digital Revolution, 27 Doctoral Training Centres (DTC), 276 career prospects and opportunities, 153 centres of excellence, 153, 165 funds, 155 government grants and funding, 155 implementation, 157, 158 industry funding, 155 investment, 153 laboratory equipment, 153 self-sustenance, 157, 158 Southern Africa, 156

317 Sub-Saharan Africa (SSA), 154, 155 sustainability, 156 top-down approach, 153 UK perspective, 153, 154 Double degrees, 32, 37 Double majors, 32, 37 Dynamic modelling, 108 Dynamic trends, 199, 204 E Econet Wireless, 198 Ecosystem, 274 Education 5.0 system, 35, 232, 241 Electrical installations, 283 Energy, 156 Engineering academics, 26, 33, 35, 37, 62, 146, 147, 158, 160 Engineering and manufacturing companies, 13 Engineering and Physical Sciences Research Council (EPSRC), 154 Engineering capacity, 4 Engineering change management, 43, 44, 55 Engineering education, 251, 274, 293 academics and students, 3 microchips, 3 ODA, 2 OEMs, 3 sustainability, 2 transformations, 27–29 western governments, 2 Engineering practices, 279 questionnaire and survey, 297, 298 Engineering skills, 1, 164 development and training, 256, 262–264 EEEP, 9 engineering academics and industry, 9 industry and academia, 10 NUSESA end-of-project report, 8 population count, 8 Engineering systems, 43 Engineering systems thinking, 44 Engineering training and policies collaborations in SA, 33 double degrees, 32 double majors, 32, 37 polytechnics to universities, 30 shortages and mismatch, skills, 31 Engineers, 108 Enriching Engineering Education Program (EEEP), 3–5, 150, 151, 159, 164, 165, 195 Entrepreneurial programmes, 245

318 Entrepreneurial universities, 244–247, 251 Entrepreneurships, 213, 216, 228, 294 in academia, 231 business incubators, 249 business proposals, 249 models and mechanisms, 239–241 obstacles to academia entrepreneurship, 248 in Southern Africa, 241–243 stimulants for academia entrepreneurship, 247–248 tertiary institutions, 232 unsolicited proposals, 249 Equipment and Technology (ET), 258–262, 264, 266, 268–270 ET sub-models, 260 ET systems thinking sub-model, 260, 262 European Development Fund (EDF), 242 Eventual simulation, 108 F Feedback loops, 45, 48–50, 52 Face-to-face education, 37 Fixed parameters, 109 Flexibility, 226 Food Science and Technology (FST), 221, 222 Foreign funding agents, 242 Foundry efficient production, 125, 129 engineering academics’ interventions, 130 engineering operations, 125 flow of materials, 125 global financial crisis, 126 machine tools, 126 optimisation, 128, 129 railway industry, 126 recommendations, 130 research methodology, 126–128 results, 128, 129 state-of-the-art, 126 Zimbabwe, 126 Fourth Industrial Revolution, 164 Functional block diagrams, 108 Funding, 157 Furniture manufacturing plant, 113, 114 G Gating system, 133, 134 Geoinformatics, 5 Global Challenges Research Fund (GCRF), 164 Global financial crisis, 168, 192

Index Global System for Mobile Communications (GSM), 183–184 Gross domestic product (GDP), 6 Groundwater enterprise, 285 model, 283, 284 project, 289 Group technology, 116 H Harare Institute of Technology (HIT), 95, 221 Higher education institutions (HEI), 2, 190 Higher Education Partnerships EEEP, 196 HEP SSA, 197 NUSESA and EEEP coopetition, 195, 197 Higher Education Partnerships for Sub-­ Saharan Africa (HEP SSA), 164, 165 cooperative manner, 199 coopetition model, 201, 202 COVID-19 restrictions, 199 EEEP, 197, 201 engineering academics, 200 industrialisation and innovation, 202 initiative, 197 local governments, 197 partner institutions, 201 partnership, 197 and SAE2Net, 197, 199, 203 High Pressure Grinding Rolls (HPGR), 136, 140 Human resources development, 257 I Importance-performance analysis (IPA), 244, 245 Incubation and product development, 210 performance, 225 systems thinking process, 227 Industrial attachments, 60, 69 Industrial Design Thinking (IDT), 90 Industrial evolution, 12 Industrial practices, 279 Industrial revolutions (IRs), 107, 110, 170, 174, 176, 199, 230, 231, 233, 236, 241, 251, 255, 256, 258 academic and technological attributes, 27 first, 19 4IR, 26, 27 origins and transformations, 21–22 research and development, 21

Index second, 20 successive stages, 21 transformations in other sectors, 22 Industrial secondments, 68–71, 78 Academia Industry Secondments, 99, 100 academics, 98 criteria, 99 postdoctoral research, 98 United Kingdom, 98 Industrial technology parks, 218 See also Innovation hub Industrial transformations, 57, 292 Industrialisation, 20, 23, 24, 29, 35 agro-industrial park, 240 and commercialisation, 234 development, 231 Education 5.0, 232, 233 entrepreneurships, 230, 241 in academia, 231, 232 IPR, 236, 237 SAE2Net partnership, 239 spin-off, 235 support infrastructure, 238, 239 transformations, 231 TTOs, 240 Zimbabwe’s establishment, 232 Industrialising environment, 10, 108 Industry-Academic Partnership Program (IAPP), 153 Industry-based learning (IBL), 5, 33, 35, 37, 38, 104 academia, 90 academic qualifications, 90 basics of engineering, 90 Chinhoyi University of Technology, 96, 97 efforts, 91 evaluation, 92, 93 formulation, 92, 93 global financial crisis, 89 Harare Institute of Technology (HIT), 95 Industrial Revolutions, 89, 91 industry partnerships, 90 industry perspective, 89 learning, 89 Namibia University of Science and Technology, 95–97 polytechnics, 91 Royal Academy of Engineering, 90 skills, 90, 91 students, 90 systems thinking synchronisation, 102, 103 teaching, 89 technical colleges, 91

319 tertiary education, 90 tertiary institutions, 90 Universidade Eduardo Mondlane, 94 University of Johannesburg, 93, 94 University of Zimbabwe, 98 Industry-based projects, 4, 13 Industry-funded projects, 157 Industry 4.0 (4IR), 26, 27 Industry 5.0, 27 Industry funding, 155 Innovation hubs, 218, 219, 221, 223–225, 227 and agro industrial park, 219 CMR, 219, 220 collaboration, 213 FST, 221, 222 IIS, 220 renewable energy, 222, 223 success, 211 TDC, 221 Innovations, 21, 26, 34–36, 38 Innovative entrepreneurship, 239 Innovators business incubators, 215 corporate incubators, 215 and customers, 226 and entrepreneurs, 214, 217 and external expertise, 226 impact of incubators, 217 incubation systems thinking process, 227 and incubators, 225 and investors, 214 programmes for mentorship, 214 Institute for Intelligent Systems (IIS), 220 Integrated management systems, 24 Integrated systems thinking approach, 257 Integrated UST model, 266–269, 271, 275 Integration, 22, 26, 37 Intellectual property rights (IPR), 231, 236, 237, 240, 242 Interconnected system, 44 International assistance, 76 International backstopping, 75, 76 International Conference for Manufacturing Engineering and Engineering Management, 119 Internationalisation, 33, 293 Intra-institutional coopetition, 197 Inventor entrepreneur model, 235 K Knowledge sharing, 59, 62, 66, 193 Knowledge-sharing workshops, 62

320 L Laboratory equipment, 60, 64, 73 Limitations, 276, 285–287 Limn Flowsheet Processor, 138, 140 Local Area Networks (LAN), 29 Looping feedback, 266, 269, 271 M Machine distance matrix, 117 Macroeconomic situations academia and industry, 8 economic sanctions, 6 engineering and manufacturing, 5 foreign currency cash, 7 holistic approach, 8 local manufacturers, 8 SADC gross domestic product, 7 SADC region, 6 Zimbabwean currency, 6 Maintenance expertise, 175 Manpower Development Act, 276 Mauritius authorities, 31 Mechanical Engineering, 196 Modelling systems, 108, 109 Mineral processing, 220 Arena and Limn Flowsheet Processor, 141 comminution and flotation circuits, 139, 140 cycle time analysis, 139 experimentation, 137–139 flotation circuit, 140 logical movements, 140 machines, 139 mining and mineral processing, 135 optimum peak, 140 platinum, 135 platinum mining, 135, 141 process flows, 135 processing cycle, 135 research methodology, 135, 136, 138 resource utilisation, 140 simulation, 137–139 sustainable platinum production, 141 valuable minerals, 135 Model validation, 258, 269, 270 Model verification, 258, 269, 270 Modern technology capacity building, 168 collaboration, 168 equipment, 168, 169 industry and academia, 169

Index laboratories, 168 laboratory equipment, 168 machines, 169 NUSESA, 168 obsolescence, 168 Multi-product assembling plant analysis, 119 baby tenders, 125 data, 125 multiplicity, 119 recommendations, 125 research methodology assembly line analysis and design, 120 baby tenders, 123 data collection and analysis, 120 development, 121 domestic baby tenders, 120 furniture manufacturing company, 119 generic simulation models, 121 industrial pallets, 120, 122 materials flow, 121 mathematical and simulation model, 121 measurements, 119 parameters, 122 probability distributions, 122 simulation experimentation, 121 simulation models, 119, 122 results, 122, 124 simulation model, 125 storage space, 125 validation, 122, 124 verification, 122, 124 N Namibia University of Science and Technology (NUST), 97, 222, 242 National Development Strategy 1 (NDS 1), 232 National University of Science and Technology, 95, 96 Natural resources, 145 Negative balancing feedbacks, 49 loops, 49 Network of Users of Scientific Equipment in Eastern and Southern Africa (NUSESA), 3, 4, 165, 167, 182, 195 New Partnership for Africa’s Development (NEPAD), 242 NUSESA collaborative research, 183

Index O Obsolescence, 168, 171 Online learning, 36–37 Operational challenges, 275, 276 Opportunities, 274, 276, 278–280, 284, 287, 289 Optimisation, 110–112 Organisation for Economic Cooperation and Development (OECD), 2, 171 Original Equipment Manufacturers (OEMs), 3, 169, 170, 259 Overseas Development Authority (ODA), 2 P Pair-wise analysis, 173, 174, 176, 185 Parallel engineering education, 27 Partnership agreements, 181 PDP systems thinking sub-model, 264, 266–270 Philosophy, 42 Physical systems, 45 Plant layouts, 111 Plant reorganisation assembly flows and procedures, 113 in-line quality control, 118 machine distance matrices, 118 machine tools, 113 optimisation, 113, 116, 118 plant layout, 113 process paths, 118 reorganised and adopted layout, 118 research methodology, 113, 115 transportation distances, 118 workstations, 113 Platinum Group Metals (PGM), 278 Policies, 300 Polytechnic of Namibia, 28 Polytechnics, 27, 29, 58 Positive reinforcing loops, 49 Positive University Management (Reinforcing – R) loop, 50, 51 Pracademics, 276 Precious metal refinery (PMR), 278 Predictions, 288 Preventive maintenance, 183 Probability distributions, 122 Problem-based learning (PBL), 5, 33, 37, 38 challenges and possible solutions, 87–89 design thinking, 100, 101 designing, 84, 85 early childhood development, 82 elements, 82 emergence and use, 83

321 front-to-back approach, 83 fundamental principles, 82 group design projects, 83 human development, 82 implementation, 86, 87 industrial design, 100, 101 Industrial Revolution, 81 polytechnics and technical colleges, 82 practical and real-world problems, 82 students, 83 systems thinking synchronisation, 102, 103 vs. traditional learning, 83 transition, 81 Process and systems mapping, 45, 46 Process flows, 108 Process mapping, 110–112 Production process, 128 Productivity, 20, 23, 25–27, 275, 278, 289 Professional Development Policies (PDP), 264–270 Professorial chairs, 159, 165 Public–private partnerships (PPP), 75, 177, 178 Pugh method, 85 R Reductionism, 42, 43, 48, 54 Regional collaborations, 287–288 Regional integration, 191, 202 Regulatory policies, 23 Relationship networks, 191 Renewable energy, 222–224 Resource organisations, 66, 67 Resuscitation, polytechnics/creation, 31 Royal Academy of Engineering, 91 Royal Academy of Engineering Africa Prize, 202 Run-of-Mine (RoM), 136 S Safety, Health, Environment and Quality (SHEQ), 147 School of Engineering Sciences and Technology, 96 Science and technology parks, 210–213, 223 Scientific equipment, 168 SDT systems thinking sub-models, 262, 263, 266, 270 Second Industrial Revolution, 20 Segmentation, 226 Semi-autogenous grinding (SAG), 135 Service customisation, 226

322 Sharing available resources, 74 Shortages, 275, 276 Shortfalls, 276 Simulation models, 124 Simulation of operations, 109, 110 Simulation packages, 260 Simulation processes, 122 Situational analysis data collection, 175 industrialised world, 170 industrial transformations, 170 industry-based learning, 171 institutional memory, 176 laboratory equipment, 171 maintenance documentation, 171, 175 maintenance expertise, 177 NUSESA collaboration, 172, 176 OEMs, 170, 172 preventive maintenance, 172 Skills audits, 31 Skills Development and Training (SDT), 262–264, 268–270 Smart Procurement Partnerships (SPP), 181, 282 SPP model, 180, 182, 183 Social responsibility schemes, 149 Soft Systems Methodology (SSM), 54 Sources of funding, 158 Southern Africa doctoral training centres, 201 Southern Africa Engineering Education Network (SAE2Net), 197, 209, 237, 238, 240, 242, 251, 257, 286, 293 collaboration, 275–277 institutions, 246 partnership, 236, 239, 243, 247, 248, 287 Spin-offs, 235, 237–240, 243, 246, 247, 251, 280 activities, 284 companies, 231 Standardisation, 33 Start-ups, 230, 231, 235, 237–240, 243, 247, 249, 251, 280 STELLA (systems thinking software tools), 42 Success variable factors, 225 Surrogate entrepreneur model, 235, 236, 239 Sustainability, 156, 243, 244, 301 Sustainability planning and implementation emphasis, 147 engineering academics, 146, 147 industry partners, 146 interviews, 147 SHEQ, 147 Sustainable manufacture analysis, 134

Index conventional tools, 134 energy consumption, 134 gating system, 133, 134 Industrial Revolution, 131 operational costs, 134 processes, 130 recommendations, 134 research methodology, 131, 133 System interactions, 46, 47 System models, 109 Systems integration, 264 Systems modelling, 294 Systems thinking, 199 analysis and synthesis, 43, 44 application, 44 causal loop flow diagrams, 49, 50 Chinese approach, 52 cognitive competences and skills, 43 components, 42 conceptual frameworks, 54 critical thinking, 52 diagnostic tool for organisations, 51 emergence, 46–47 feedback loops, 48, 49 holistic approach, 43 implementation, 43, 51–52 interconnectedness, 44, 45 interdependences, 42 methodology, 41 negative balancing loops, 49 non-linear modelling, 54 positive reinforcing loops, 49 problem-solving approach, 53 process and systems mapping, 45, 46 production plant, 49 professional engineers, 47 reductionism, 43, 48, 54 research, 54 resolving complex and operational issues, 54 rigidity, 43 science, engineering and technology, 53 skills and competencies, 42 social sciences, 47 software tools, 42 sub-models, 52 system dynamics and complexities, 48 systems theory, 47 traditional and analytical modelling, 51 unconnected systems map for stakeholders, 46 use and application, 52 workstations, 47 Systems thinking causal flow diagram, 180

Index

323

Systems thinking groundwater enterprise model, 284 Systems thinking integration, 233, 266, 270 documenting processes and procedures, 162 engineering academics, 160, 162 engineering change management and transformation, 162 factors, 161 foreign-owned/supported platinum mining and processing company, 162 industry and academia, 162 modern business operations, 162 policies, 161 responses, 161 survey questionnaire, 161 technology training and policies, 163 Systems thinking methodology, 294 Systems thinking models, 267 Systems thinking sub-models, 257, 259

TecQuipment, 169 Tertiary institutions, 11, 150, 160 The Welding Institute (TWI), 74 Transformations, 19 Transitional Stabilisation Programme (TSP), 232 Transport systems, 156 Transportation distances, 116 Travel distances, 118 Triple Helix model, 230, 258, 282, 292, 295

T Taxation, 158 Team performance, 193 Technological companies, 108 Technological Revolution, 20, 27 Technologies, 299 Technology and knowledge transfer, 212, 223 Technology dynamics challenges and opportunities, 23 industrialising countries, 24 techniques for productivity, 25–26 Technology transfer, 66, 261, 265, 268, 271 Technology transfer centres, 243 Technology Transfer Offices (TTO), 237, 239, 240, 242, 243 Technopreneurship, 243 Technopreneurship Development Centre (TDC), 221, 243

V Virtual collaborations, 287

U Uncertainties, 34 Universal Systems Thinking (UST) model, 258, 262, 267–271, 295 Universidade Eduardo Mondlane, 94 University of Johannesburg, 93, 94 University of Zimbabwe, 98 UZ Groundwater Enterprise Project, 284

W Water resources, 156 Wealth creation, 230, 232, 233, 237, 238 Weighing process, 128 Wide Area Networks (WAN), 29 Workstations, 129 2016 World Congress on Engineering, 119 Z Zero-sum game, 206 Zimbabwe Manpower Development Fund (ZIMDEF), 158 Zimbabwe’s Trade Balance, 6 Zimbabwe strategic plan, 35