Modern Manufacturing Processes [1 ed.] 0128194960, 9780128194966

Table of contents :
Cover
Modern Manufacturing Processes
Copyright
Contents
List of contributors
Preface
Section 1: Advances in Manufacturing Processes
one Advanced manufacturing techniques for composite structures used in aerospace industries
1.1 Polymer matrix composites
1.2 Processing methods
1.3 Molding techniques
1.4 Hand lay-up process
1.5 Resin transfer molding process
1.6 Compression molding
1.7 Vacuum bagging
1.8 Vacuum enhanced resin transfer molding technology
References
two Advances in manufacturing analysis: fractal theory in modern manufacturing
2.1 Introduction
2.2 Theory of fractals
2.2.1 Definition and properties
2.2.2 Methods of computing fractal dimension
2.2.2.1 Box counting method
2.2.2.2 Fractal Brownian motion
2.2.2.3 Variogram method
2.2.2.4 Power spectrum
2.2.2.5 Area-based methods
2.3 Case studies: fractal analyses in manufacturing
2.3.1 Fractal analyses in thin films
2.3.2 Fractal analyses in laser manufacturing
2.3.3 Fractal analyses in machining
2.3.4 Fractal analyses in friction stir
2.4 Conclusions
Acknowledgment
References
Section 2: Application in Modern Manufacturing Processes
three Weldability appraisement of dissimilar metal joints: application of ultrasonic spot welding to Li-ion batteries
3.1 Introduction
3.2 USW process
3.3 USW system
3.3.1 Lateral drive spot welding system
3.3.2 Wedge-reed spot welding system
3.4 General process parameters
3.5 Mechanical analysis of joints
3.5.1 Tensile and T-peel strength results
3.5.2 Microhardness
3.5.3 Fracture surface morphology
3.6 Microstructural analysis of joints
3.6.1 Optical microscopy of weld cross-section
3.6.2 Scanning electron microscopy of fracture surface
3.6.3 Energy-dispersive X-ray spectroscopy analysis
3.6.4 X-ray diffraction analysis
3.6.5 Electron backscatter diffraction analysis
3.6.6 Transmission electron microscopy analysis
3.7 Conclusions
References
four Applications of coconut shell ash/particles in modern manufacturing: a case study of friction stir processing
4.1 Introduction
4.1.1 Application of coconut shell as concrete reinforcement, aggregate, and as filler
4.2 Application of coconut shell ash as activated carbon or as charcoal
4.3 Application of coconut shell particle as water purification and heavy metals removal
4.4 Application of coconut shell in metal, polymer, and ceramic matrix composites
4.5 Materials and methods
4.5.1 Materials collection and preparation
4.5.2 Methodology of friction stir processing
4.6 Characterization of the friction stir processed Al7075/CCSA
4.6.1 Structural integrity of Al7075/CCSA
4.6.2 Mechanical properties: tensile analysis
4.6.3 Surface integrity evaluation
4.7 Results and discussion
4.7.1 Mechanical properties: tensile behavior
4.7.2 Evaluation of surface integrity for the processed samples
4.7.3 Structural evaluation analysis: X-ray diffraction results
4.8 Conclusion
Conflict of interest
References
five Fractography analysis and constitutive modeling for dynamic plasticity of austenite stainless steel (ASS 304) at hot-w...
5.1 Introduction
5.2 Material and experimental details
5.3 Microstructure examination and fractography
5.4 Constitutive models
5.5 Constitutive model (m-FB) modified Fields–Backofen
5.6 Constitutive model (KHL) Khan–Huang–Liang
5.7 Johnson–Cook (JC) model
5.8 Constitutive equation (m-Arr.) type
5.9 Zerilli–Armstrong (m-ZA) model
5.10 Constrained optimization
5.11 Result and discussion
5.12 Conclusion
Acknowledgment
References
six Laser transmission welding of dissimilar plastics: analyses of parametric effects and process optimization using grey-b...
6.1 Introduction
6.2 Grey-based Taguchi method
6.3 Experimental work
6.4 Parametric analysis
6.5 Multiobjective optimization
6.6 Conclusion
References
seven Investigations on effect of thickness and rolling direction of thin metal foil on forming limit curves in microformin...
7.1 Microforming
7.2 Experimental investigations
7.2.1 Limiting dome height test—specimen
7.2.2 Experimental setup
7.2.3 Surface strain measurement
7.2.4 Forming limit diagrams
7.2.5 Effect of rolling direction on forming limit curve
7.2.6 Effect of foil thickness on forming limit curve
7.3 Conclusions
References
eight Evaluation and characterization of rolling of brass at cryogenic conditions
Nomenclature
8.1 Introduction
8.2 Materials and methods
8.2.1 Work piece preparation
8.2.2 Experimental plan
8.2.3 Experimental setup
8.3 Results and discussion
8.4 Analysis of variance and regression equation
8.5 Conclusions
References
nine Multiaxis CNC programming and machining
9.1 Numerical control of machine tools
9.2 Integrating CNC and automation
9.2.1 5-Axis machining
9.3 Flow of commands for 5-axis machine
9.4 CNC programming validation
9.5 Continuous improvement without editing the CNC program
9.5.1 Complex tool path programing in multiaxis machining centers
9.5.2 Cutting tool path definition in multiaxis machine tools
References
Section 3: Sustainability in Modern Manufacturing Processes
Ten Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana
10.1 Introduction
10.2 Sachet water in Ghana
10.3 Challenges of water PE-packaging
10.4 Recycling
10.4.1 Recycling legislation
10.4.2 Recyclates
10.4.3 Recycling processes
10.4.4 Method of sachet-water waste recycling
10.4.5 Cost-benefit analysis of recycling
10.5 The way forward
References
eleven Sustainability and survivability in manufacturing sector
11.1 Introduction
11.2 Elementary concepts of sustainability in manufacturing
11.2.1 Metrics
11.2.2 Evaluation of manufacturing system performance
11.3 Manufacturing process
11.3.1 Measures taken in manufacturing process
11.4 Survivability of a communication network
11.5 Challenges in sustainable development
References
Index
Back Cover

Citation preview

MODERN MANUFACTURING PROCESSES

Woodhead Publishing Reviews: Mechanical Engineering Series

MODERN MANUFACTURING PROCESSES

Edited by

KAUSHIK KUMAR J. PAULO DAVIM

Woodhead Publishing is an imprint of Elsevier The Officers’ Mess Business Centre, Royston Road, Duxford, CB22 4QH, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, OX5 1GB, United Kingdom Copyright © 2020 Elsevier Ltd. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-819496-6 (print) ISBN: 978-0-12-822774-9 (online) For information on all Woodhead Publishing publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Matthew Deans Acquisitions Editor: Brian Guerin Editorial Project Manager: Rachel Pomery Production Project Manager: Surya Narayanan Jayachandran Cover Designer: Christian J. Bilbow Typeset by MPS Limited, Chennai, India

Contents

List of contributors Preface

ix xiii

Section 1 Advances in Manufacturing Processes 1.

Advanced manufacturing techniques for composite structures used in aerospace industries

3

Raghu Raja Pandiyan Kuppusamy, Satyajit Rout and Kaushik Kumar

2.

1.1 Polymer matrix composites 1.2 Processing methods 1.3 Molding techniques 1.4 Hand lay-up process 1.5 Resin transfer molding process 1.6 Compression molding 1.7 Vacuum bagging 1.8 Vacuum enhanced resin transfer molding technology References

3 5 6 7 8 9 10 10 12

Advances in manufacturing analysis: fractal theory in modern manufacturing

13

Fredrick M. Mwema, Esther T. Akinlabi, Oluseyi P. Oladijo, Olawale S. Fatoba, Stephen A. Akinlabi and Stefan T˘alu 2.1 Introduction 2.2 Theory of fractals 2.3 Case studies: fractal analyses in manufacturing 2.4 Conclusions Acknowledgment References

13 14 24 34 34 35

v

vi

Contents

Section 2 Application in Modern Manufacturing Processes 3.

Weldability appraisement of dissimilar metal joints: application of ultrasonic spot welding to Li-ion batteries

43

Mantra Prasad Satpathy, Bharat Chandra Routara and Susanta Kumar Sahoo

4.

3.1 Introduction 3.2 USW process 3.3 USW system 3.4 General process parameters 3.5 Mechanical analysis of joints 3.6 Microstructural analysis of joints 3.7 Conclusions References

43 44 45 47 49 53 64 67

Applications of coconut shell ash/particles in modern manufacturing: a case study of friction stir processing

69

Omolayo M. Ikumapayi, Esther T. Akinlabi, Jyotsna D. Majumdar and Stephen A. Akinlabi 4.1 Introduction 4.2 Application of coconut shell ash as activated carbon or as charcoal 4.3 Application of coconut shell particle as water purification and heavy metals removal 4.4 Application of coconut shell in metal, polymer, and ceramic matrix composites 4.5 Materials and methods 4.6 Characterization of the friction stir processed Al7075/CCSA 4.7 Results and discussion 4.8 Conclusion Conflict of interest References

5.

Fractography analysis and constitutive modeling for dynamic plasticity of austenite stainless steel (ASS 304) at hot-working temperatures

69 72 74 76 80 83 85 93 93 93

97

A. Anitha Lakshmi, Ch. Srinivas Rao and Tanya Buddi 5.1 5.2 5.3 5.4 5.5 5.6

Introduction Material and experimental details Microstructure examination and fractography Constitutive models Constitutive model (m-FB) modified Fields Backofen Constitutive model (KHL) Khan Huang Liang

97 100 101 106 107 111

Contents

5.7 Johnson Cook (JC) model 5.8 Constitutive equation (m-Arr.) type 5.9 Zerilli Armstrong (m-ZA) model 5.10 Constrained optimization 5.11 Result and discussion 5.12 Conclusion Acknowledgment References

6.

Laser transmission welding of dissimilar plastics: analyses of parametric effects and process optimization using grey-based Taguchi method

vii 116 117 119 119 120 127 127 127

131

Bappa Acherjee 6.1 Introduction 6.2 Grey-based Taguchi method 6.3 Experimental work 6.4 Parametric analysis 6.5 Multiobjective optimization 6.6 Conclusion References

7.

Investigations on effect of thickness and rolling direction of thin metal foil on forming limit curves in microforming process

131 133 135 137 140 142 143

145

Gyan Patel and Ganesh Kakandikar 7.1 Microforming 7.2 Experimental investigations 7.3 Conclusions References

8.

Evaluation and characterization of rolling of brass at cryogenic conditions

145 147 154 154

157

Swadesh Kumar Singh, Satyanarayana Kosaraju, Jayahari Lade, V. Dinesh Varma and M. Sandeep Nomenclature 8.1 Introduction 8.2 Materials and methods 8.3 Results and discussion 8.4 Analysis of variance and regression equation 8.5 Conclusions References

157 157 159 162 164 165 166

viii

9.

Contents

Multiaxis CNC programming and machining

167

T. Vishnu Vardhan and B. Sridhar Babu 9.1 Numerical control of machine tools 9.2 Integrating CNC and automation 9.3 Flow of commands for 5-axis machine 9.4 CNC programming validation 9.5 Continuous improvement without editing the CNC program References

167 168 169 170 174 175

Section 3 Sustainability in Modern Manufacturing Processes 10. Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

179

Emmanuel Baffour-Awuah, Stephen Akinlabi and Tien-Chien Jen 10.1 Introduction 10.2 Sachet water in Ghana 10.3 Challenges of water PE-packaging 10.4 Recycling 10.5 The way forward References

11. Sustainability and survivability in manufacturing sector

179 181 182 186 197 200

205

Ankita Awasthi, Kuldeep K. Saxena and Vanya Arun 11.1 Introduction 11.2 Elementary concepts of sustainability in manufacturing 11.3 Manufacturing process 11.4 Survivability of a communication network 11.5 Challenges in sustainable development References Index

205 207 212 215 217 218 221

List of contributors Bappa Acherjee Department of Production Engineering, Birla Institute of Technology, Ranchi, India Esther T. Akinlabi Department of Mechanical Engineering Science, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg, South Africa Stephen Akinlabi Department of Mechanical & Industrial Engineering Technology, University of Johannesburg, Johannesburg, South Africa Stephen A. Akinlabi Department of Mechanical Engineering, Faculty of Engineering and Technology, Butterworth Campus, Walter Sisulu University, South Africa Vanya Arun College of Engineering and Technology IILM, Greater Noida, India Ankita Awasthi College of Engineering and Technology IILM, Greater Noida, India B. Sridhar Babu CMR Institute of Technology, Hyderabad, India Emmanuel Baffour-Awuah Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa Tanya Buddi Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India Bharat Chandra Routara School of Mechanical Engineering, KIIT Deemed University, Bhubaneswar, India Olawale S. Fatoba Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa Omolayo M. Ikumapayi Department of Mechanical Engineering Science, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg, South Africa Tien-Chien Jen Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa

ix

x

List of contributors

Ganesh Kakandikar School of Mechanical Engineering, Dr. V. D. Karad MIT World Peace University, Pune, India Satyanarayana Kosaraju Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad, Telangana, India Kaushik Kumar Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi, India Raghu Raja Pandiyan Kuppusamy Department of Chemical Engineering, National Institute of Technology, Warangal, India Jayahari Lade Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad, Telangana, India A. Anitha Lakshmi Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India Jyotsna D. Majumdar Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur, India Fredrick M. Mwema Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa; Materials, Design & Manufacturing Group (MADEM), Department of Mechanical Engineering, Dedan Kimathi University of Technology, Nyeri, Kenya Oluseyi P. Oladijo Department of Chemical, Materials and Metallurgy, Botswana International University of Science and Technology, Palapye, Botswana; Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa Gyan Patel School of Mechanical Engineering, Dr. V. D. Karad MIT World Peace University, Pune, India Ch. Srinivas Rao Department of Mechanical Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India Satyajit Rout Department of Civil Engineering, National Institute of Technology, Warangal, India Susanta Kumar Sahoo Department of Mechanical Engineering, National Institute of Technology, Rourkela, India

List of contributors

M. Sandeep Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad, Telangana, India Mantra Prasad Satpathy School of Mechanical Engineering, KIIT Deemed University, Bhubaneswar, India Kuldeep K. Saxena Institute of Engineering and Technology, GLA University, Mathura, India Swadesh Kumar Singh Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad, Telangana, India Stefan T˘alu Technical University of Cluj-Napoca, The Directorate of Research, Development and Innovation Management (DMCDI), Cluj-Napoca, Romania T. Vishnu Vardhan CMR Institute of Technology, Hyderabad, India V. Dinesh Varma Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad, Telangana, India

xi

Preface The editors are pleased to present the book Modern Manufacturing Processes under the book series Woodhead Publishing Reviews: Mechanical Engineering Series. Book title was chosen looking at the present trend and shift in the industrial world and future of the same. Industrial revolutions were the giant steps for mankind toward global development and prosperity. Industrial revolution started in around 1750 with I 1.0 (1st Industrial Revolution) where human and animal power was replaced by mechanical power systems like Steam Engine, Spinning Wheel, Water Wheel, etc., resulting in an enhancement and betterment in productivity. It took about a century to introduce electricity, assembly lines, conveyor belts, etc., and initiation toward mass production was made. This was designated as 2nd Industrial Revolution (I 2.0). In 19th century, under 3rd Industrial Revolution (I 3.0), integrated manufacturing with electronics provided automated production machinery. Presently with globalization and open market economy, the market has become consumer driven or customer dictated. This has given rise to 4th Industrial Revolution or I 4.0. The present era of I 4.0 has digitalized the industrial world especially the manufacturing sector and the situation has forced the manufacturing companies to face increasingly frequently changing and unpredictable market imperatives caused by globalization, increased competitions, and of course digitalization. The sector which once dictated the world economy is now striving for existence. To stay alive and to revive the lost position, industries are required not only to produce their goods with high productivity but also to allow for rapid response to market pressures and changing consumer needs, and all these at a minimum cost and minimum environmental effects. One prominent way of achieving the target is modernization of the manufacturing processes. This book is primarily intended to provide researchers and students on an overview of the current modernization in the manufacturing machines and processes, a vital sector dictating the world economy. Manufacturing can be classified into traditional, nontraditional, virtual, and additive. The book has pondered over the complete manufacturing world and indeed would provide a source to establish an effective channel of communication between the academic community of design and manufacturing

xiii

xiv

Preface

engineers in academic and research institutions, professionals working in industry and related businesses, government agencies, and policy-makers associated directly or indirectly with manufacturing sector. The chapters in the book have been grouped into three parts, that is, Advances, Application, and Sustainability completing the cycle. Hence, Section I (Advances in Manufacturing Processes), contains Chapter 1, Advanced Manufacturing Techniques for Composite Structures Used in Aerospace Industries and Chapter 2, Advances in Manufacturing Analysis: Fractal Theory in Modern Manufacturing; Section II (Application in Modern Manufacturing Processes) has Chapters 3 9, and Section III (Sustainability in Modern Manufacturing Processes) provides Chapter 10, Recycling of Polyethylene: An Attempt to Sachet and Bottled Water Sustainability in Ghana and Chapter 11, Sustainability and Survivability in Manufacturing Sector. Section I starts with Chapter 1, Advanced Manufacturing Techniques for Composite Structures Used in Aerospace Industries, which discusses about advanced manufacturing techniques for composite structures used in aerospace industries. This book chapter focuses on different liquid composite molding techniques that have been adapted to manufacture aerospace composite structures. The chapter elaborates on manufacturing of epoxy carbon composite laminate through primitive hand lay-up technique to advanced resin transfer molding techniques. Chapter 2, Advances in Manufacturing Analysis: Fractal Theory in Modern Manufacturing provides review of the applications of fractal theory in modern manufacturing. A brief conceptual foundation, typical examples, and methods of computing fractals have been summarized in the chapter including box-counting, area-based measurements, and fractional Brownian motion (fBm) methods. Fractal analysis is important in understanding the growth of structures during different manufacturing processes (and parameters) and developing fractal-like structures for enhanced performance in various engineering applications. Finally, along with applications of fractals in thin films, laser processing, machining, and friction stir processes/welding, the chapter also provides directions for future research and applications of fractal theory in manufacturing and their potentials. Chapter 3, Weldability Appraisement of Dissimilar Metal Joints: Application of Ultrasonic Spot Welding to Li-Ion Batteries, the next chapter and also the first chapter of Section II, elaborates on weldability appraisement of dissimilar metal joints with application of ultrasonic spot welding (USW) to Li-ion batteries. Fossil fuel crisis has become the

Preface

xv

burning issue to modern manufacturing scenario. Automobile sector is moving toward battery electric vehicles (BEVs) banking on the energy capacity of batteries. Here Li-ion batteries, due to its high-energy storing capacity when compared with conventional lead-acid batteries, are a prominent alternative. Manufacturing of Li-ion batteries involves a significant amount of joining to reduce the power loss and gain of desired power during the transmission process. Thus, a conservative and energyefficient method is necessary. Recently, USW process is widely adopted for assembling the Li-ion battery packs and its modules. The chapter explores the effect of different welding parameters like weld time, weld energy, weld pressure, and vibration amplitudes with a fixed ultrasonic frequency of 20 kHz for joining various dissimilar sheets. This chapter not only imparts new knowledge but also provides an insight to enhance the reliability and quality of the USW process related to Li-ion battery manufacturing. Chapter 4, Applications of Coconut Shell Ash/Particles in Modern Manufacturing: A Case Study of Friction Stir Processing, enlightens the readers with another new manufacturing process, namely friction stir processing. This present study exploited different applications of coconut shell ash/particles in additives, filler, aggregates, reinforcements, activated carbon, water purification as well as energy generation. It also exploited the application of carbonized coconut shell ash (CCSA) in high-strength aluminum, Al7075 alloy. The surface and structural integrities, as well as mechanical characteristics are described with the aid of surface roughness tester, X-ray diffraction (XRD) analysis, and Xforce P-type Zwick/Roell Z250 Tensile tester. The morphological study of fracture surfaces was done using scanning electron microscopic (SEM) analysis and chemical compositions of the present study were obtained via X-ray fluorescence (XRF). The results from the study revealed that the addition of carbonized coconut shell ash has greatly improved the fabricated aluminum matrix composite (AMC) structure-wise and surface integrity-wise. The next chapter, that is, Chapter 5, Fractography Analysis and Constitutive Modeling for Dynamic Plasticity of Austenite Stainless Steel (ASS 304) at Hot-Working Temperatures, elaborates on fractographic analysis and constitutive modeling for dynamic plasticity at hot-working temperatures. The study was conducted on ASS 304 alloy. A comparative study was conducted to evaluate the efficiency of the model mJohnson Cook (JC), the model m-Arrhenius (Arr), the model m-Zerilli Armstrong (ZA), the model Fields Backofen (FB), and the model

xvi

Preface

Khan Huang Liang (KHL) to predict flow stress behavior at hightemperature range at different strain rates. The chapter provides excellent results and also provides a detailed discussion of the extent of viability of various models and the most suitable model where the experimental results supported the prediction. The chapter also recommends the simulation and FEM-based work for future researchers on the subject. In Chapter 6, Laser Transmission Welding of Dissimilar Plastics: Analyses of Parametric Effects and Process Optimization Using GrayBased Taguchi Method, multiobjective optimization has been applied to identify optimal process parameters to analyze parametric effects of laser transmission welding of dissimilar plastics. In this chapter attempt is made to optimize the welding parameter for multiple weld quality characteristics during laser transmission welding of acrylic to acrylonitrile butadiene styrene (ABS). The process has been optimized using Taguchi method in combination with gray relational analysis. The welding parameters such as laser power, welding speed, stand-off distance, and clamp pressure were considered as input parameters and weld strength and welding width was the responses. A confirmation test is performed showing the validity and authenticity of the adopted methodology. In Chapter 7, Investigations on Effect of Thickness and Rolling Direction of Thin Metal Foil on Forming Limit Curves in Microforming Process, investigations on effect of thickness and rolling direction of thin metal foil on forming limit curves in microforming process was done. Forming limit diagram is an important tool in analysis of sheet metal forming process, another very important traditional manufacturing process. Forming of microthin sheets (thickness ,100 µm) is prone to more defects and requires more precision process called “microforming” and the same is gaining more attention of researchers due to miniaturization in many fields. Unlike macroforming or normal forming, many variations occur in the properties of material at microthickness level and hence new failure criteria are required to be defined and identified for sheets of microthickness. In this chapter, experimental investigations for microthin brass foil along with different rolling directions was done to plot forming limit diagram. One of the most important test, that is, hemispherical punch test was performed in according to relevant standard test and comparison for different specimen under various conditions were compared and inference were drawn. One of the challenges faced by the manufacturing fraternity is machining at cryogenic conditions. Chapter 8, Evaluation and Characterization

Preface

xvii

of Rolling of Brass at Cryogenic Conditions, elaborates on rolling of brass samples at cryogenic conditions. In this chapter the influence of temperatures, directionality, and velocity on the ultimate tensile strength, yield strength, and percentage elongation of brass sheets under cryogenic conditions was investigated. The experimental results were also used to create a regression equation which would help the future researchers in predicting results as such experimentation is quite expensive and difficult as well. Chapter 9, Multiaxis CNC Programming and Machining, the concluding chapter of the section, introduces the readers to multiaxis CNC programming and machining. The present world demands variety in products and it is not possible with special purpose machines in mass production. To meet the demand for high product variations the industry is working with small batches. The recent developments in the field of CNC technology have shown its capability to produce complex shapes at ease. The multiaxis machines are highly included in production processes due to their flexibility and suitability for different control and processing units. The chapter deals with difficulties and common errors that happens with multiaxis CNC machines and also provides the remedies for the same. Chapter 10, Recycling of Polyethylene: An Attempt to Sachet and Bottled Water Sustainability in Ghana, the commencing chapter of Section III, talks about recycling of polyethylene (PE), one of the most used plastics which is creating major environmental issues. The attempt made by the authors for usage of recycled PE for creating sachet and bottled water in Ghana. In the global call for water for all, the Millennium Development Goals (MDG) target 7c was set with the aim of reducing the percentage of global population without access to improved water sources in rural and urban communities by half. Sachet and bottled water have contributed to the achievement of this noble objective especially in developing countries such as Ghana. The aim of this chapter was to review literature on the conventional techniques of recycling plastics in general and PE in particular, as a packaging material for sachet and bottled water. Issues dealt with include environmental and public health challenges; recycling legislation; recyclates; recycling processes; cost-benefit analyses of recycling; and the way forward. Chapter 11, Sustainability and Survivability in Manufacturing Sector, the concluding chapter of the section and the book, provides review of sustainability and survivability in manufacturing sectors. Sustainable manufacturing is self-evolving methodology. It has relevance in different

xviii

Preface

segments like economics, environment, and society. There are many challenges encountered by manufacturing sector where the concept of sustainability is required. In this chapter, a conclusive investigation is made on sustainability idea, tools, techniques of its implementation, and policies required to implement it in manufacturing. First and foremost, the Editors would like to thank the Almighty for His blessings for completing the work to their satisfaction. God, you have given the power to work hard, pursue dreams, and believe in passion. The Editors could never have done this herculean task without the faith they have in you, the Almighty. They are thankful for this. The Editors would also like to thank all the Chapter Contributors, the Reviewers, Editorial Advisory Board Members, Book Development Editor, and the team of Elsevier Personnel for their availability for work on this editorial project. Last, but definitely not least, the editors would like to thank all the well wishers, colleagues, students, and all who were directly or indirectly helping in providing them encouragement. They would have probably given up without their support. Kaushik Kumar J. Paulo Davim

CHAPTER ONE

Advanced manufacturing techniques for composite structures used in aerospace industries Raghu Raja Pandiyan Kuppusamy1, Satyajit Rout2 and Kaushik Kumar3 1

Department of Chemical Engineering, National Institute of Technology, Warangal, India Department of Civil Engineering, National Institute of Technology, Warangal, India 3 Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi, India 2

1.1 Polymer matrix composites Composite materials are produced by stitching dissimilar materials that have diversified properties. The constituent materials function as whole unit that offers composite material of unique properties. Composites are made up of one continuous phase and one or more discontinuous phase. The discontinuous phases are mixed and uniformly distributed over the continuous phase. The continuous phase is called matrix. The material rigidity, environmental resistance, and hold up of discontinuous phase are the main functions of matrix. Metals, polymers, and ceramics can be used as matrix material. The discontinuous phase is called the reinforcement which gives mechanical strength and stiffness to the composite material. Materials of fibrous form, particle fillers, and whiskers can be used as reinforcements for the composite material. Polymer matrix composite (PMC) material uses either thermoplastic material or thermoset resin as the matrix and mats of glass, carbon, etc., as the reinforcement. On functioning, these resin matrices distributes the load among the each fibrous units and protects the fibrous mats from physical damage on application due to wear, abrasion, and impact. PMC’s offer unique and superior characteristics such as higher mechanical strength, material stiffness, better environmental resistance, and easy formability in terms of Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00001-4

© 2020 Elsevier Ltd. All rights reserved.

3

4

Raghu Raja Pandiyan Kuppusamy et al.

molding processes. Importantly, superior characteristics are obtained along with low density and higher strength to weight ratio, which makes a first choice compared with usual applied materials in many applications [1]. Light weight coupled with higher strength and tailor-made properties make them suitable for more advanced applications such as bullet trains, aircrafts, satellites, and submarines. Recently, focus shifts to apply PMCs in automotive, transport, consumer, infrastructure, and sporting goods because of their advantages such as integrated component production with lower assembly costs. However, the installation of PMCs to automotive, transport, infrastructure, consumer, and sport industries has been slowed due to the lack of understanding of production process, the lack of validated experimental and raw material characteristics information, nonavailability of material design facilities, nonavailability of proper procedures and guidelines, and limited hands-on experience. Thus the successful and economical fabrication of a composite component requires a proper product design and manufacturing facilities [2]. Depending upon the type of polymer matrix used, PMC’s are classified into thermoplastic PMC and thermoset PMC. Thermoplastic PMC currently represents a relatively small part of the PMC industry. Thermoplastic PMC are prepared using heat and pressure and there is no chemical reaction process that occurs during processing. The thermoplastic matrix is supplied in solid form and the thermoplastic PMC is formed by inserting the reinforcement material into the molten thermoplastic matrix. The production of thermoplastic PMC’s are difficult because of higher melt viscosity of the thermoplastic matrix. However, thermoplastic PMC’s are prepared with filler, powder, and short fiber reinforcements using injection and extrusion moldings. Recently, long fiber thermoplastic composites manufacturing methods have been developed with the (1) injection and extrusion of relatively long fiber filled pellets of thermoplastics, (2) reinforced reaction injection process, (3) coating of thermoplastics on long fibers coupled with thermoforming, and (4) pultrusion of long fibers into the thermoplastic matrix [3]. The thermoset PMC uses a thermoset resin as the polymer matrix. Thermoset resins can be cross-linked and converted to hard solid using a curing agent or an application of heat. This cross-linking operation is called curing. The thermoset PMC is formed by impregnating the resin onto a reinforcing material, followed by a curing step to produce the finished part. Thermoset resins are initially available in liquid state and hence it is easy to introduce the inserts like fillers and reinforcement fibers.

Advanced manufacturing techniques for composite structures used in aerospace industries

5

Polyesters, epoxies, phenolics, polyurethanes, and polyimides are some of the commonly used polymer matrix systems to produce a composite material. Among them, unsaturated polyester (UP) resins are the commonly used resin system in most applications due to its low price, curing nature, and its improved characteristics toward chemicals. UP resins are pale yellowish viscous liquid containing polyesters mixed with styrene monomer. Styrene reduces the viscosity of the UP resin solution and it helps in cross-linking process, which makes the liquid resin to rigid solid state. Reinforcement fibers are fine diameter one-dimensional elements with a fairly large aspect ratio. The most common reinforcements are glass, carbon, aramid, and boron fibers. More than 90% of composites made uses glass fiber because of its all-round properties and relatively lower cost. The glass fiber is commercially available in the forms namely yarns, rovings, chopped strand mats, chopped strands, and woven rovings. Each of these forms has its own special application. Yarns and rovings are continuous fibers used in composite production processes such as filament winding and pultrusion. Chopped strands are used for making injection and compression molding compounds. Chopped strand mats and woven rovings are three-dimensional preforms used for making laminates for a variety of applications [1,3,4].

1.2 Processing methods The manufacturing methods bring a way to combine resin matrices and reinforcement fiber mats to the required shape of the target component ensuring minimum voids and maximum resin-fiber wetting. Hence, the objective of any composite processing method is to accomplish a maximum wet-out, satisfying the part performance requirements with the desired rate of production. The measure of resin impregnation is governed by the processing parameters such as applied pressure and cure temperature of the manufacturing method employed. Irrespective of the selected manufacturing technique, factors such as raw material characteristics including reinforcement permeability, fiber volume fraction, resin curing kinetics, viscosity, and product dimension and complexity affects the outcome of the finished part. These factors may get affected with changes made in the processing parameters and hence, the dependency of these factors with the process parameters should be revealed for the successful production of high quality products [2].

6

Raghu Raja Pandiyan Kuppusamy et al.

There are raw material parameters and processing method variables that influence the manufacturing method and properties of finished product. Resin cure kinetics, resin viscosity, resin gelation time, and exothermy are the resin parameters that influence the manufacturing processes and final product characteristics. Reinforcement fiber mat architecture, mat porosity, and mat direction permeabilities are the reinforcement fiber parameters that influence manufacturing processes and final product characteristics. Maximum fiber volume fraction, maximum fiber-resin wetting, no voids formation, ease in shaping, reduced cycle times, ease in temperature application for curing, and less tools requirements are the favorable parameters to make a processing method as a choice to manufacture a composite component. During curing, resin undergoes chemical and physical changes. Physically resin changes from liquid to gel state, then to rigid solid state. Chemically, resin undergoes crossing linking with the help of curing aids such as accelerators and catalysts and with the application of temperature. The resin cures with the release of heat. With increase in curing, the viscosity of resin increases exponentially. Hence, parameters like resin gelation time, peak exothermic temperature, resin cure kinetics, and resin cure viscosity are major parameters for manufacturing processes. Several resins have been developed specifically for each manufacturing process in accomplishing processing traits with desirable physical properties. Heat is often used to speed up the curing process [5]. Mold filling phase and curing are the two major phases for any manufacturing method. With complexity in geometry, both phases find difficulty in pressuring resin for fiber impregnation. Then, in curing, applied temperature may not be uniform, thus we have different cure distribution along the product thickness. The major manufacturing techniques are molding, winding, and other continuous automated production methods such as pultrusion methods. However, the choice of the composite production process for a particular application is governed by a trade-off between lower manufacturing cost, high performance part, production rate, size, shape, and ease in making complex geometries.

1.3 Molding techniques Composite manufacturing process through molding techniques uses a cavity that has the shape of the product. Molding of a composite

Advanced manufacturing techniques for composite structures used in aerospace industries

7

product is accomplished by using either an open mold or a closed mold. In the open mold process, only one half of the mold is used for the development of the product. Only the surface that is in contact with the mold will be smooth and the other surface will be rough. The thickness is also not precisely controlled. All the open mold processes use wet resin lay-up. In the closed mold process, both halves of the mold are used and the product is made within the cavity of mold. The product will have good finish on both the surfaces. The thickness also can be correctly controlled. The molding processes namely hand lay-up (HLU) method and resin transfer molding (RTM) method are described in the following sections [1 3].

1.4 Hand lay-up process A schematic of the HLU process is shown in Fig. 1.1. Production of a composite component is done by manual laying up of reinforcement layers and liquid resin layers in sequence. A roller is used for the compaction and the homogeneous fiber wetting. Then the component is cured under room temperature and it is removed after solidification. HLU process allows the manufacture of product wide range of applications and geometries with low initial investment. Despite these advantages, there are several disadvantages which includes low reinforcement volume fraction, nonuniform quality leading to uneven thickness, and nonuniform distribution of reinforcement material and matrix. Being an open mold process, it emits a large volume of styrene which makes the process nonenvironmental friendly. Furthermore, postprocessing fabrication is more often required which compromises the reliability of the product. Longer production time, lower production rate, and high

Figure 1.1 Hand lay-up process.

8

Raghu Raja Pandiyan Kuppusamy et al.

involvement of skilled labor make the process unsuitable for large scale and complex geometries production forcing the manufacturers to explore the options of closed mold alternatives such as liquid composite molding (LCM) techniques [1 3]. Fig. 1.1 shows the preparation of epoxy resin carbon fiber composite laminates through HLU process for simple aerospace structures.

1.5 Resin transfer molding process RTM consists of a mold cavity that is in the shape of the part to be manufactured. The fiber preform is placed in the cavity. The mold is closed and clamped. The resin mixed with the curing agents is then injected into the preform through one or more gates from a pressurized container. Once the cavity is full, resin injection is discontinued. Finally, the resin is allowed to cure either at ambient or at elevated temperatures [6]. The resin can be injected using SPARTAN-II Lite RTM Machine model of GlasGraft, United States, as shown in Fig. 1.2. The injection machine can be operated at constant pressure conditions. The constant pressure injection dispenses 192 mL of resin per stroke. The machine can be operated at a maximum pressure of 70 atm. The machine uses infinite catalyst ratio setting with different constant injection pressures. The injection machine uses a single delivery gun system [7].

Figure 1.2 Resin transfer molding process.

Advanced manufacturing techniques for composite structures used in aerospace industries

9

1.6 Compression molding The composite laminate prototypes are prepared and tested using economical hot press processing through compression molding prior to real application and high-end costly manufacturing techniques like autoclave molding. These hot press cured composite prototypes avoid the bulk raw material requirement at the initial phase of the process and product development. Also, these prototype studies helped in judging the cure cycle to the actual cure panel development through RTM process. It aided several simpler trials to test possible cure cycles to determine the cure evolution at the laminates. The following are the raw materials and associated parameters to prepare the hot pressed composite laminate— Resin: RTM6 Resin (Hexcel), Reinforcement: Carbon fiber woven roven mat, Mat Architecture: 6 layers at 45 /45 /45 /45 /45 /45 , and Dimension: 100 mm 3 100 mm. Initially, the reinforcement layers are saturated with RTM6 resin using HLU method. Then, each resindrenched are arranged to the required mat architecture and kept to the pseudo-mold made by folded Teflon sheets. Finally, this set-up is kept under the hot press to initiate the hot press process. The pictures of the hot press machine and the molds used for the prototypes development are shown in Fig. 1.3. In the hot press, the whole laminating process is programmed with the timely pressure and temperature applications. The heat application to the process is disintegrated into resin preheat, resin ramp to the cure cycle, cure cycle, and the cooling rate. All the temperature applications at the different cure zones are programmed as a function of time.

Figure 1.3 Compression molding process.

10

Raghu Raja Pandiyan Kuppusamy et al.

1.7 Vacuum bagging Fig. 1.4 shows the vacuum bagging techniques, where vacuum is used as the driving force for resin impregnation through the reinforcement mats. The resin impregnation can be performed either at room temperature or elevated temperature. Fig. 1.4 shows the vacuum bagging technique at elevated temperature by performing inside temperature control oven. The laminate having raw materials and mat architecture are discussed in Section 1.6, was prepared using vacuum bagging process and the respective post cured epoxy carbon fiber laminate is displayed.

1.8 Vacuum enhanced resin transfer molding technology Vacuum enhanced resin transfer molding technology (VERTMTy) has advantages over other molding processes, since it is designed to use both injection pressure and vacuum as combined driving forces for the resin to flow through porous reinforcement medium. The main components of the complete mold assembly are: resin storage pot, metal mold with injection ports and vents, heating and cooling assembly in metal mold, temperature controllers, and vacuum pump. The complete molding system is shown in Fig. 1.5. The developed mold assembly can produce composite laminates with dimensions of 600 mm 3 300 mm. The corner screw system was designed in such a way that the part thickness can be

Figure 1.4 Vacuum bagging process.

Advanced manufacturing techniques for composite structures used in aerospace industries

11

Figure 1.5 Vacuum enhanced resin transfer molding technology (VERTMTy).

varied from 2 to 8 mm. Electrical cartridges with control arrangement were used to heat uniformly top and bottom half of the mold. Water circulation system was also arranged by drill holes between cartridges arrangement on bottom and top half of the mold to cool the mold after the application of cure cycle. In this work, the Hexcel RTM6 Epoxy resin and G0926 5H satin weave carbon fabric are the polymer matrix and reinforcement fibers used to manufacture the composite part. Six layers of carbon fiber woven fabric of architecture 90 /90 /90 /90 /90 / 90 was used to make a product of dimension 600 mm 3 300 mm. About 180 C for 3 h was used as cure cycle to manufacture the composite laminate [8]. To start the manufacturing process, the mold is cleaned with acetone to remove surface dirt and dried with compressed air. Then, the wax coating is applied for surface uniformity and followed by mold releasing agent. Further, peel ply is laid to avoid surface contamination on the composite laminate during manufacturing process. Then, the reinforcement mats of required geometry are arranged and two halves of the mold are clamped to air tight. Now, vacuum is applied at the vents for 30 min so as to ensure that the mold is at full vacuumed condition. Following this, compressed resin from the resin storage pot is injected into the mold through injection gate. The resin leaks out at the vent after the mold is fully saturated with resin. Finally, temperature cycle is applied to cure the composite laminate. Fully cured epoxy carbon composite laminate is shown in Fig. 1.5.

12

Raghu Raja Pandiyan Kuppusamy et al.

References [1] Peters ST. Handbook of composites. 2nd ed. London, UK: Chapman & Hall; 1998. [2] Mazumdar SK. Composite Manufacturing materials, processes and process engineering. 1st ed. Boca Raton, FL: CRC Press; 2002. [3] Mallick PK. Fiber reinforced composites-materials, manufacturing and design. 3rd ed. Boca Raton, FL: CRC Press; 2008. [4] Hollaway LC. Handbook of polymer composites for engineers. 1st ed. Cambridge, England: Woodhead Publishing Limited; 1994. [5] Advani SG, Murat Sozer E. Process modeling in composites manufacturing. 1st ed. New York: Marcel Dekker, Inc; 2003. [6] Potter K. Resin transfer moulding. 1st ed. London, UK: Chapman & Hall; 1997. [7] Kuppusamy RRP, Neogi S. Development of resin transfer molding process using scaling down strategy. Polym Compos 2014;35(9):1683 9. [8] R.R.P. Kuppusamy, 2018. Development of aerospace composite structures through vacuum-enhanced resin transfer moulding technology (VERTMTy): vacuum-enhanced resin transfer moulding. In: Kumar K, Paulo Davin J, editors. Composites and advanced materials for industrial applications. Hershey, PA: IGI Global. p. 99 111.

CHAPTER TWO

Advances in manufacturing analysis: fractal theory in modern manufacturing Fredrick M. Mwema1,2, Esther T. Akinlabi3, Oluseyi P. Oladijo1,4, ˘ 6 Olawale S. Fatoba1, Stephen A. Akinlabi5 and Stefan Talu 1

Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa Materials, Design & Manufacturing Group (MADEM), Department of Mechanical Engineering, Dedan Kimathi University of Technology, Nyeri, Kenya 3 Department of Mechanical Engineering Science, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg, South Africa 4 Department of Chemical, Materials and Metallurgy, Botswana International University of Science and Technology, Palapye, Botswana 5 Department of Mechanical Engineering, Faculty of Engineering and Technology, Walter Sisulu University Butterworth Campus, South Africa 6 Technical University of Cluj-Napoca, The Directorate of Research, Development and Innovation Management (DMCDI), Cluj-Napoca, Romania 2

2.1 Introduction The concept of fractal geometry has found applications in various fields including medicine [1], surface engineering [2,3], crash rate prediction [4], manufacturing technologies [5], geosciences [6], powder metallurgy [7,8], biometrics [9,10], image analyses (texture and segmentation) [11,12], stock market analysis [13,14], and so forth. In all the applications the processes are assumed to have self-similar characteristics at different times or scales; and such properties are exhibited by most natural systems such as coastlines, mountains, vegetation cover, etc. [1]. These natural systems exhibit fascinating patterning which cannot be described by the traditional Euclidian geometry and hence the need for the fractal geometry as described by early work of Mandelbrot [15]. The fractal theory has been employed in different manufacturing processes to either understand the structural growth/formation or to produce fractal-like components for enhanced product performance. In thin film and surface engineering, for example, fractal analysis is utilized in studying the growth mechanism during the deposition (manufacturing) processes. Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00002-6

© 2020 Elsevier Ltd. All rights reserved.

13

14

Fredrick M. Mwema et al.

In three-dimensional (3D) printing (additive manufacturing) technologies such as laser deposition, there is increasing urge for products which mimic naturally occurring (fractal) systems such as animals, plants, rivers, clouds, and among others. These technologies have been shown to enhance the performance of the manufactured products. For instance, 3D-printed treelike (fractals) heat exchanger systems have been shown to outperform the conventional tubular systems [16,17]. Although, there are several publications on the applications of fractal theory in modern manufacturing and materials, there are few dedicated reviews providing a perspective of the subject. In fact, most of the published reviews have focused on the general subject of fractals without narrowing to manufacturing processes. Recent reviews in this field include that were published by Lopes and Betrouni [1] on the application of fractal theory in medicine; by Zuo and Wang [18] on fractal modeling of geochemical data; by Chen et al. [19] on design of microfluidics and nanofluidic; by Joshi et al. [20] on the application of fractals in analyzing food systems; Pippa et al. [21] on the potential benefits of the fractal concepts in pharmaceutical sciences; and by Kesic’ and Spasic’ [22] on application of fractal methods in clinical neurophysiology. This chapter reviews, for the first time, the applications of the fractal theory in manufacturing processes along with considerations of its potential benefits in the modern manufacturing. Theory of fractals and the most common methods of fractal analysis are also discussed.

2.2 Theory of fractals 2.2.1 Definition and properties In his attempt to determine the length of the British coastline, Mandelbrot (1967) defined fractal as a fragmented geometry whose subdivisions are approximates of the whole geometry [23]. This definition has evolved with time and, generally, fractals exhibit the following properties: (1) fractals have fine structures and as the scale of measurement increases, more details are observed, (2) the geometries are too irregular that they cannot be described by the conventional geometry and the degree of irregularity is constant on all scales, (3) they exhibit self-similar characteristics and consists of self-repeating patterns of simple units, and (4) they are described by noninteger dimensions, that is, values between two whole numbers [15]. The concept of dimension (D) can be illustrated as follows.

Advances in manufacturing analysis: fractal theory in modern manufacturing

15

Considering the conventional shapes in Fig. 2.1, the definition of dimension can be illustrated. A straight line of length (r 5 1) is considered a one-dimensional geometry (D 5 1), a square with lengths (r 5 1) is considered a two-dimension (D 5 2) whereas a cube of same lengths is a three-dimension (D 5 3) shape. If the line is subdivided into two equal parts (N 5 2) in lengths (r 5 2) and further into N 5 3, its dimension (D) does not change. Similar argument holds for square and cube as shown in Fig. 2.1. In such a case, the relationship between the length (r) and number of subdivisions (N) is N 5 rD from which D 5 lnðNÞ lnðrÞ . In fractals, this dimension is known as the fractal dimension (D) and as illustrated in Fig. 2.1, it does not vary with the scale of measurement. The concept of D can be illustrated using examples of fractal shapes. Koch curve generated by dividing a straight into three parts and replacing the middle section with two portions of equal lengths is one of the common fractal shapes. The procedure is repeated until a Koch curve is produced as illustrated in Fig. 2.2. According to definition of D above, for each stage, there are three equal lengths (r 5 3) and four divisions (N 5 4). Therefore, the fractal dimension D of the Koch curve can be obtained as D 5 lnð4Þ lnð3Þ 5 1:26. Another example of fractal shape is the Sierpinski gasket which is typically an equilateral triangle which has been recursively portioned into smaller equilateral triangles. Each side of the triangles is divided into two equal lengths (r 5 2) and three similar triangles as the original (N 5 3). It basically involves removing the central part of the triangle (white region)

Figure 2.1 Illustrating the concept of dimension of conventional geometries.

16

Fredrick M. Mwema et al.

Figure 2.2 Procedure of generating a Koch curve. Obtained from https://en.wikipedia.org.

recursively until a gasket-like triangle is obtained. As such, the fractal dimension of the Sierpinski gasket in Fig. 2.3 is 1.58. In fact, an infinite application of the Sierpinski triangle generator results in zero area. For n number of iterations, the area removed (Ar) and the areas (A) of the original triangle are related by the following expression. "
n21 # 3 Ar 5 A 1 2 4 As n tends to infinity, the removed area (Ar) tends to the original area (A). A similar operation has been applied to a square shape to obtain Sierpinski carpet as shown in Fig. 2.4. In this operation, a central square is removed at a scaling factor of 1/3 (the sides of the original square are divided into three equal lengths, r 5 3). This leaves the original square divided into eight subsquares (N 5 8). Therefore, the fractal dimension of such shape is 1.89.

Advances in manufacturing analysis: fractal theory in modern manufacturing

17

Figure 2.3 Construction of the Sierpinski gasket. Obtained from https://en.wikipedia.org.

Figure 2.4 Sierpinski carpet with D 5 1.89. Obtained from https://en.wikipedia.org.

Applying the similar Sierpinski carpet operations to a cube, generates a Sierpinski sponge in Fig. 2.5. As shown, each central cube is removed in the front, central, and back faces. This leaves the front and back faces with 8 cubes each and 4 cubes at the central region such that there is a total of 20 cubes (N 5 20). The length of each side of the cube is divided into 3 (r 5 3) and therefore the fractal dimension can be computed as ln (20)/ln(3). The fractal dimension of the sponge lies between 2 and 3 implying that it is more than a two-dimensional (2D) object, but it does not fully fill the three-dimensional space (Fig. 2.1). Fig. 2.6 shows more examples of both naturally occurring and engineered fractals for various applications and uses.

2.2.2 Methods of computing fractal dimension As illustrated above, there are various phenomenon and structures, both natural and artificial, which exhibit fractal characteristics. In image analysis

18

Fredrick M. Mwema et al.

Figure 2.5 Sierpinski sponge with D 5 2.726. Obtained from https://en.wikipedia.org.

Figure 2.6 Natural and artificial fractal structures. Such structures consist of small repeating units (and shapes) to form self-similar structures.

of such structures, fractal geometry is usually described via computation of the fractal dimension (D). There are various techniques used to calculate the fractal dimensions of images, which can be classified as box-counting, area measurements, and Brownian motion methods [1,17]. Although these methods use different mathematical formulations, they follow the same three-step procedure: (1) determining the various steps of

Advances in manufacturing analysis: fractal theory in modern manufacturing

19

measurement (N) and values of each step (r) of the fractal object, (2) plotting log(N) against log(r) and then undertaking a linear regression of the scatter plots, and (3) computing the D from the gradient of the linear regression line of the scatter plots. 2.2.2.1 Box counting method This is the most widely used and simplest method of determining the fractal dimension (D) in structures [24]. It involves binarizing the signal of the fractal feature or structure under investigated. The area of the feature (s) is then subdivided into grids of equal lengths (r) as shown in Fig. 2.7. The number of boxes (or squares), denoted by N, depends on the size of r; the smaller the value of r the higher the number of boxes. The fractal dimension from box-counting method, Db, is obtained by the following relationship as defined in various texts [15,24]. logðNÞ r-0 logðrÞ

Db 5 2 lim

A linear logarithmic relationship exists between N and r as log(N) 5 log(C) 2 Dlog(r) and therefore a bi-logarithmic plot of N against r gives

Figure 2.7 Box counting method for natural fractal structure. Image obtained from https://en.wikipedia.org.

20

Fredrick M. Mwema et al.

the fractal dimension (D) as the gradient. To undertake the box counting process, color images must be converted into grayscale, which this leads to loss of some of the information of the original image [25]. As such, improved methods of box counting have been developed. Differential box counting method is one of such methods, which does not involve binarization of the images. In this method, the grayscale image is divided into series of cubes whose heights represent the intensity of the grayscale. The cubes are then scaled (r) into boxes and the number of boxes (nr) covering the (i,j)th cube is determined from the difference between the position of the box occupied by the lowest (k) and highest (l) gray levels according to the equation below. nr ði; jÞ 5 l 2 k 1 1 Then, N(r) is determined as follows; X N ðr Þ 5 nr ði; jÞ i;j

The above process is repeated to obtain N(r) in a set of various scales (r) and then fitting the least squares of log(N(r)) against log(r) to determine the fractal dimension (D) of the features as earlier described. The accuracy of the box-counting method depends on the choice of the size of the grid. Extensive studies have been undertaken to find the upper and lower bounds for the grid size and justification for choice of small sizes has been proposed [26,27]. It has been reported that box-counting methods are not numerically accurate and tends to underestimate the actual value of the fractal dimension (D). As such, various improved differential boxcounting methods have been proposed [1,25,2729]. Other variants of box-counting methods such as extended box-counting, etc., are described in literature [26,30]. 2.2.2.2 Fractal Brownian motion These methods are based on a nonstationary model which generalizes the Brownian motion for description of random processes which have nonindependent and normally distributed increments [31]. Fractal Brownian motion (fBm) can be defined as a self-similar, normally distributed and time (0, T) continuous Gaussian processes (BH) characterized by a parameter called Hurst exponent (H). A fBm is a generalization of Brownian motion which begins at zero, has an expectation of zero and whose covariance is given as follows for HA (0, 1): [31,32]

Advances in manufacturing analysis: fractal theory in modern manufacturing

21

Figure 2.8 Hurst exponent of different fBm motions. Obtained from https://en.wikipedia.org/wiki/Fractional_Brownian_motion.

E½BH ðtÞBH ðsÞ 5

 1  2H jt j 1 jsj2H 2 jt2sj2H 2

The Hurst exponent/index (H) describes the roughness of the motion; the smaller the value, the higher the roughness and vice versa. When H is 0.5, the process is said to be a Brownian motion, when it is less than 0.5, there is a negative correlation of the increments (very ragged motion) and when it is more than 0.5, there is a positive correlation of the increments (smooth motion) as illustrated in Fig. 2.8 [32]. In images such as micrographs, a particle motion over its surface can be considered a fBm and, therefore, section profiles of such images can be considered as fBm as illustrated by Yadav et al. [33]. There are two algorithms commonly used to compute fractal dimension (D) from fBm namely variogram and power spectrum methods [1]. 2.2.2.3 Variogram method In this method, a separation vector (h) is determined within each range of points within the fBm. For each case, there is data corresponding to the head and tail of the separation vector as shown in Fig. 2.9 (the motion is assumed fBm). When the tail and head of the vector corresponds to the first and second, second and third, third and fourth until the n and (n 1 1) data points this is known as lag 1 as shown in Fig. 2.9 [34]. When the tail and head correspond to the n and n 1 2 data points, respectively, it is known as lag 2 and so forth. From Fig. 2.9, the tabular data of head and tail is obtained and a scatter plot of head against tail as shown in Fig. 2.10. As shown in Fig. 2.10, the mass moment of inertia of each point should be determined in relation to the line x 5 y as the product of the mass and the perpendicular distance (?) from the line x 5 y. The perpendicular distance can be determined from the law of triangles as x 2 y/O2.

22

Fredrick M. Mwema et al.

Figure 2.9 Illustrating the use separation vector to obtain the tail and head data points of lag 1.

Figure 2.10 Scatter plots of head against tail points (lag 1) of the data points from Fig. 2.9. The idea is to determine the mass moment of inertia of each of these points in relation to the line x 5 y.

Advances in manufacturing analysis: fractal theory in modern manufacturing

23

If the total number of the points is N, then the average squared distance from each point to the line x 5 y (variance) can be written as d 2 ðhÞ 5

2 N  1X 1 pffiffiffi ðZi 2Zi1h Þ N i 2

where, Zi represents the point at the tail and Zi1h the point at head of the separator vector (h). This equation represents the semi-variance (γ h ) of all the data points and can be simply written as follows [35]. N 1 X ½ðZi 2Zi1h Þ2 γh 5 2N i51

The data of γ h is then plotted against the separator vector (h) to generate the semi-variogram of the fBm curve. In summary, to determine a fractal dimension through variogram method, first is to determine the semi-variance (γh ) values for different separations (h). A regression analysis on the plot of logðγh Þ against logðhÞ is undertaken from which the slope of the line is determined as 4-2D, where D is the fractal dimension of the curve [35]. 2.2.2.4 Power spectrum An image is composed of lines which exhibits fBm characteristics. In this method, the image is decomposed into waves of different frequencies and wavelengths through Fourier transformation, the power spectrum of each line is computed and averaged over range of spatial frequencies (inverse of frequency) [36,37]. Mostly, 2D fast Fourier transform (2D-FFT) is used and the procedure has been extensively discussed in literature [3,3841]. The fractal dimension (D) is computed by fitting the power spectrum models obtained from the fBm into known physical laws such as inverse power law, ABC-correlation model, and so forth [3,40]. Power spectrum method uses power spectral density functions (PSDFs) and has been shown effective for self-affine surfaces and due to the fact that it requires gridded data, it is slow and only works for isotropic surfaces [1]. As such, various modifications of power spectrum methods of fBm functions have been evaluated such as those reported in Refs. [40,41] in which a power spectrum density with enhanced correlation lengths were illustrated. Asvestas, Matsopoulos, and Nikita in 1998 illustrated the use of power differentiation method (PDM) and modified

24

Fredrick M. Mwema et al.

PDM methods as an improvement to conventional PSD technique for medical imaging applications [42]. 2.2.2.5 Area-based methods In these methods, the area (A(r)) of the signal structured into elements such as triangle of different scales (r) are computed. A plot of log(A) against log(r) is generated and a slope of the regression analyses of the plot gives the fractal dimension (D) of the image. Area (A(r))perimeter (P) relationship is among the commonly used area-based method for determination of D. The AP relationship was first used by Mandelbrot for description of D of island-type objects such as ore chips [15,43] in which area and parameter were related as Ar ~ P 2=D . When using this method, one must be careful not to use perimeter obtained from different scales since perimeter values significantly change with the scales as compared with the area values. As such, readers are referred to a recent publication by Florio, Fawell, and Small in 2019 on the use of AP method for determination of D in clustered aggregates [43]. A similar approach was also used on fractal measurements of aggregates formed in different flocculation environments [44]. Other commonly used area-based methods for fractal dimension computation include blanket method, isarithm method, triangular prism method, and Korcak’s empirical relationship. These methods have been extensively described by these studies [1,45].

2.3 Case studies: fractal analyses in manufacturing 2.3.1 Fractal analyses in thin films Surface characteristics of thin films play a major role in their performance and applications [4648]. Some of the properties influenced by surface nature of thin films include wettability and self-cleaning [47], electrical conductivity, corrosion, mechanical stability, etc. [2,3,4954]. As such, characterizing the surfaces of thin films is very important to quantify distribution of features and their roughness. Fractal analyses in thin films are used to compute the fractal dimension (D), equivalent roughness, Hurst exponent (H), correlation lengths (k), etc., to understand the growth mechanisms of the films using different deposition methods and

Advances in manufacturing analysis: fractal theory in modern manufacturing

25

conditions [5557]. These measurements are usually undertaken on topography data obtained from atomic force microscope (AFM) and scanning electron microscope (SEM) images. Here, some of the results of fractal analyses and applications to thin films are presented. A recent study by Ghosh and Pandey in 2019 investigated the effect of substrate type on the characteristics of Indium-doped zinc oxide (IZO) deposited on glass (IZO/glass), indium tin oxide (IZO/ITO), and silicon (IZO/Si) through solgel spin coating method [47]. Besides the statistical roughness characterization, both mono- and multifractal analyses were employed for the three substrates. The study used PSDFs and box counting methods to compute the fractal dimensions for the three substrates (Fig. 2.11). The correlation function (k), which denotes the short range spread of the surface complexity was computed using the heightheight correlation functions. Fig. 2.12 shows the plot of the root mean square (RMS) roughness against the average fractal dimensions obtained from the two methods as reported by Ghosh and Pandey (2019). The samples deposited on silicon substrates were shown to exhibit the highest RMS values and the lowest average values of D whereas, IZO deposited on glass substrates have the lowest RMS and highest average values of D. As shown in Fig. 2.12,

Figure 2.11 Computation of fractal dimensions from AFM images of IZO deposited on glass, ITO, and Si via solgel spin coating. Obtained from Ghosh K, Pandey RK. Fractal and multifractal analysis of In-doped ZnO thin films deposited on glass, ITO, and silicon substrates. Appl Phys A 2019;125(2):98 with permission from SpringerNature license no. 4571870732797.

26

Fredrick M. Mwema et al.

Figure 2.12 Relationship between RMS roughness and average fractal dimensions. Obtained from the power spectrum and box counting methods in Fig. 2.11 [47].

RMS exhibits a linearly decreasing relationship with D with a strong correlation between the two variables as R2 5 0.9991 and the regression equation as RMS 5 2231.85D 1 585.06 [47]. The results imply that IZO deposited on glass substrates (IZO/glass) exhibited a complex lateral molecular ordering of fine and small crystals whereas IZO on silicon substrates had simple lateral molecular arrangement and large crystals. As such, fractal dimension is an important tool to understand growth mechanisms of films on different substrates for better choice of the substrate type for different applications of thin films. In rather a related study, Soumya et al. in 2017 investigated the relationships among the fractal dimension, surface roughness, and annealing temperature of zinc sulfide (ZnS) thin films deposited on quartz substrates via pulsed laser deposition technique [48]. After deposition, the films were annealed in argon gas conditions at 300 C, 400 C, 500 C, and 600 C and similar to Ghosh and Pandey [47], the fractal dimensions of the AFM images obtained at the surfaces of the films were computed. The RMS roughness was shown to increase with the annealing temperature; however, the two fractal dimension computations yielded contradicting results with the box counting method showing decrease of D with the temperature while power spectrum method D values increased up to 500 C beyond which they started to decrease. However, the correlation coefficients, R2, for all the temperatures in the power spectrum method were

Advances in manufacturing analysis: fractal theory in modern manufacturing

27

too low (ranging between 0.33 and 0.76) [48]. As such, the study chose the results from the box counting method since higher correlation coefficients (B0.999) were obtained. The choice of fractal dimension method in thin films depend on the nature of the AFM digital data (images) available and as noted in this study, images with many voids (porosity) provide better results with box counting method. It is also noted that thin films’ images with less clarity (in which the grain boundaries cannot be observed) should be analyzed through manual box counting rather than a computer software. As shown in Fig. 2.13, the box counting values of D decreased with the increase in annealing temperature. Annealing transforms ZnS thin films from amorphous to crystalline structure [58] between annealing temperatures of 100 C and 300 C. Within this temperature range there is growth of grains and atomic ordering leading to increase in surface roughness. Beyond 300 C, there is agglomeration and formation of interconnected islands of ZnS structures as reported in Ref. [59]. The atomic ordering and subsequent agglomeration of the ZnS structures is responsible for the decreased fractal dimensions in study [48]. Talu et al. in 2016 studied the evolution of the fractal characteristics of gold nanoparticles embedded in carbon films using areal autocorrelation function (AACF) [50]. The films were prepared via radiofrequency plasma enhanced chemical vapor deposition technique at powers ranging between 80 and 120 W. Using the AACF formula [60] on the AFM

Figure 2.13 Variation of fractal dimension with the annealing temperature of ZnS prepared on quartz substrates via PLD [48].

28

Fredrick M. Mwema et al.

Figure 2.14 The evolution of bifractal characteristics (D1 and D2) and RMS roughness of gold nanoparticles embedded on carbon films as reported by Talu et al. [50].

images of the films, bi-log plots of structure functions (S) versus separation lags (τ) were generated from which the fractal dimensions were determined using the power law defined as S 5 Kτ 2ð22DÞ where K is defined as pseudo-topothesy [50]. These plots revealed bifractal nature of these films such that two values of D (D1 and D2) were obtained for each power. The summary of the fractal dimensions and RMS values from this study are illustrated in Fig. 2.14. There were no direct correlations between the deposition power and surface roughness of the films with the highest RMS values reported at 100 W and the lowest at 110 W. Additionally, the fractal dimensions (D1 and D2) were uncorrelated with the deposition power (R2 5 0.0176) and the RMS values. These results may imply that there exists an optimal value of power for quality preparation of the gold nanoparticles onto the carbon film and, thus, a need to undertake a design of experiment for the fabrication of the thin films. In other studies, Mwema et al. has illustrated the use of PSDFs to compute the fractal dimensions, correlation lengths, Hurst exponents, and equivalent roughness of aluminum thin films sputtered on various metallic substrates [3,39,55]. The fractal dimension (D) was shown to increase with the RMS values for Al thin films sputtered on metallic substrates. Through fractal analyses, it was possible to show that increasing the substrate temperature between room temperature and 100 C results in lateral growth rather than vertical build-up of the sputtering material [56]. For further information regarding applications of fractal theory in thin films,

Advances in manufacturing analysis: fractal theory in modern manufacturing

29

the readers are referred to some of the existing references [46,51,6167]. There is a consensus from these literatures that a lot of work has been undertaken on thin films with emphasis on understanding the relationships among the deposition parameters/conditions, growth mechanisms, posttreatment processes, and surface roughness. Future works should attempt to utilize the complex geometry (fractal) theories to predict the growth mechanisms and process interrelationships with the properties of the fabricated thin films.

2.3.2 Fractal analyses in laser manufacturing Fractal analysis is utilized in laser processed surfaces to understand their hierarchal evolution at different length scales and relate the results to their preparation, performance, and application. A study by Kurella and Dahore [68] utilized the box counting method to study the nature of CaTiO3 coating deposited on Ti alloy. The aim of the study was to achieve a biomimetic coating for biocompatibility applications. SEM images were obtained on the surface of the coating using different magnifications (up to B40 kX) and then taken through an image analyses in ImageJ software as described in the article [68]. The D values were computed for laser speeds denoted as low (,175 cm/min), medium (175275 cm/min), and high ( . 275 cm/min). It was observed that the fractal dimensions for high and low laser speeds varied considerably with the SEM magnifications. On the contrary, the values of D for the medium laser speed deposition of the coating remained nearly constant across the various SEM magnifications. It was, therefore, possible for the authors to use the medium laser speeds to manufacture samples with better biomimetic precipitation. This understanding is important when fractal scan strategy of the laser beam is necessary for manufacturing of fractal structures such as the third order Hilbertand and second order Peano-Gosper configuration [69] and other ordered structures [17]. Typical ordered structures of 3D printed heat exchanger as developed by Wang et al. [17] are presented in Fig. 2.15. In another study, the fractal dimensions of laser machined surfaces of structural carbon steel Q235 were computed [70]. The machining was undertaken using CO2 Laser on four different combinations of process parameters, that is, laser power, machining speed, auxiliary gas pressure, and thickness of the steel sample. The topography data was then obtained on laser machined surfaces using white light interferometer at scan size of

30

Fredrick M. Mwema et al.

Figure 2.15 Illustrating CAD designs of fractal-tree-like heat exchangers manufactured through 3D printing, (A) Y-pattern and (B) H-pattern types. Adapted from Wang et al. Experimental and numerical investigation of fractal-tree-like heat exchanger manufactured by 3D printing. Chem Eng Sci 2019;195:250261 with permission from Elsevier license no. 4597030946013.

550 3 550µm. For all the samples, 3D height profile images were obtained. The fractal dimensions for the samples were computed using box-counting method. The values of D were shown to generally increase with decreasing average roughness (Ra) although the correlation was not very strong (R2 5 0.8477). Large values of D in laser machining imply that the surface is fine and has dense texture, indicating better machined surface. On the other hand, small values of D indicate coarse and sparse texture implying that the obtained surface has defects and deep cuts [70]. In a related study, Zhao et al. in 2013, investigated the fractal behavior of surface of laser machined heavy plate to understand the mechanism of cutting and processing parameters [71]. The surface topography was obtained using Laser Scanning Confocal Microscope (LSCM) and using the box counting method, the laser machined surfaces were seen to exhibit fractal characteristics. Contrary to the former study, there was no linear relationship between D and Ra in this study. However, the authors were able to comprehensively explain the complexity of surface topography and its relationship to the processing parameters during laser cutting. There is increasing need for manufacturing of fractal-like structures and components for various high-performance applications. One such need is in the field of heat exchangers (heat transfer devices) for cooling in advanced applications such as electronics, microreactors, and fuel cell [17,72]. Laser additive manufacturing has the highest potential to produce such fractal-like components [73,74]. To accurately reproduce the fractal

Advances in manufacturing analysis: fractal theory in modern manufacturing

31

features onto a laser manufactured product, it is therefore necessary to explore fractal analysis for various laser processing parameters. It can be noted that there are few published works directly analyzing the fractal behavior of laser manufactured components despite these increasing efforts to produce fractal-like structures.

2.3.3 Fractal analyses in machining Most surfaces machined through milling, turning, drilling, grinding, and electric discharge operations exhibit self-affinity characteristics [75]. As such various studies have been conducted on fractal analyses of machined surfaces using different methods. The power spectrum method has been used on the AFM images of ground surfaces as reported in Ref. [75]. An early work evaluated the applications of variation, box counting, cover, and power spectrum methods on computation of fractal dimensions of profiles of surfaces obtained via turning, electrical discharge, and grinding [76]. The variation method was determined as the best technique for determination of fractal dimensions during machining in that study. Fractal analyses can be used to evaluate the effect of variations of the cutting forces during a milling operation as illustrated by Namazi, Farid, and Seng [77]. As illustrated, the cutting depth in a milling operation is a direct indicator of the variations of the cutting forces and as such the concept of fractals in the time series of the force variations can be used to determine the fractal dimensions in a machining process. Using this concept and box counting method, study by Namazi et al. [77] investigated the effect of cutting depth on the fractal nature of the cutting forces during wet and dry milling operations. It was established that for both wet and dry milling, the fractal dimension of the cutting force signals decreased with the increase in the depth of cutting. These results indicate that as the depth of cut increases the force signal becomes less complex since as the deeper cuts increases the area of toolworkpiece interface and therefore reduces the complexity of the force signal. It was also reported that for low depth of cut the fractal dimensions were larger in dry machining than in the wet conditions implying greater complexity in the force signal in dry machining [77]. A similar research used fractal characteristics of cutting forces and acoustic emission (AE) signals to study the wear properties during machining of CFRP [78]. The regularized box counting method used on the signals was shown to efficiently describe the tool wear evolution and hence

32

Fredrick M. Mwema et al.

the quality of machining. In a related study, Li et al. in 2018 studied the fractal characteristics of milled surfaces of different roughness using wavelet-based technique [79]. The surface profiles of the machined surfaces were obtained with a Talysurf PGI 1240 profiler and the wavelet algorithms were used to compute the fractal dimensions and established that fractal dimension increased with decrease in the average roughness (Ra) values of the milled surfaces. Grzesik and Zak [80] presented a comparison of surface textures of hardened steel parts machined through hard turning, belt grinding, and externally honed. The 3D profiles of the machined surfaces were obtained by contact profilometer diamond stylus and various topography parameters determined using Mountains Map Software. The fractal dimensions were reported and related to the roughness properties in which the hard-turned surfaces were shown to have the lowest roughness and fractal dimension values. The honed surfaces were shown to have the highest fractal dimensions whereas the surfaces obtained from the belt grinding exhibited the highest roughness values [80,81]. Other larger pool of resources of application of fractal theory in machining operations are available in various databases [8284]. The general finding is that fractal analysis has been explored majorly for academic purposes and that its applications in modern machining operations is still rare due to its complexity and unfamiliar chaos theory to the industry. Based on the published works, it is of consensus that fractal theory can be useful for sustainable manufacturing/machining [85], machining process monitoring [8688], machine maintenance [89], diagnosis of various machine parts [90], and tool wear analysis [9194]. More research is recommended on more modern machining operations to exploit the potential of the fractals.

2.3.4 Fractal analyses in friction stir The surface topography of materials produced through friction stir welding (FSW) has been analyzed through fractal methods by various researchers. Zuo et al. in 2018 used pixel-covering method to investigate the effect of process parameters on the surface topography of AA7075 aluminum alloy welded at different rotational and welding speeds [5]. The microtopography images obtained through SEM were taken through image analysis and computation of the fractal dimension in a MATLAB program. It was reported that the fractal dimension decreases with the

Advances in manufacturing analysis: fractal theory in modern manufacturing

33

rotational speed and increases with the welding speed. Contrary to most thin films and machining, there was a direct relationship between the fractal dimension and roughness of the friction stir welding surfaces as reported in this study [5]. A different relationship between the fractal dimension and weld/rotational speeds was established by Das et al. [95]. Images of the friction stir welded surfaces were taken using digital camera, from which box counting and 2D wavelet analysis were used to compute the fractal dimensions [95,96]. The study concluded that fractal theory can be used to monitor the effectiveness of the friction stir welding process. Determination of the fractal dimensions using waveform method proposed by Katz [97] can be used to detect defects in friction stir welds as illustrated by Das et al. [88]. It is believed that fractal dimensions extracted from signals obtained in a friction stir welding process can indicate the defective regions of the weld. In this study [88], variation (increase or decrease) in the fractal dimension of the total rotation speed signals of the friction stir welding indicated defects in the weld. Higuchi algorithms implemented in MATLAB program have also been used on the time series of the spindle motor currents and tool rotational speeds [98]. A general summary of the application of fractal theory in friction stir processes is illustrated in Fig. 2.16.

Figure 2.16 Summary of the computation of fractal dimension (D) concept in friction stir processes. The topography images were obtained from Bhat NN, Kumari K, Dutta S, Pal SK, Pal S. Friction stir weld classification by applying wavelet analysis and support vector machine on weld surface images. J Manuf Process 2015;20:274281 [99] with permission from Elsevier (license number 4597060545144).

34

Fredrick M. Mwema et al.

It is clear from the preceding discussion that there are very few publications on the fractal analysis of the friction stir welding and processing despite its significance in defect and quality assessment of the friction stir processes. Future works are necessary to explore on further applications fractal theory on friction stir processing and welding.

2.4 Conclusions In this chapter, a brief overview on the significance of the fractal theory in manufacturing is presented and it has been learnt that most manufacturing processes have fractal behavior and the following conclusions can be drawn: • Fractal dimensions are used to estimate the self-similar/affine characteristics of manufacturing processes and can be determined by either using the signals (wavelet) obtained directly from the process or via image analysis of the topography profiles of the surfaces of the manufactured products. • There exists a relationship between the fractal dimension and roughness of the surfaces of component manufactured through different processes. In thin film surfaces, the RMS roughness exhibits an indirect relationship with the fractal dimension. It implies that process parameters, which lead to increase in surface roughness, are indirectly related to the fractal dimension. On the contrary, the surface roughness and fractal dimensions exhibit a proportional relationship in friction stir welding processes. These relationships are not exhaustive and further research into various aspects of manufacturing are necessary to develop more reliable models. • From the literature reviewed in this chapter, very little efforts were observed in determining the effective computation techniques of fractal dimensions for specific manufacturing processes. Future works should determine on the effectiveness of using either image analysis or signal processing in determining the fractal characteristics of different manufacturing processes. Such studies should guide on the accuracy of any of the computation paths.

Acknowledgment Acknowledgment to the University of Johannesburg for awarding Global Excellence Stature (GES) 4.0 postdoctoral scholarship 2019-2020.

Advances in manufacturing analysis: fractal theory in modern manufacturing

35

References [1] Lopes R, Betrouni N. Fractal and multifractal analysis: a review. Med Image Anal 2009;13(4):63449. [2] T˘ ¸ alu S¸ , Bramowicz M, Kulesza S, Ghaderi A, Dalouji V, Solaymani S, Khalaj Z, et al. Microstructure and micromorphology of Cu/Co nanoparticles: surface texture analysis. Electron Mater Lett 2016;12(5):5808. [3] Mwema FM, Oladijo OP, Akinlabi ET. The use of power spectrum density for surface characterization of thin films. In: Yang X-Y, editor. Photoenergy and Thin Film Materials. Hoboken, NJ: John Wiley & Sons, Inc; 2019. p. 379411. [4] Chand S, Dixit VV. Application of Fractal theory for crash rate prediction: insights from random parameters and latent class tobit models. Accid Anal Prev 2018;112 (2017):308. [5] Zuo L, Zuo D, Zhu Y, Wang H. Effect of process parameters on surface topography of friction stir welding. Int J Adv Manuf Technol 2018;98(58):180716. [6] Agterberg FP, Cheng Q. Introduction to special issue on ‘fractals and multifractals,’. Comput Geosci 1999;25(9):9478. [7] Yang X, Zhang R, Ma S, Yang X, Wang F. Fractal dimension of concrete mesostructure based on X-ray computed tomography. Powder Technol 2019;350:919. [8] Liu Y, Wang C, Zhang Y, Xiao S, Chen Y. Fractal process and particle size distribution in a TiH2 powder milling system. Powder Technol 2015;284:2728. [9] Chen W-K, Lee J-C, Han W-Y, Shih C-K, Chang K-C. Iris recognition based on bidimensional empirical mode decomposition and fractal dimension. Inf Sci (NY) 2013;221:43951. [10] Peng X, Qi W, Su R, He Z. Describing some characters of serine proteinase using fractal analysis. Chaos Soliton Fract 2012;45(7):101723. [11] Melendez J, Garcia MA, Puig D, Petrou M. Unsupervised texture-based image segmentation through pattern discovery. Comput Vis Image Underst 2011;115 (8):112133. [12] Neil G, Curtis K. Shape recognition using fractal geometry. Pattern Recognit 1997;30(12):195769. [13] Ikeda T. Multifractal structures for the Russian stock market. Phys A Stat Mech Appl 2018;492:21238. [14] Wang H-Y, Wang T. Multifractal analysis of the Chinese stock, bond and fund markets. Phys A Stat Mech Appl 2018;512:28092. [15] Mandelbrot BB. Self-affine fractals and fractal dimension. Phys Scr 1985;32:25760. [16] Pence D. The simplicity of fractal-like flow networks for effective heat and mass transport. Exp Therm Fluid Sci 2010;34(4):47486. [17] Wang G, Gu Y, , et al.Zhao L, , et al.Zeng G, , et al.Tang Z, , et al.Sun Y Experimental and numerical investigation of fractal-tree-like heat exchanger manufactured by 3D printing. Chem Eng Sci 2019;195:25061. [18] Zuo R, Wang J. Fractal/multifractal modeling of geochemical data: A review. J Geochem Explor 2016;164:3341. [19] Chen X, Li T, Shen J, Hu Z. Fractal design of microfluidics and nanofluidics-A review. Chemometr Intell Lab Syst 2016;155:1925. [20] Joshi B, Beccard S, Vilgis TA. Fractals in crystallizing food systems. Curr Opin Food Sci 2018;21:3945. [21] Pippa N, Dokoumetzidis A, Demetzos C, Macheras P. On the ubiquitous presence of fractals and fractal concepts in pharmaceutical sciences: a review. Int J Pharm 2013;456(2):34052. [22] Kesi´c S, Spasi´c SZ. Application of Higuchi’s fractal dimension from basic to clinical neurophysiology: a review. Comput Methods Prog Biomed 2016;133:5570.

36

Fredrick M. Mwema et al.

[23] Mandelbrot B. How long is the Coast of Britain? Statistical self-similarity and fractional dimension. Science (80) 1967;156(3775):6368. [24] Annadhason A. Methods of fractal dimension computation. IRACST -Int J Comput Sci Inf Technol Secur 2012;2(1):22499555. [25] Nayak SR, Mishra J, Khandual A, Palai G. Fractal dimension of RGB color images. Optik (Stuttg) 2018;162:196205. [26] Li J, Du Q, Sun C. An improved box-counting method for image fractal dimension estimation. Pattern Recognit 2009;42(11):24609. [27] Liu Y, Chen L, Wang H, Jiang L, Zhang Y, Zhao J, et al. An improved differential box-counting method to estimate fractal dimensions of gray-level images. J Vis Commun Image Represent 2014;25(5):110211. [28] Jiménez J, Ruiz de Miras J. Fast box-counting algorithm on GPU. Comput Methods Prog Biomed 2012;108(3):122942. [29] Nayak SR, Mishra J, Palai G. An extended DBC approach by using maximum Euclidian distance for fractal dimension of color images. Optik (Stuttg) 2018;166: 11015. [30] Nayak SR, Mishra J. An improved method to estimate the fractal dimension of colour images. Perspect Sci 2016;8:41216. [31] Chow WC. Fractal (fractional) Brownian motion. Wiley Interdiscip Rev Comput Stat 2011;3(2):14962. [32] Lou S, Ouyang C. Fractal dimensions of rough differential equations driven by fractional Brownian motions. Stoch Proc Appl 2015;126(8):241029. [33] Yadav RP, Agarwal DC, Kumar M, Rajput P, Tomar DS, Pandey SN, et al. Effect of angle of deposition on the fractal properties of ZnO thin film surface. Appl Surf Sci 2017;416:518. ˇ cíková H, Percival DB. Estimators of fractal dimension: assessing the [34] Gneiting T, Sevˇ roughness of time series and spatial data. Stat Sci 2012;27(2):24777. [35] Mukherjee K, Ghosh JK, Mittal RC. Variogram fractal dimension based features for hyperspectral data dimensionality reduction. J Indian Soc Remote Sens 2013;41(2): 24958. [36] Jacobs TDB, Junge T, Pastewka L. Quantitative characterization of surface topography using spectral analysis. Surf Topogr Metrol Prop 2017;5(1):013001. [37] Raoufi D. Fractal analyses of ITO thin films: a study based on power spectral density. Phys B Condens Matter 2010;405(1):4515. [38] Gavrila R, Dinescu A, Mardare D. A power spectral density study of thin films morphology based on AFM profiling. Rom J Inf Sci Technol 2007;10(3):291300. [39] Mwema FM, Oladijo OP, Sathiaraj TS, Akinlabi ET. Atomic force microscopy analysis of surface topography of pure thin aluminium films. Mater Res Express 2018; 5(4):115. [40] Gong Y, Misture ST, Gao P, Mellott NP. Surface roughness measurements using power spectrum density analysis with enhanced spatial correlation length. J Phys Chem C 2016;120(39):2235864. [41] Senthilkumar M, Sahoo NK, Thakur S, Tokas RB. Characterization of microroughness parameters in gadolinium oxide thin films: a study based on extended power spectral density analyses. Appl Surf Sci 2005;252(5):160819. [42] Asvestas P, Matsopoulos GK, Nikita KS. A power differentiation method of fractal dimension estimation for 2-D signals. J Vis Commun Image Represent 1998;9(4): 392400. [43] Florio BJ, Fawell PD, Small M. The use of the perimeter-area method to calculate the fractal dimension of aggregates. Powder Technol 2019;343:5519. [44] Guérin L, Frances C, Liné A, Coufort-Saudejaud C. Fractal dimensions and morphological characteristics of aggregates formed in different physico-chemical and

Advances in manufacturing analysis: fractal theory in modern manufacturing

[45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63]

37

mechanical flocculation environments. Colloids Surf A Physicochem Eng Asp 2019;560:21322. Chen Z, Liu Y, Zhou P. A comparative study of fractal dimension calculation methods for rough surface profiles. Chaos Soliton Fract 2018;112:2430. T˘ ¸ alu S¸ , Morozov IA, Yadav RP. Multifractal analysis of sputtered indium tin oxide thin film surfaces. Appl Surf Sci 2019;65(3):294300. Ghosh K, Pandey RK. Fractal and multifractal analysis of In-doped ZnO thin films deposited on glass, ITO, and silicon substrates. Appl Phys A 2019;125(2):98. Soumya S, Swapna MS, Raj V, Mahadevan Pillai VP, Sankararaman S. Fractal analysis as a potential tool for surface morphology of thin films. Eur Phys J Plus 2017; 132(12):551. T˘ ¸ alu S¸ , Luna C, Ahmapourian A, Achour A, Arman A, Naderi S, et al. Micromorphology and fractal analysis of nickelcarbon composite thin films. J Mater Sci Mater Electron 2016;27(11):1142531. T˘alu S¸ , Bramowicz M, Kulesza S, Solaymani S, Shafikhani A, Ghaderi A, et al. Gold nanoparticles embedded in carbon film: micromorphology analysis. J Ind Eng Chem 2016;35:15866. Naseri N, T˘alu S¸ , Kulesza S, Qarechalloo S, Achour A, Bramowicz M, et al. How morphological surface parameters are correlated with electrocatalytic performance of cobalt-based nanostructures. J Ind Eng Chem 2018;57:97103. Stach S, Sapota W, T˘alu S¸ , Ahmapourian A, Luna C, Ghobadi N, et al. 3-D surface stereometry studies of sputtered TiN thin films obtained at different substrate temperatures. J Mater Sci Mater Electron 2017;28(2):211322. Yadav RP, Kumar M, Mittal AK, Pandey AC. Fractal and multifractal characteristics of swift heavy ion induced self-affine nanostructured BaF 2 thin film surfaces. Chaos 2015;25(8):083115. Kavyashree, et al. Substrate effect on the evolution of surface morphology of BaF2thin films: a study based on fractal concepts. Appl Surf Sci 2018;77(4):74354. Mwema FM, Oladijo OP, Akinlabi ET. Effect of substrate temperature on aluminium thin films prepared by RF-magnetron sputtering. Mater Today Proc 2018;5 (9):2046473. Mwema FM, Akinlabi ET, Oladijo OP, Majumdar JD. Effect of varying low substrate temperature on sputtered aluminium films. Mater Res Express Jan. 2019;6(5): 056404. Yadav RP, Kumar M, Mittal AK, Dwivedi S, Pandey AC. On the scaling law analysis of nanodimensional LiF thin film surfaces. Mater Lett 2014;126(July):1235. Ahn H, Um Y. Post-annealing effects on ZnS thin films grown by using the CBD method. J Korean Phys Soc 2015;67(6):104550. Vashistha IB, Sharma MC, Sharma SK. Post annealing treatment of zinc sulphide thin film as a buffer layer for solar cell application. Surf Eng 2017;33(4): 299304. Neˇcas D, Klapetek P. One-dimensional autocorrelation and power spectrum density functions of irregular regions. Ultramicroscopy 2013;124:1319. Təlu ¸ S¸ , Patra N, Salerno M. Micromorphological characterization of polymer-oxide nanocomposite thin films by atomic force microscopy and fractal geometry analysis. Prog Org Coat 2015;89:506. T˘ ¸ alu S¸ , Bramowicz M, Kulesza S, Ghanderi A, Solaymani S, Savaloni H, et al. Micromorphology analysis of specific 3-D surface texture of silver chiral nanoflower sculptured structures. J Ind Eng Chem 2016;43:1649. T˘ ¸ alu S¸ , Kulesza S, Bramowicz M, Pringle AM, Pearce JM, Murugesan M, et al. Micromorphology analysis of sputtered indium tin oxide fabricated with variable ambient combinations. Mater Lett 2018;220:16971.

38

Fredrick M. Mwema et al.

[64] T˘ ¸ alu S¸ , Bramowicz M, Kulesza S, Solaymani S. Topographic characterization of thin film field-effect transistors of 2,6-diphenyl anthracene (DPA) by fractal and AFM analysis. Mater Sci Semicond Process 2018;79:14452. [65] T˘ ¸ alu S¸ , Bramowicz M, Kulesza S, Dalouji V, Ilkhani M, Ghaderi A, et al. Influence of annealing process on surface micromorphology of carbonnickel composite thin films. Opt Quantum Electron 2017;49(6). [66] T˘ ¸ alu S¸ , Bramowicz M, Kulesza S, Dalouji V, Solaymani S, Kenari MF, et al. Fractal features and surface micromorphology of diamond nanocrystals. J Microsc 2016; 264(2):14352. [67] T˘ ¸ alu S¸ . Characterization of surface roughness of unworn hydrogel contact lenses at a nanometric scale using methods of modern metrology. Polym Eng Sci 2013;47: 214150. [68] Kurella AK, Dahotre N. Fractal approach to hierarchically evolved laser processed CaP coatings. Adv Eng Mater 2010;12(6):51721. [69] Catchpole-smith S, Aboulkhair N, Parry L, Tuck C, Ashcroft IA, Clare A. Fractal scan strategies for selective laser melting of ‘unweldable’ key words: selective laser melting, nickel alloys, scan strategies. Addit Manuf 2017;15:11322. [70] Chen H, Zhou Y. Fractal characteristics of 3D surface topography in laser machining. IOP Conf Ser Mater Sci Eng 2018;382(4). [71] Zhao L, Zhang Y, Ma DG, Li W. Fractal analysis of laser cutting heavy plate surface topography. Appl Mech Mater 2013;395396:104952. [72] Lohtander M, Valkeapää S, Varis J. The capability of the laser based additive manufacturing process in the manufacture of fractal like heat transfer devices. Key Eng Mater 2013;572:6058. [73] Chiu WK, Yeung YC, Yu KM. Toolpath generation for layer manufacturing of fractal objects. Rapid Prototyping J 2006;12(4):21421. [74] Hengsbach S, Lantada AD. Direct laser writing of fractal surfaces: strategy to design and manufacture textured materials. Adv Eng Mater 2015;17(2):17280. [75] Jiang Z, Wang H, Fei B. Research into the application of fractal geometry in characterising machined surfaces. Int J Mach Tools Manuf 2001;41(1314):217985. [76] Hasegawa M, Liu J, Okuda K, Nunobiki M. Calculation of the fractal dimensions of machined surface profiles. Wear 1996;192(12):405. [77] Namazi H, Farid AA, Seng CT. Fractal-based analysis of the influence of cutting depth on complex structure of cutting forces in rough end milling. Fractals 2018;26 (05):1850068. [78] Rimpault X, Chatelain JF, Klemberg-Sapieha JE, Balazinski M. Fractal analysis of cutting force and acoustic emission signals during CFRP machining. Procedia CIRP 2016;46:1436. [79] Li G, Zhang K, Gong J, Jin X. Calculation method for fractal characteristics of machining topography surface based on wavelet transform. Procedia CIRP 2019;79:5004. ˙ K. Characterization of surface textures generated on hard[80] Grzesik W, Rech J, Zak ened steel parts in high-precision machining operations. Int J Adv Manuf Technol 2015;78(912):204956. ˙ K. High-precision machining of hard steel parts using special abra[81] Grzesik W, Zak sive operations. In: Lecture Notes Mech Engineering notes Mech Eng; 2017. 297308. [82] Hotar V, Salac P. Surface evaluation by estimation of fractal dimension and statistical tools. Sci World J 2014;2014:110. [83] Rimpault X, Balazinski M, Chatelain J-F. Fractal analysis application outlook for improving process monitoring and machine maintenance in manufacturing 4.0. J Manuf Mater Process 2018;2(3):62.

Advances in manufacturing analysis: fractal theory in modern manufacturing

39

[84] Muguthu JN, Gao D. Profile fractal dimension and dimensional accuracy analysis in machining metal matrix composites (MMCs). Mater Manuf Process 2013;28(10): 11029. [85] Peralta ME, Marcos M, Aguayo F, Lama JR, Córdoba A. Sustainable fractal manufacturing: a new approach to sustainability in machining processes. Procedia Eng 2015;132:92633. [86] Bukkapatnam STS, Kumara SRT, Lakhtakia A. Analysis of acoustic emission signals in machining. J Manuf Sci Eng 1999;121(4):568. [87] Rimpault X, Bitar-Nehme E, Balazinski M, Mayer JRR. Online monitoring and failure detection of capacitive displacement sensor in a Capball device using fractal analysis. Measurement 2018;118:238. [88] Das B, Bag S, Pal S. Defect detection in friction stir welding process through characterization of signals by fractal dimension. Manuf Lett 2016;7:610. [89] Saravanan S, Yadava GS, Rao PV. Condition monitoring studies on spindle bearing of a lathe. Int J Adv Manuf Technol 2006;28(9):9931005. [90] Yang J, Zhang Y, Zhu Y. Intelligent fault diagnosis of rolling element bearing based on SVMs and fractal dimension. Mech Syst Signal Process 2007;21(5):201224. [91] Kassim AA, Mian AAMannan MA. Texture analysis using fractals for tool wear monitoring. In: Proc Int Conf Image Process; 2002. p. III-105III-108. [92] Chen MJ, Ni ZJ, Fang L. Research on tool wear based on texture fractal dimension. Appl Mech Mater 2011;6668:11636. [93] Prabhu S, Vinayagam BK. Fractal dimensional surface analysis of AISI D2 Tool steel material with nanofluids in grinding process using atomic force microscopy. J Braz Soc Mech Sci Eng 2011;33(4):45966. [94] Bukkapatnam STS, Kumara SRT, Lakhtakia A. Fractal estimation of flank wear in turning. J Dyn Syst Meas Control 2000;122(1):89. [95] Das B, Pal S, Bag S. Monitoring of friction stir welding process using weld image information. Sci Technol Weld Join 2016;21(4):31724. [96] Chen X, Li J, Han H, Ying Y. Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors. R Soc Open Sci 2018;5(5):180087. [97] Katz MJ. Fractals and the analysis of waveforms. Comput Biol Med 1988;18 (3):14556. [98] Das B, Bag S, Pal S. Probing weld quality monitoring in friction stir welding through characterization of signals by fractal theory. J Mech Sci Technol 2017;31(5): 245965. [99] Bhat NN, Kumari K, Dutta S, Pal SK, Pal S. Friction stir weld classification by applying wavelet analysis and support vector machine on weld surface images. J Manuf Process 2015;20:27481.

CHAPTER THREE

Weldability appraisement of dissimilar metal joints: application of ultrasonic spot welding to Li-ion batteries Mantra Prasad Satpathy1, Bharat Chandra Routara1 and Susanta Kumar Sahoo2 1

School of Mechanical Engineering, KIIT Deemed University, Bhubaneswar, India Department of Mechanical Engineering, National Institute of Technology, Rourkela, India

2

3.1 Introduction Lithium-ion (Li-ion) batteries are now extensively adopted by many automotive manufacturing industries due to its high energy storing capacity, reliability, safety, robust, and lightweight nature [1]. These manufacturing industries are developing fully featured loaded electric vehicles (EVs), which follow the strict statutory regulations and reduces the emission of greenhouse gases [2]. In this cutting-edge research and development in EVs, automobile manufacturers are aiming at reducing the weight of the automobile and implementing the latest powertrain technology with the assistance of intelligent systems. This requires highly efficient energy storing systems like Li-ion batteries. Thus, there is an ample amount of requirement of battery manufacturing, which contains a large number of cells to be interlinked either in series or parallel to deliver the required power and driving range. Most of the Li-ion batteries are used as pouch cell format in automobiles. This format employs a tab-to-busbar interconnects for the transmission of electrical power. The combination of these pouch cells forms a module, and hundreds of modules are interconnected in a battery pack which ultimately defines the power of the Li-ion battery pack. The busbar is the primary element that decides the effectiveness of Li-ion batteries by providing the desired amount of electrical, thermal and mechanical Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00003-8

© 2020 Elsevier Ltd. All rights reserved.

43

44

Mantra Prasad Satpathy et al.

properties. Moreover, the energy-carrying capacity and the cost of Li-ion batteries are mainly based on the selection of its material and thickness [3]. The materials used in the busbar should have high electrical and thermal conductivities with suitable thickness to meet the excessive heat generation because of the joint resistance. Typically, aluminum (Al) and copper (Cu) are commonly used materials not only in the domains of busbars, power device modules packing, and Li-ion batteries assembly but also these materials are extensively used in microelectronic technology [4]. Unfortunately, the joining of this material by fusion spot-welding process produces bulk and brittle intermetallic compounds (IMCs), a high level of weld distortion, and an average joint strength [5]. Due to this reason, an alternative solid-state welding process came up with the absence of these inferior properties. Ultrasonic spot welding (USW) is an environmentally friendly and low-cost method to produce the joint between dissimilar sheets within a few seconds. In comparison to the fusion spot welding, USW has far shorter weld cycle, and it can produce stronger joints on the basis of the same weld region [6,7]. It also consumes less energy per joint than fusion spot welding. The current research work is focused on the analysis of welding of Al and Cu joints by using the USW process to discover the effects of different welding parameters such as weld pressure, weld time, weld energy, and vibration amplitude on the T-peel and tensile shear failure loads of the joints. Moreover, a systematic approach is followed to improve the joining quality of the welded sheets through an in-depth analysis of the weld interface using scanning electron microscopy (SEM) with various microstructural characterization approaches. Microhardness of the crosssectional weld area is also studied to reveal the material softening and hardening phenomena during the welding process.

3.2 USW process In the 1950s, the USW method was first established for thin metal foil joining, tube sealing, and wire bonding [8]. As it is a solid-state joining process, the bond between two or more metal sheets is formed by the application of continuous shearing vibration of the sonotrode in an ultrasonic frequency with a particular amount of clamping pressure.

Weldability appraisement of dissimilar metal joints

45

Meanwhile, this shearing action causes friction between the two parts and removes any type of contaminants or oxide layer present on the faying surface. Thus, there is close contact between the two cleaned surfaces generating the local heat at the weld region. Initially, the tiny interatomic bonds are formed at the interface, and these are gradually expanded with respect to time. The frequency of ultrasonic welding is between the range of 20 and 100 kHz. A typical ultrasonic cycle takes about less than 1 s to complete the welding process. Furthermore, it has the quality of direct joining of dissimilar materials without requiring a flux. The schematic diagram of USW is illustrated in Fig. 3.1.

3.3 USW system These spot welders are categorized into two configurations, namely the lateral drive system and wedge reed system. However, these two types of systems have different shapes and applications. But, the principle of the deformation in the weld area by these vibrational mechanisms remains the same [9].

3.3.1 Lateral drive spot welding system This type of welding system is comprised of the ultrasonic frequency generator with a power amplifier, transducer, booster, sonotrode with

Figure 3.1 Schematic illustration of USW process.

46

Mantra Prasad Satpathy et al.

weldable tips, and anvil, as shown in Fig. 3.2 [11]. Initially, the 50 Hz frequency of standard alternating current (AC) supply is converted to highfrequency power (15 70 kHz) with the help of an ultrasonic frequency generator, and its strength is increased by the power amplifier. The piezoelectric transducer/converter is made up of lead zirconatetitanate (PbZnTi) crystals/ceramic rings. When the voltage with high frequency is applied to these rings [10], a large mechanical displacement is observed. The booster subsequently amplifies the transducer’s vibration amplitude depending upon its geometries, and it also serves as mounting for the total welding stack. The horn or mechanical amplifier again increases these values up to that level, where it will be sufficient for welding. Another role of the horn is to act as a tool during the welding process. As there is a direct contact between tool and workpiece during the welding, the wear and tear will happen to the horn. Thus, some sonotrodes are designed with replaceable tips. But, most of the sonotrodes are acted as a single unit in order to reduce energy loss. Moreover, the materials for the horn and booster should be chosen in such a way that these parts can withstand high wear rate, corrosion, and fatigue loads. Thus, titanium and tool steels are commonly used as booster and horn materials. In this type of welding system, the horn is placed parallel to the workpiece. Meanwhile, an anvil is used to support the fixture and to hold the bottom specimen firmly. Consequently, a sufficient relative motion between the sheets is observed without any slippage. Therefore, the ultrasonic energy transferred to the weld coupon in a transverse manner. The specimens, usually of thin metal sheets, are overlapped on each other with bottom specimen firmly attached to the anvil surface.

3.3.2 Wedge-reed spot welding system Like the lateral drive system, the wedge-reed system also consists of five components, such as a generator, transducer, wedge, reed, and anvil, as shown in Fig. 3.3 [10]. In this system, the wedge has the same function as

Figure 3.2 Various components of lateral drive ultrasonic metal welding system [10].

Weldability appraisement of dissimilar metal joints

47

Figure 3.3 Schematic diagram of wedge-reed ultrasonic metal welding system [10].

a booster. The ultrasonic energy is transferred from the transducer to the reed through the wedge. The reed vibrates in a bending mode and produces transverse vibrations at the welding tip [12]. Generally, the wedge is attached to the reed by means of welding or brazing to avoid any type of loss during the transfer of vibration energy. However, in some situations, the anvil is also vibrating and resonating out of phase to increase the relative motion between the surfaces [12]. Thus, this system is capable of producing high-quality joints between high strength alloy sheets. Meanwhile, the transducer does not receive any direct resistance from the weld spot rather than it only drives the reed. Thus, the parameters at the weld spot cannot be controlled accurately.

3.4 General process parameters Mechanical properties and microstructural analysis of the ultrasonic spot-welded joint are generally defined by the selection and control of standard process parameters. These parameters are vibration amplitude, clamping force, ultrasonic frequency, weld energy, and weld time. Some other special parameters can also be taken into consideration like surface roughness of faying surfaces, specimen dimensions, sample cleanliness from oxides and contaminants, hardness, and geometrical form of tool fixtures. Meantime, the vibration amplitude of the sonotrode or horn tip is an important parameter affecting the weld quality by transmitting a suitable amount of mechanical energy to the weld region. The controller

48

Mantra Prasad Satpathy et al.

can control the value of amplitude by increasing or decreasing it through the modification of the current passing over the transducer. For example, the system can be set to any specific value of amplitude, which results in the supply of the correct amount of power. Generally, the range of vibration amplitude is between 10 and 100 µm. Clamping force is another key system parameter of USW. It is applied between the sonotrode tip and the fixed anvil. This clamping force magnitude is greatly dependent on the material properties and thicknesses of the welding specimen to be joined. This force may vary from tens of Newton to thousands of Newton. When applying the force value, care must be taken because insufficient force can lead to slip off the sonotrode tip, and excessive force can cause hindrance of relative motion between the sheets and excessive deformation of the specimen. Likewise, ultrasonic frequency is typically generated by the transducer, and its range lies between 20 and 40 kHz. The controller is the device that can also control the frequency of oscillation, which remains constant throughout the welding process. However, any changes in the welding system, such as a big difference in clamping force values, system heating, and wear effects, may lead to a shift in the frequency of tools. These differences can also noticeably affect the vibration amplitude of the exciting tool. Furthermore, the welding time is generally determined from levels of both welding energy and power. It can be represented as a dependent or independent variable according to the system used. Mostly, the ultrasonic welding process is completed around 0.2 1.0 s. In Fig. 3.4A and B, the relationship between weld energy, time, and power is shown. It can be seen that weld energy, time,

Figure 3.4 (A) Dependency of weld power with weld time, and (B) weld energy under weld power curve [13].

Weldability appraisement of dissimilar metal joints

49

and power are not independent. The power time curve can present several forms that are dependent on material types, surface conditions, material dimensions, welding parameters, tooling dimensions, and a particular characteristic of a fixed welding machine.

3.5 Mechanical analysis of joints 3.5.1 Tensile and T-peel strength results Tensile shear and T-peel tests are employed to analyze the mechanical strength of the USW joints. Fig. 3.5A demonstrates the relationship of lap shear tensile strength with various welding times of the anodized and nonanodized AA1050/Cu samples. It is clearly ascertained that the samples are not appropriately welded when the welding time is less than 0.35 s. The lap shear tensile strength increases gradually, with the welding time increased. Fig. 3.5B presents a traditional lap shear tensile tested sample that has crack surfaces with two types of fracture modes. The fracture modes change from interfacial debonding to base material fracture when the welding time increases up to a particular level during the USW process. For base material fractured samples, the lap shear tensile strength increases up to a certain limit after that it decreases further with increasing welding time. This is due to the vigorous softening of aluminum alloy,

Figure 3.5 (A) Comparison of tensile shear strength of AA1050/Cu welded samples at various weld times, (B) fractured samples during lap shear strength tests [14].

50

Mantra Prasad Satpathy et al.

and more amount of plastic deformation occurred in the weld zone at the elevated temperature. At various welding times, lap shear strength of the nonanodized aluminum-based samples is higher than anodized aluminumbased samples. This is due to the presence of residual anodic aluminum oxide layer on the weld zone, which directly affects the mechanical strength of Al/Cu samples. In Fig. 3.6, the relationship between tensile shear and T-peel failure loads with the various weld time is described for different surface conditions. As the surface conditions influence the weld quality and strength of the joint thus, four different surface conditions are considered. Firstly, for the lubricating surface condition, the ethanol is utilized to the faying surface. Initially, these two failure loads remain relatively constant up to certain weld time, followed by a rapid increment of these failure loads. Thus, it can be comprehended that the adhesive wear takes place because of the evaporation of ethanol at the high welding time and vibration amplitude. It creates an appropriate atmosphere for the plastic deformation of the Al sheet. Now, after reaching the maximum limit of control factors, the failure loads decrease suddenly because of extreme weld time, and cracks are spotted at the edge of the weld region. Secondly, for the normal faying surface condition, both failure loads show maximum shear strength up to a certain limit. After that, it decreases gradually with the welding time due to the crack formation occurs in the weld area. Similarly, in the case of electrolytic polished and emery polished surface conditions, initially, there is a high-pitched increase in these failure loads. However, the values of these failure loads are less than that of the normal state but more than the lubricating surfaces. The fact for this phenomenon is that at the starting stage of welding, the electrolytic and emery polished surface roughness value is higher compared with the rest of the surfaces, and it leads to high-temperature generation with excessive material softening.

3.5.2 Microhardness The plastic deformation that occurred in the aluminum sheets during the USW process is also investigated by the microhardness analysis. Fig. 3.7 reveals the microhardness variation of the weld region at different welding conditions. The minus side indicates the distance of the hardness distribution of Al from the weld region, and the plus side indicates the distance of hardness distribution of the Cu side. The increasing tendency of the hardness in the area of the weld in both atmospheric and underwater

Figure 3.6 Tensile shear and T-peel failure loads of Al (AA1100) Cu (UNS C10100) weld samples for different surface conditions: (A) tensile shear failure load and (B) T-peel failure load [15].

52

Mantra Prasad Satpathy et al.

Figure 3.7 Microhardness variations at different welding conditions [16].

welding conditions indicate that the finer crystals, and strain hardening in the weld region. In the case of atmospheric welding, the welded region temperature is increasing gradually due to the recrystallization of material by the annealing effect, and thus, the hardness is lowered. However, in the case of underwater welding, a comparative high microhardness value is obtained due to the suppressing of heat at the welded area.

3.5.3 Fracture surface morphology The specific reason for the tensile shear and T-peel failure load variations can be perceived from the fracture surface analysis (Fig. 3.8). An evolution of failure modes can be clearly detected with the increase in welding energy. At lower welding energy, the interfacial detachment at the

Figure 3.8 Fracture surfaces of ultrasonically welded Al (AA 6061) pure Cu joint obtained with various welding energies [5].

Weldability appraisement of dissimilar metal joints

53

welded area is clearly visible with microwelds on both Al and Cu sides (Fig. 3.8A). When the welding energy increases, the size and number of microwelds are also increased. The weld pull-out failure arises when the bonded region at the weld interface is too large to be separated, as shown in Fig. 3.8B. Further increase in the weld energy, the sample thickness is significantly decreased because of the deeper penetration of the sonotrode tip with intensified ultrasonic energy (Fig. 3.8C). As a result, the cracks happen in the aluminum sheet at the boundary of the weld spot.

3.6 Microstructural analysis of joints 3.6.1 Optical microscopy of weld cross-section The optical microscopy on the weld cross-section exposes the quality of weld produced during the USW process. It is evident from Fig. 3.9A and B that at low welding energy, the bond line remains less affected by the ultrasonic energy, and it is macroscopically flat. When the welding energy increases steadily, a small variation can be detected in the macroscopic examination, as shown in Fig. 3.9C and D. The rate of waviness of the bond line directly relates to the amount of ultrasonic energy passed to the weld zone. Furthermore, it is also noticed from Fig. 3.9 that the penetration of sonotrode and anvil knurls are increasingly growing with the rise in welding energy. It is due to the softening of the materials at intensified energy. The high magnification image of the weld cross-section is displayed in Fig. 3.10 to revel the plastic deformation at the weld zone. The weld interfaces at the aluminum side are composed of a wavy- or swirllike pattern. When the welding energy is increased, the penetration of the deformation zone is also increased significantly. A wavy bond line formation mainly enhances the joint strength between the materials. However, when the weld energy is surpassed a certain value, the bond line becomes too wavy in the aluminum side. As a result, lots of voids are present in the welded area. The presence of these voids may act as fracture initiation sites during lap shear tensile testing and decrease the joint strength and ductility.

Figure 3.9 Optical microscopy of weld cross-section of AA 6061/Cu weld samples at various welding energies [5].

Figure 3.10 High magnification optical microscopy images of Al tabs interfaces [17].

56

Mantra Prasad Satpathy et al.

3.6.2 Scanning electron microscopy of fracture surface The SEM analysis of fracture surface conditions is shown in Fig. 3.11. As Al is comparatively softer material than Cu thus, more plastic deformation occurs at Al side, and it can be seen in Fig. 3.11A and C. From these figures, sonotrode and anvil print on the weld samples are clearly visible. It is expected that the intermetallic bond formation happens between the two sheets, and it affects the joint strength significantly. Fig. 3.11B and D are the magnified images of the black circled area. In this figure, the vertically fractured patterns are located inside the weld region. Due to the occurrence of heavy plastic deformation around the weld region, a crack is also formed on the Al side. The effect of hardness of Cu can be clearly observed from Fig. 3.11D. Some of the zones of Cu fractured surface are subjected to wear only, and there is no bond formation happened in these zones. The microbonds are represented as fine dimple-like structures. Fig. 3.12 represents the SEM micrographs of the weld cross-section at different weld times. There are two types of welding region noticed during this SEM analysis. In both figures, the oxide layers are cracked into the Al matrix. These oxide layers and Cu elements may be transfused into the Al matrix through the mechanical intermixing, and it is induced in the softened Al matrix by raising the temperature of interface due to plastic deformation during the USW process. The average diffusion thickness of the Al oxide layer increases with increasing welding time. Therefore, most Al oxide layers were removed from the weld interfaces in the specimen as shown in Fig. 3.12B. Meanwhile, some voids and noticeable cracks are repeatedly observed even in the early welding stages. Whenever the interface temperature of dissimilar joints exceeds the recrystallization temperature, then the hard and brittle IMCs at the weld interface is formed. The type of IMCs is dependent on the temperature, and it can be inferred from the binary phase diagrams of the metals. Fig. 3.13 displays the Al/Cu phase diagram.

3.6.3 Energy-dispersive X-ray spectroscopy analysis The diffusion of elements and its thickness are further analyzed by the back-scattered SEM images along with energy-dispersive X-ray spectroscopy (EDS) chemical analysis (Fig. 3.14). Fig. 3.14A illustrates the joint made at lower weld energy. The thickness of this diffusion zone is around 4 7 µm. Meanwhile, the IMC layer can hardly be seen at the weld interface when welding energy is minimum. This result confirms that no

Figure 3.11 SEM images of fractured surfaces of USW Al and Cu samples (A); Al side (B); magnified image of A (C) Cu side; and (D) magnified image of C [15].

Figure 3.12 SEM images of weld interfaces at different weld time (A) 0.2 s and (B) 0.4 s [14].

Weldability appraisement of dissimilar metal joints

59

Figure 3.13 Al Cu binary phase diagram [18].

continuous IMC layer is formed in the welded region. However, this thickness increases with the rise in weld energy, and it can be perceived from Fig. 3.14B and C. Once again, Fig. 3.14C proves that at maximum weld energy, many cracks are formed at the periphery of the weld zone. Numerous IMCs can form in the Al/Cu joint, such as Al Cu, Al2Cu, and Al4Cu9. This type of IMC layer is creating detrimental effects to the joining strength. Furthermore, the chemical composition on the Al fractured surface is clearly confirmed by the EDS volume scan analysis (Fig. 3.15). The contrast of these images is based on sample surface topology as well as atomic weight. In case of heavier metal, more electrons are reflected with lighter color and stereo surface topology features. The blackscattered SEM images contrast are more sensitive to the atomic weight, and it shows a better black/white contrast. Thus, the volume scan on the black abraded region reveals the Al element and very few amounts of Ni element (as the welding is performed between Al and Ni coated Cu). On the other hand, the white look-like region displays the Ni element only.

3.6.4 X-ray diffraction analysis The X-ray diffraction (XRD) analysis is performed to recognize the phase of IMCs formed during the joining process. Fig. 3.16 shows the traditional fracture surface and XRD forms of the AA 1060/Cu joints. It is confirmed from the XRD analysis that the Al2Cu brittle IMC layer can

60

Mantra Prasad Satpathy et al.

Figure 3.14 SEM and EDS images of weld interfaces at different weld energies [5].

cause low joint strength along with fracture at the welded surface. The joint strength is found to be decreasing with the further increase in the welding time due to the generation of more Al2Cu brittle IMCs.

3.6.5 Electron backscatter diffraction analysis Fig. 3.17 presents typical electron backscatter diffraction (EBSD) analysis results on the weld samples at various weld times. The black lines represent the grain boundaries of both Al and Cu, and the grain orientation

Figure 3.15 SEM images of Al side (A) secondary electron image; (B) back-scattered electron image; (C) and (D) EDS chemical analysis at location A and B [17].

Figure 3.16 (A) Weld cross-section with fracture line. (B) XRD analysis on weld cross-section [19].

Figure 3.17 EBSD images around the weld interface of AA 1050/Cu samples with inverse pole figures at different welding times [14].

64

Mantra Prasad Satpathy et al.

directions can be inferred from the color scale legend in the inverse pole to rolling direction of weld sheets. The white color arrowheads indicate the location of the weld interface. In all three cases, no significant amount of change is noticed on the Cu side due to comparatively higher hardness than Al. The significant perceptible changes are detected on the Al side. Around the weld region, the Al side microstructure changes significantly with the increase in weld time due to the incidence of severe plastic deformations during the USW process. The thickness of the deformed weld region varies with the location due to the presence of knurled type textures on the sonotrode tip. On the other hand, the volume of plastic deformation in the valley region is placed under knurled patterns, and it can be smaller than that in the region located outside of the knurled tip. Indeed, the microstructure in the vicinity of the joint region changes significantly as welding time increased.

3.6.6 Transmission electron microscopy analysis Transmission electron microscopy (TEM) analysis is utilized to comprehend the complete microstructures in the weld region. Fig. 3.18A and B exhibits a bright field and annular dark field at the weld interface between Al (AA1050) and Cu weld samples. The grain size of aluminum material at the joint region is approximately 100 200 nm (Fig. 3.18A). Additionally, various sizes of Al material grains are observed in the welded area. These grains are generated during the bond formation in the weld region. Some area of the weld interface is also found as reactive layer (Fig. 3.18B). The thickness of these grains is about 40 100 nm. In this figure, Al2Cu IMC is detected by the chemical analysis using the TEM EDS process. This thin IMC layer significantly contributes to the enhancement of weld strength in the USW of Al/Cu specimens. However, the increase in the thickness of the IMC layer has an adverse effect on joint strength and quality.

3.7 Conclusions The present work is successfully summarized with the exhaustive study on each attribute of USW of Al/Cu sheets. This study incorporates the evaluation of impelling input factors on the response like weld

Figure 3.18 (A) Bright-field; (B) annular dark-field TEM images at the weld interface of Al (AA 1050) and Cu joints [20].

66

Mantra Prasad Satpathy et al.

strength and the interface microstructure of the welded joint. The following conclusions could be extorted from the current investigation: 1. The tensile shear and T-peel failure loads are raised with the increase in welding time or energy up to a specific limit. After that, these failure loads decrease with an increase in weld time or energy. In another case, these failure loads decrease as the surface roughness of the material increases. 2. The hardness value for the welded samples at low weld time is found to be better with respect to the other received samples. This is occurred because of the considerable amount of cold work at the weld surface. For this short weld time, hardness value in the weld surface is maximum compared with the valley region. 3. In fracture surface analysis, the increase in welding energy raises the size and number of the microwelds along the weld cross-section. The weld pull-out failure arises when the bonded region at the weld interface is too large to be separated. Further increase in weld energy results in a significant decrease in sample thickness because of the deeper penetration of sonotrode tip. 4. At shorter weld time, a complex type of weld pattern is observed below the sonotrode tip edges. In this case, the weld interfaces are quite straight. As the welding time increases, the plastic deformation area also expands, and the bond-line is changed from a typical straight line to a convoluted wavy pattern. 5. Different SEM analysis reveals several levels of weld quality. The weld strength is decreased, and the failure mode reverts back when the welds are produced with higher weld region temperature. Weld defects such as cracks and IMCs are found at the weld interface. 6. The EDS analysis reveals the diffusion process at the weld interface, and the width of this diffusion layer increases with the welding time. At the highest weld time, there is an excessive reduction of the yield strength of the materials, and it is leading to the cracks at the periphery of the welding zone. 7. EDS line scan and XRD confirm the IMC formation during USW of Al/Cu weld samples. The AlCu, Al2Cu, and Al4Cu9 compounds are formed because of the diffusivity property of Al are higher than Cu at the developed welding temperature. 8. EBSD analysis demonstrates the grain orientation and the recrystallization by the elevated temperature and high strain rate at the weld

Weldability appraisement of dissimilar metal joints

67

interface. This is essential to achieve the superior quality of welds in the USW process. 9. TEM analysis suggests that the thin Al2Cu IMC layer up to 40 100 nm is beneficial in enhancing the joint strength during USW of Al to Cu alloys. However, the wide IMC thickness is having an adverse effect on weld strength.

References [1] Das A, Li D, Williams D, Greenwood D. Joining technologies for automotive battery systems manufacturing. World Electr Veh J 2018;9:22. [2] Nesbeit M, Fergusson M, Colsa A, Ohlendorf J, Hayes C, Paquel K, et al. Comparative study on the differences between the EU and US legislation on emissions in the automotive sector: study. Luxembourg: EU Publications; 2016. [3] Kirkpatrick L. Aluminum electrical conductor handbook. Arlington, VA: The Aluminum Association; 1989. [4] Fuhrmann T, Schlegel S, Grossmann S, Hoidis M. Comparison between nickel and silver as coating materials of conductors made of copper or aluminum used in electric power engineering. In: ICEC 2014; 27th International Conference on Electrical Contacts; 2014. p. 1 6. [5] Zhao YY, Li D, Zhang YS. Effect of welding energy on interface zone of Al Cu ultrasonic welded joint. Sci Technol Weld Join 2013;18:354 60. Available from: https://doi.org/10.1179/1362171813Y.0000000114. [6] Chen YC, Nakata K. Effect of the surface state of steel on the microstructure and mechanical properties of dissimilar metal lap joints of aluminum and steel by friction stir welding. Metall Mater Trans A 2008;39:1985 92. [7] Liyanage T, Kilbourne J, Gerlich AP, North TH. Joint formation in dissimilar Al alloy/steel and Mg alloy/steel friction stir spot welds. Sci Technol Weld Join 2009;14:500 8. [8] Su P, Gerlich A, North TH, Bendzsak GJ. Energy utilisation and generation during friction stir spot welding. Sci Technol Weld Join 2006;11:163 9. [9] Bloss MC. Ultrasonic metal welding: the weldability of stainless steel, titanium, and nickel-based superalloys. Columbus, OH: The Ohio State University; 2008. [10] Graff K. Introduction to high power ultrasonics. Columbus, OH: Edison Welding Institute; 1999. [11] Graff KF, Short M, Norfolk M. Very high power ultrasonic additive manufacturing (VHP UAM) for advanced materials. In: Solid Freeform Fabrication Symposium, Austin, TX; 2010. [12] Ahmed N. New developments in advanced welding. 1st ed England: CRC Press; 2005. [13] Gallego-Juárez JA, Graff KF. Power ultrasonics: applications of high-intensity ultrasound. Cambridge: Elsevier; 2014. [14] Fujii HT, Endo H, Sato YS, Kokawa H. Interfacial microstructure evolution and weld formation during ultrasonic welding of Al alloy to Cu. Mater Charact 2018;139:233 40. [15] Satpathy MP, Sahoo SK. Microstructural and mechanical performance of ultrasonic spot welded Al-Cu joints for various surface conditions. J Manuf Process 2016;22:108 14. Available from: https://doi.org/10.1016/j.jmapro.2016.03.002. [16] Matsuoka S, Imai H. Direct welding of different metals used ultrasonic vibration. J Mater Process Technol 2009;209:954 60.

68

Mantra Prasad Satpathy et al.

[17] Wu X, Liu T, Cai W. Microstructure, welding mechanism, and failure of Al/Cu ultrasonic welds. J Manuf Process 2015;20:321 31. [18] Massalski TB, Okamoto H, Subramanian PR, Kacprzak L. Binary alloy phase diagrams. 2nd ed Materials Park, OH: ASM International; 1990. p. 2882. [19] Liu G, Hu X, Fu Y, Li Y. Microstructure and mechanical properties of ultrasonic welded joint of 1060 aluminum alloy and T2 pure copper. Metals (Basel), 7. 2017. p. 361. [20] Fujii HT, Goto Y, Sato YS, Kokawa H. Microstructural evolution in dissimilar joint of Al alloy and Cu during ultrasonic welding. Mater Sci Forum 2014;783:2747 52.

CHAPTER FOUR

Applications of coconut shell ash/particles in modern manufacturing: a case study of friction stir processing Omolayo M. Ikumapayi1, Esther T. Akinlabi1, Jyotsna D. Majumdar2 and Stephen A. Akinlabi3 1

Department of Mechanical Engineering Science, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg, South Africa 2 Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur, India 3 Department of Mechanical Engineering, Faculty of Engineering and Technology, Butterworth Campus, Walter Sisulu University, South Africa

4.1 Introduction Coconut shell (CS) is an agricultural solid-waste material that has been causing environmental unfriendliness to people living around the production site. The poor management, utilization, and proper disposal of agricultural wastes caused environmental menace which affects the health status of the dwellers. Notwithstanding, a lot of benefits had been exploited by several researchers varying from particulate for structural or construction additives, powder reinforcement in polymer and metal matrix composites, water purification, and energy generation. Coconut shell ash (CSA) has been reported to have produced the highest activated carbon among the agrowaste materials [1]. Coconut plant has lots of useful waste materials such as fronds, husk as well as shell. In this study, the applications of the strongest part of the coconut, which is CS in science and technology are extensively exploited. The CS is located between the coconut flesh and coconut husk, and this is typically used to protect and enclose the inner part of coconut. The applications of CS have proven in the following areas, namely reinforcement and coarse aggregate, activation carbon, filler, and energy source due to its high toughness, excellent adsorption capability, durability properties, efficient abstractive resistance, and most suitable for Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00004-X

© 2020 Elsevier Ltd. All rights reserved.

69

70

Omolayo M. Ikumapayi et al.

long standing. The effective and efficient utilization can be in form of macroparticles, microparticles, as well as nanoparticles [1]. CS is a lignocellulosic agricultural waste material in which its plant is cultivated in over 90 countries globally [2]; and it was reported to be predominant in the following countries, namely Indonesia, Brazil, Malaysia, Thailand, India, Philippines, Nigeria as well as Sri Lanka. The statistical analysis of global production of coconut in year 2012 is depicted in Fig. 4.1. In this record, Indonesia reported to have produced the highest percentage of CS with tons of 18,000,000 which amounts to 36.5% global market production, the Philippines produced 15,862,386 tons as at 2012 which amounts to 32.17% global production, India produced 10,560,000 tons which gives 21.42% global production of CS while Brazil produced 2,883,532 tons with 5.86% global percentage, and Sri Lanka production of CS as at year 2012 was 2,000,000 tons with a global percentage of 4.06% [3].

4.1.1 Application of coconut shell as concrete reinforcement, aggregate, and as filler It was established that CS as solid wastes contributed to 60% of domestic wastes and its disposal has been problematic and this led to the use of CS as composite materials in the production of concrete after extensive research on its suitability [2]. The most sustainable area of application of CS has been in coarse aggregate for concrete production as additives, filler, and reinforcement. It has been proven that cement natural binder is very expensive to produce sandcrete blocks, concrete, mortar as well as lancrete bricks and this has led to searching for a promising alternative replacement binder. The fundamental raw materials used for the

Figure 4.1 Global percentage of coconut in year 2012 [3].

Applications of coconut shell ash/particles in modern manufacturing

71

production of concrete are (1) water, (2) cement, (3) coarse aggregate (gravel or granite chippings), and (4) sand (fine aggregate); the summation cost for the production of concrete depends entirely on the availability of the aforementioned materials [4]. On this note, researchers and engineers are greatly concerned with the growing rate at which resources are depleting and this has propelled them to seek and develop a promising replacement which is entirely new materials from biomaterials as binders. It is well noted that utilization of concrete material in building and construction industries are growing geometrically due to high demand of concrete. To meet this demand with low cost and still maintain its properties, has endeared the researchers for using agricultural waste materials that will still serve the intended purposes and retains its integrities. Many researchers have worked on this area and there are some attributes that CS possess that makes it excellently suitable for reinforcing concrete. The attributes are [3]: 1. CS are biodegradable and eco-friendly 2. High modulus and promising strength characteristics 3. It contains excellent lignin contents which makes the fabricate composites to be resistant to weather conditions 4. The surface texture when CS was used for the formation of concrete becomes nearly smooth on concave face and becomes nearly rough on convex face 5. CS can be used in any form on concrete either in macro or micro; (6) the sugar content in CS has no effect on the strength and formation of concrete 6. It contains lower cellulose content, and this made it absorb lesser moisture when compared with other agrowastes 7. They are renewable resources 8. Absence of health hazards 9. Low density Leman et al. [2] investigated the physical and chemical attributes of CS powder to be considered as filler in concrete production. These properties were established via scanning electron microscopic (SEM), of X-ray fluorescence (XRF), specific gravity, particle size distribution as well as density determination. It was revealed from the XRF result that CS largely potassium oxide (K2O) with 1.21%, carbon with 10.00%, and silicon dioxide (SiO2) with 0.98% which played important roles in mixing of the concrete. Others chemical composition revealed are chlorine (Cl) with 0.79%, iron (III) oxide (Fe2O3) with 0.35%, magnesium oxide (MgO)

72

Omolayo M. Ikumapayi et al.

with 0.31%, sodium oxide (Na2O) with 0.29%, calcium oxide with 0.23%, and molybdenum (VI) oxide (MoO3) with 0.17%. Kanojia and Jain [3] studied the efficacy of CS as coarse aggregate in concrete. The study aimed at providing an alternative aggregate for concrete over conventional coarse aggregates. Both density and compressive strength were tested and it was found that there was 62% reduction in compressive strength was achieved with 40% replacement of conventional coarse aggregates within a test time of 7 days whereas 21.5% reduction in compressive strength was achieved for the same 40% replacement for 28 days. It was concluded that the cost of additional cement was inevitable, but the overall performance was great with the use of alternative aggregates as against the natural one. CS has proven to be effective and efficient as partial replacement as coarse aggregates for the depletion of natural source. The study carried out will help researchers to arrive ultimate decision regarding the amount of CS to be applied as additive for nature coarse aggregates during the mixing and production of concretes [3]. The study into the durability characteristics of CS on aggregate concrete was investigated by Nadir and Sujatha [5]. In this study, admixture of CS particulates, ground granulated furnace slag with fly ash was used as reinforcements at different mixing ratios. The following tests were conducted to establish the durability of the produced concretes, sorptivity, water absorption, rapid chloride penetration, volume of pore voids as well as bulk diffusion. The research revealed that by the addition of admixtures on the coarse aggregates, the durability properties of the produced concrete is said to be improved [5]. Effect of milling time was investigated on the CS using top-down approach to produce uncarbonized CS nanoparticles. Mechanical milling of CS was done for 70 h by the application of ceramic balls of varying sizes. SEM coupled with energy-dispersive X-ray spectroscopy (EDS) as well as transmission electron microscope (TEM) were employed for morphological examination. Nanoparticle derived from the milling of CS powder of 37 μm, was estimated to be 18.23 nm [6].

4.2 Application of coconut shell ash as activated carbon or as charcoal One of the commercial products of CS that possessed desirable and esteemed characteristics because of its worth is coconut charcoal. Coconut

Applications of coconut shell ash/particles in modern manufacturing

73

charcoal as a valuable commercial product is used to produce active carbon and some other global market products which shall be discussed. CS has been confirmed to have produced the highest activated carbon among the agrowaste materials globally. Some of the uses of coconut charcoal are listed below: 1. Coconut shell charcoal (CSC) is used as fuel in most of the food industries as a promising replacement to normal coal because of its high heating content and nice fragrance produced during burning. Most of the food industries are now using coconut charcoal for the preparation of barbecues and other cultural aliments. 2. CSC possessed is an excellent and promising purifier and moisturizer, and these attributes made it suitable to produce soaps. Coconut charcoal soaps was revealed to be sensitive and suitable for most skins and they are available in most of the groceries and some of the supermarket close to us. 3. Coconut charcoal has been confirmed for its efficacy as a natural teeth whitener. It has been experimented for the cleaning of yellowish and dark teeth with an amazing result which gave instant white teeth. 4. In recent times, researchers confirmed that coconut charcoal has been used as feed for animals especially pigs, cattle as well as poultry. It was revealed that, milk production rates has increased tremendously as a result of feeding the cattle with coconut charcoal and the expectant life of pigs has increased with reduction in diseases that affected them and the pigs have gained weights at the same time. 5. It was revealed that excellent quality of grasses is produced when CSC is used alongside with sand and other biomass materials to plant grasses. Golf courses developers are now using this new and amazing technology to their advantage to get quality playfield. Salleh et al. [7] studied the potency of activated carbon derived from CS in reinforcing polymer matrix composites and this was later encapsulated with epoxy resin. Different percentage by volume of CS activated carbon were used ranging from 2 to 6 wt.% while the percentage by volume of polymer (polypropylene, PP) that was used ranging from 4 to 8 wt.% in step of 2 wt.% in each case. The polymer matrix composite was prepared by silicon rubber molds having the following shapes, namely rectangular as well as dumbbell in accordance with the standard of ASTM D256 and ASTM D2099, respectively. It was noted that tensile strength of the fabricated polymer matrix composite increases with the increase in CS activated carbon from 4 to 8 wt.% and the tensile strength was

74

Omolayo M. Ikumapayi et al.

achieved at PP 4 wt.% 1 AC 6 wt.% composite whereas the impact strength of the study was obtained at PP 6 wt.% 1 AC 4 wt.%. CSA and CSC were compared experimentally. In this experiment to reinforce the open mold process was used to cast polyester matrix composites using CSC as the reinforcement and absorption; mechanical as well as abrasion tests were conducted on the fabricated composite. It was noted that flexural and tensile properties are said to have improved with increase in the volume of coconut shell particles from 1 to 5 wt.%. It was also established that the abrasion resistance properties of the fabricated polymer matrix composite reinforced with CSA decreases with increase in the percentage by volume of CSA while the value of CSC was slightly higher than CSA. The same trend was noted in water absorption ability [8].

4.3 Application of coconut shell particle as water purification and heavy metals removal It is evidentially clear that heavy metals and some elements found in the body of water has caused unbearable threats to the environment, people living around the place, and the public health due to the food chain and toxicity. Such heavy metals, ions, or elements include uranium, fluoride, cesium, chlorine, strontium, and lead II ion in which most of the heavy metals or ions may come from the industries producing the following items glass, battery, ceramic, printing, metal painting as well as lead additives for gasoline and these can cause partial or permanent damage to the following organs kidneys, liver, neuronal system, brain as well as reproduction system. Due to some activities in the production of some reactive materials some wastes have been generated and this needs instant treatment. The separation, removal, and concentration of these wastes can be achieved via any of the following means, namely precipitation, adsorption, evaporation, and ion exchange. In this research work coconut shell activated carbon was used for the adsorption of cesium, strontium, and uranium ions from the aqueous medium. The study used Freundlich isotherm as well as Langmuir isotherm fitted models for the analysis [9]. Carbonic materials are becoming more popular and widely used in manufacturing process for filler, reinforcement, purification of water as well as fuel production. Son et al. [10] developed carbon material via coconut shell especially carbon dioxide for the adsorption technique.

Applications of coconut shell ash/particles in modern manufacturing

75

Catalytic centers were developed in this study for doping of metals such as cobalt, nickel, magnesium, copper, and calcium on coconut char by dipping it in aqueous medium. The evaluation of the produced samples was carried out using adsorption capacity, surface area, and morphological study via SEM. It is essential to note that, coconut shell carbon that was produced via potassium hydroxide (KOH) activation was employed to absorb lead (II) from aqueous medium. Agitation time, adsorbent concentration as well as initial concentration were studied with the use of nitrogen adsorption process as well as SEM analysis. It was revealed that porous structure was eminent because of high concentration of KOH. The model used for the validation of the adsorption were Langmuir, Dubinin Radushkevich, Temkin, Halsey, Freundlich, and Harkins Jura isotherms [11]. In the same vein, coconut shell activated carbon was used for water treatment as a means of defluoridation. This was used to absorb excess fluorine in the body of water. The WHO has setup a standard for fluoride content for the drinking water between 1.5 and 4.0 mg-F/L. It must be aware that fluoride can be consumed from various means either through vegetables consumption with fluoride contents between 0.1 and 0.4 mg/ kg or food stuffs varying from 2 to 5 mg/kg in barley, rice consumption with 2 mg/kg while canned fish can contain as much as 370 mg-F/kg. It must further be noted that dry tea leaves contained about 400 mg/kg. It was revealed that fluoride contaminated water has been major source of human exposure to chloride and this accounts for about 90% intake of fluoride ion on a daily basis. The evaluation of batch experiment was conducted to determine the degree of removal of fluoride ions in the body of water. It was established that coconut shell activated carbon was suitable for the treatment of fluoride ions in water. It was further established that particle sizes contributed to the adsorption rate of the fluoride ions. The smaller the particle size the better was the absorption rate. The absorption rate was validated using Langmuir and Freundlich isotherm models. This study suggested that coconut shell activated carbon is suitable for filter of portable water at home so that it can be free of fluoride ions [12]. Coconut shell activated carbon was used to remove 2,4-dichlorophenol (2,4-DCP). The coconut shell was carbonized in about 500 C for 2 h and was activated chemically using zinc chloride (ZnCl2). The removal of chlorinated phenols from the body of aqueous medium was achieved

76

Omolayo M. Ikumapayi et al.

through the following models—Freundlich, Langmuir, as well as Temkin isotherm. It was revealed that the best model that fitted the absorption of was 2,4-DCP was Freundlich isotherm [13].

4.4 Application of coconut shell in metal, polymer, and ceramic matrix composites Aluminum matrix composite (AMC) was fabricated via compocasting technique by reinforcing it with CSA with varying percentage by volumes of CSA from 5%, 10% to 15% and in this study, efficacy of wear properties were conducted using pin-on-disc experimental set-up, 2000 m was employed as sliding distance during tribological experiment, 10 N of applied load, and the sliding velocity that was used rated 2 m/s. The following statistical methods were also adopted grey relational grade (GRG), fuzzy interface system (FIS), as well as Tagushi desirability functional analysis (DFA). It was observed that addition of CSA increases the tensile strength and hardness properties of the fabricated composite and this also decreases the elongation and the density of the fabricated composite. Analysis of variance (ANOVA) was used to predict the optimum parameters. It was noted that grey-fuzzy reasoning grade (GFRG) produced the least error of approximately 0.015 than other statistical methods [14]. Aluminum alloy was reinforced with coconut shell particles via double stir-casting technique with varying percentage by volume from 3 to 15 wt.%. The mechanical and metallographic properties were evaluated; and density, microstructure as well as hardness properties were carried out. SEM-energy-dispersive X-ray (EDX) and XRF analyses were used in this study. Results revealed that increase in the percentage by volume of coconut shell particles decreases the density of the cast aluminum metal matrix composite but the hardness of the reinforced and cast aluminum metal matrix composites was said to have increased. The analysis in this study revealed through XRF that CSA contains 15.6% Al2O3, 0.57% CaO, 16.2% MgO, 12.4% Fe2O3, 0.22% MnO, 0.52% K2O, 0.3% ZnO, 45.05% SiO2, and 0.45% Na2O [15]. Hybridization of aluminum with CSA admixture with graphite was investigated during stir-casting experiment. Tribological integrity of the cast samples were evaluated using different parametric measures. It was revealed that mechanical properties such as hardness as well as tensile

Applications of coconut shell ash/particles in modern manufacturing

77

strength were improved when coconut shell was added alone whereas when graphite was added the following were improved—tribological behavior, toughness, and specific strength [16]. The study established the efficient utilization of carbonized coconut shell powder as polymer reinforcement during synthesis of aluminum (1XXX) nanoparticle using ball-milling which serves as solid interface and lubricant. In this study, Fourier-transform infrared spectroscopy (FTIR), TEM, X-ray diffraction (XRD), and SEM were employed in the analysis. It was noted that aluminum nanoparticle was greatly reduced with increase in the milling time [17]. In this study, coconut shell powder was used as a filler in natural rubber composites production. The potency of the produced nature rubber composites was tested using different techniques varying from tear and tensile strength analysis, swelling evaluation was conducted to reveal crosslink density as well as hardness of the vulcanizates was measured. The fractography of the tensile samples was taken by SEM. It was revealed that reinforcing the natural rubber with coconut shell powder greatly enhanced the hardness, tensile strength, and thermal properties. The study further revealed that, coconut shell powder contains 29.4% lignin, 27.7% pentosans, 26.6% cellulose, 8% moisture, 0.6% ash, 4.2% solvent extractives, and 3.5% uronic anhydrides [18]. Mechanical properties and morphological characteristics of reinforced polymer (polyethylene) matrix composites with low density coconut shell powder with an average particle size of 100 μm, was investigated. The percentage by volume of coconut shell particulates were varied between 0% and 25% with a step of 5% and its effect was studied on the fabricated polymer matrix composites. It was established that only hardness of the reinforced composite increased with an increase in coconut shell particles while impact and tensile strengths, ductility as well as modulus of elasticity were all reduced with increase in the percentage of coconut shell powder. This study established the possibility of using agricultural solid waste such as coconut shell powder as a replacement to metallic powder for reinforcing polymer matrix composites [19]. Oliveira and Marques [20] made a vivid chemical treatment comparison in using green coconut husk as well as curaua fiber for compatibility with PP matrix. The two samples were evaluated before and after the chemical treatments to ascertain its influence of morphology and thermal stability. An increase in crystallinity index was observed when using

78

Omolayo M. Ikumapayi et al.

coconut shell fiber from 53% when in untreated natural fiber to 67% when treated with coconut shell fiber. Similar observation was noted in curaua fiber which increase from 61% when in untreated natural fiber to 81% when treated with curaua fiber [20]. Coconut shell powder was used as a filler on different silane coupling agents in blended thermoplastic polyurethane and natural rubber (ISNR-5). The mechanical and metallographic characteristics of the modified interfacial adhesion were studied. The properties investigated were abrasion resistance, tensile strength, hardness as well as tear strength while FTIR and SEM of the modified samples were also carried out. SEM and thermogravimetric analysis revealed that mechanical properties especially thermal stability increased with addition in coconut shell powder [21]. Sarki et al. [22] researched on the potential utilization of coconut shell particulates as fillers in eco-composite materials. In this study, mechanical attributes and morphology of the fabricated epoxy polymer matrix composite was investigated. An excellent interfacial interaction between the reinforcement particles (coconut shell powder) and the substrate (epoxy polymer) was achieved. It was established in this study that addition of coconut shell particle greatly improved tensile strength, hardness, and modulus of elasticity while the impact strength was lower with increase in the filler particle. The complete coconut contains husk of 50%, meat of 25%, shell of 15%, as well as water of 10%. It was established that coconut shell is made up of cellulose of 34%, pentosans of 29%, lignin of 36% as well as ash of 1%. This 15% shell of the whole coconut was later analyzed for chemical compositions and chemical contents. The variability in chemical compositions and chemical contents of coconut shell are, respectively, presented in Tables 4.1 and 4.2. The variability in elemental compositions of coconut shell is presented in Table 4.3 while the ranges of chemical, mechanical, and physical properties of coconut shell as reported by Gunasekaran et al. [25] is presented in Table 4.4. In this present study, carbonized coconut shell ash (CCSA) was used on the high strength armor grade aluminum alloy, Al7075-T651, the reinforcement of CCSA into Al7075 was integrated using friction stir processing (FSP). The fabricated Al7075-T651/CCSA was characterized using tribological, structural as well as mechanical properties. The results are then analyzed and presented.

Table 4.1 Variability in chemical composition of coconut shell particles. Chemical Ikumapayi and Akinlabi Leman Oluwole and Aku [1] and this study et al. [2] Oluwaseun [8] et al. formula [15]

SiO2 Al2O3 CaO MgO Fe2O3 MnO K2O ZnO Na2O MoO3

45.6% 16.76% 0.78% 19.4% 8.98% 0.17% 0.42% 0.39% 0.41%

0.98% 0.23% 0.31% 0.35% 1.21% 0.29% 0.17%

46% 16%

45.05% 15.6% 0.57% 16.2% 12.4% 0.22% 0.52% 0.3% 0.45%

18% 14% 0.5% 1.2% 0.6% 0.9%

Table 4.2 Variability in chemical content of coconut shell particles. Chemical name Sareena et al. Balan et al. Arena et al. [18] [21] [23]

Cellulose Moisture Ash Hemicellulose Uronic anhydrides Lignin Starch Pentosan Protein Fat Solvent extractives Volatile matter

26.6% 8% 0.6%

34%

30.58% 8.86% 0.56% 26.70%

21%

Siva et al. [16]

48.2% 16.68% 0.67% 18.2% 9.42% 0.25% 0.59% 0.32% 0.47%

Endut et al. [24]

6.72 6 0.18 1.03 6 0.09

3.5 5 29.4%

27% 0

33.30%

27.7% 2% 5% 4.2% 64.24 6 1.44

Table 4.3 Variability in elemental composition of coconut shell particles. Element Ikumapayi and Akinlabi [1] and Leman Arena et al. Endut et al. this Study et al. [2] [23] [24]

C H O Ca K Fe Cl Mg Si

66.2% 25.40% 0.6% 3.9% 0.7% 1.5% 0.2% 0.4%

10.00%

0.79%

45.03% 6.94% 47.47%

28.01 6 1.64

80

Omolayo M. Ikumapayi et al.

Table 4.4 Ranges of chemical, mechanical, and physical properties of coconut shell [25]. Mechanical and physical Measured Chemical Measured properties values properties values

Flakiness index Apparent specific gravity Impact value Moisture content Crushing value Shell thickness Water absorption Bulk density (tamped) Specific gravity % of voids Bulk density (loose) Abrasion value Fineness modulus (sieve analysis) % of voids (tamped)

100% 1.40% 1.50% 7.00% 8.50% 4.00% 4.50% 2.00% 3.00% 2 8 mm 20.00% 25.00% 640 650 kg/m3 1.05% 1.25% 45.00 50.00 525 550 kg/m3 1.50% 1.65% 6.00% 6.30%

pH Total phenols Glucose Reducing sugar Ash Fructose Cellulose Sucrose

6.00 6.40 05.15% 01.85% 07.40% 0.50 0.60 02.90 32.00% 14.75%

30.00 40.00

4.5 Materials and methods The section itemized the materials used in this study, means of collection, preparation, and processing. The section further explained the methods of production of CCSA, and method of fabrication of AMC under investigation.

4.5.1 Materials collection and preparation In this experiment matured coconut fruits (see Fig. 4.4A) were obtained at Hilbrow market in Johannesburg axis of South Africa. The coconut fruits were then broken with the help of cutlass into several pieces (uneven chunks) and the edible parts were then extracted while the coconut water inside was drained away. The coconut shells were then separated (see Fig. 4.2B), and the fibers lining were removed from the back of the broken coconut shell and washed thoroughly with water and acetone was used to remove any unwanted materials that can hinder the outcome of the experiment and were further broken into smaller pieces (see Fig. 4.2C). The chunks of the coconut shell were then placed inside

Applications of coconut shell ash/particles in modern manufacturing

81

Figure 4.2 (A) Coconut fruits. (B) Coconut shell. (C) Smaller piece of coconut shell. (D) Pulverized CS. (E) Carbonized CSA.

an oven pre-set at 50 C for 120 h for total dryness after which it was sundried for 7 days. The dried coconut shells were later crushed into pieces and pulverized into powder (see Fig. 4.2D) using mechanical disc-milling for 60 min and sieved with 75 μm ASTM meshes standard and this coconut shell powder, the pulverized CSA was then characterized using the following SEM incorporated with the EDX for morphological and elemental analysis and their results are depicted in Fig. 4.3, while XRF was used for chemical composition analysis, and XRD was used for structural and crystalline phases present in CSA. The pulverized and milled CSA was later heat treated by carbonization method as seen in Fig. 4.2E by putting the milled CSA inside the pure graphite crucible and heat treated them in a controlled temperature inside the muffle furnace set at 500 C for 2 h after which it was allowed to maintain thermal stability within, until it reached room temperature and this enabled thermal decomposition, homogeneity, as well as phase transformation, by doing so the texture will be improved. The CCSA was then used for reinforcing aluminum alloy using FSP to form AMC.

82

Omolayo M. Ikumapayi et al.

Figure 4.3 (A) SEM image of CSA. (B) Elemental composition of CSA.

4.5.2 Methodology of friction stir processing In this present research, 6 mm thickness of base metal—aluminum alloy, Al7075-T651 rolled plates were purchased for the research with dimensions 300 3 125 3 6 mm3. The following mechanical properties for Al7075-T651 were received via spark spectrometric analysis, 0.32 of Poison’s ratio, 150 HV if Brinell hardness, 570 MPa for ultimate tensile strength, 330 MPa for shear strength, 500 MPa for yield strength, 26 GPa for shear modulus, as well as 160 MPa for fatigue strength. FSP was then carried out on Al7075 using 2 tons NC friction stir machine produced by ETA Bangalore, India Ltd. (see Fig. 4.4A). A groove was made on the plate of Al7075 in order to put the CCSA inside it. This groove was made in a dimension 280 mm length by 3.5 mm depth by 2.0 mm width. Design of the tool was then carried out to process, stir, and mix the reinforcement with the substrate. AISI H13 steel tool was designed in such a way that the shoulder diameter was 18 mm, the pin length was 5 mm, and the pin diameter was 5 mm. In this study, double passes were carried with 100% inter-pass overlap and the processing parameters that were applied are 0.3 mm plunge depth, 1500 revolution per minutes, 20 mm/ min, and the tilt angle was of degree three. The experimental set-up during the FSP is shown in Fig. 4.4B.

Applications of coconut shell ash/particles in modern manufacturing

83

Figure 4.4 (A) NC-controlled FSW machine used. (B) Processing set-up.

4.6 Characterization of the friction stir processed Al7075/CCSA The fabricated Al7075/CCSA, FSPed Al7075 as well as Al7075 (parent metal) was characterized using mechanical testing, surface roughness analysis as well as structural evaluation. The proceeding sections highlight how the tests were carried out.

4.6.1 Structural integrity of Al7075/CCSA PHILIPS X’Pert machine was used to carry out structural analysis using XRD, the machine was operated at PW: 3040/60, 50 Hz, 240 V as well as 8.5 KVA. The test was conducted on the parent material as well as fabricated samples to examine mineralogical contents as well as crystalline structure of the samples. The computed values are dislocation density, microstrain, grain size, etc., and this was achieved using Scherrer techniques. The machine specification used in this study is depicted in Table 4.5.

4.6.2 Mechanical properties: tensile analysis Xforce P-type Zwick/Roell Z250 Tensile tester was used to carry out tensile analysis in accordance with ASTM B557M-10 standard [26]. The sample used for this study was 100 mm in length and 6 mm in thickness. The test was conducted on each sample three times to maintain consistency, reproducibility, and accuracy. The fractured surface from each sample was examined using fractography technique under SEM. The tensile

84

Omolayo M. Ikumapayi et al.

Table 4.5 XRD experimental specification. Property

Specification

Scan range (2θ) Excitation voltage K Current k ~ radiation Excitation voltage Kα radiation Scanning rate

Between 5 and 90 degrees 40 kV 0.94 30 mA λ 5 1.39225 Å 40 kV λ 5 1.5406 Å 1.0/min (2θ/seg)

Figure 4.5 (A) Illustration of tensile sample sectioning from processed zone. (B) Cut tensile sample.

test was carried out at room temperature. The illustration on the sectioning of the samples is represented in Fig. 4.5.

4.6.3 Surface integrity evaluation Surface integrity of the fabricated samples were tested using surface roughness analysis tester (Mitutoyo surf test SJ-210). The test was conducted on FSPed Al7075/CCSA, as well as FSPed Al7075. In order to ascertain the surface finish of the produced samples and textural characteristics is maintained, this test was measured out at three points on a fabricated sample and this was done to ensure surface area coverage while the mean value was taken and recorded. Photograph of the Mitutoyo surf test SJ-210 and the reading on the fabricated sample are represented in Fig. 4.6A and B, respectively.

Applications of coconut shell ash/particles in modern manufacturing

85

Figure 4.6 (A) Surface roughness tester; (B) reading on the frabricated Al7075/CCSA.

4.7 Results and discussion This section explains the results and discusions of the experiments carried out, which are tensile properties result, morphology of the fracture surfaces, surface integrity of the produced composites as well as structural evaluation of the fabricated samples.

4.7.1 Mechanical properties: tensile behavior The performance evaluation of the CCSA on the fabricated friction stir processed high strength aluminum alloy Al7075 by using tensile testing. The parent material Al7075, processed parent material FSPed Al7075 as well as fabricated matrix composite FSPed Al7075/CCSA was tested for tensile strength. The following properties studied the stress at 0.2% offset strain (Rp0.2), the stress at 0.1% offset strain (Rp0.1), the maximum stress value (Rm), the stress at 0.5% offset strain (Rp0.5), and the breaking force (Fm). The fracture surfaces were examined using fractography. The results of the tensile test carried out is presented in Table 4.6 while the graphical representation is depicted in Fig. 4.7. It was revealed in the Table 4.6 that unprocessed parent material Al7075 has higher mechanical properties than the processed and fabricated AMC FSPed Al7075/CCSA sample. Table 4.6 revealed that ultimate tensile strength (Rm) was highest in the parent material Al7075 with a value of 620 MPa while that of fabricated

Table 4.6 Tensile test results of the samples. Composites Rm Rp0.1

Al7075 FSPed Al7075/CCSA FSPed Al7075

Fm

Rp0.2

Rt0.5

At (corr.)

Rp0.5

MPa

MPa

KN

MPa

MPa

%

MPa

620.9030 379.6816 362.9048

559.0751 241.3738 213.24

22.35251 13.66854 13.06457

572.9528 254.1496 228.2679

7.334991 8.963831 7.607991

9.732209 11.80671 14.30768

588.4694 277.5694 251.8613

Applications of coconut shell ash/particles in modern manufacturing

87

Figure 4.7 The stress bar chart representing stress at 0.1%, 0.2%, and 0.5% offset strain.

matrix composite was 379 MPa and the unreinforced but processed parent material was 362 MPa. The breaking force (Fm) for the parent material Al7075 was 22.35 kN while FSPed Al7075/CCSA was 13.66 kN and that of FSPed Al7075 was 13.06 kN. The tensile strength at 0.1% offset strain (Rp0.1) for the parent material Al7075 was 559 MPa, the Rp0.1 for the fabricated AMC FSPed Al7075/CCSA was noted to be 241 MPa while the unreinforced but processed parent material FSPed was recorded as 213 MPa. Fig. 4.7 revealed the comparison of the stresses for all the samples under investigation. The fracture surface of the tensile sample is shown in Fig. 4.8. It was established that the fractography of the AMC are impressed by the size of the reinforcement particles if it is in nano, micro, or macro types; the types of reinforcement whether metallic powder, ceramic, or agrowastes powders, the substrate material whether metallic, ceramic, or polymer material, how large the reinforcement in the matrix composites and also interfacial bonding strength, surface roughness, porosity content, and precipitation effect [27]. Failure in AMC can be attributed to either interfacial decohesion, matrix failure, or reinforcement failure [28]. Fig. 4.8A represents the fractography of the parent material Al7075 which revealed stretched grain and elongated dimples and this dictates ductility in Al7075. Fig. 4.8B represents friction stir processed of the parent material, FSPed Al7075, and this revealed large dimples with bimodal distribution. At the same time Fig. 4.8C also revealed equiaxed dimples which

Figure 4.8 SEM fractography of (A) Al7075, (B) FSPed Al7075, and (C) FSPed Al7075/CCSA.

89

Applications of coconut shell ash/particles in modern manufacturing

Table 4.7 Surface roughness analysis measurement. Rotational Processing Samples Surface roughness, speed (rpm) speed (mm/ Ra (µm) min) Ra1

1500

20

FSPed Al7075 FSPed Al7075/ CCSA

Ra2

Ra3

Mean Ra (µm)

Er 6 5 (%)

Ra

Ra

12.05 11.24 11.53 11.61

0.5805

3.00

0.149

3.01

2.93

2.98

dictates cup and cone shape. This type of fracture can be attributed to sudden loading of the AMC with low ductility, hence rock candy failure.

4.7.2 Evaluation of surface integrity for the processed samples The integrity of the fabricated surface is very important in FSP or other manufacturing industries where surface finish is a primary concern. Surface roughness measurement is very vital in the final product of the fabricated samples and this will dictate the accuracy and high quality of the product, by doing so, it will boost the marketability at the same time is cost-effective [29,30]. Table 4.7 shows the results of surface roughness in which the reading was obtained at three points on the processed samples. The average values of the measurement were then computed and recorded. It was revealed that when the CCSA was added to the aluminum alloy during the FSP, it was noted that the surface integrity was greatly improved as shown in Table 4.7. The ranges of average surface roughness value, Ra was 2.93 3.01 μm with a mean value of 2.98 μm and this is far lower than when no particle was used as reinforcement which gave a range between 11.24 and 12.05 μm with a mean value of 11.61 μm. From this analysis, the addition of CCSA improved the surface of the fabricated FSPed Al7075/CCSA excellently.

4.7.3 Structural evaluation analysis: X-ray diffraction results Table 4.8 revealed the results of XRD measurement for crystallite size which was obtained from the acquired data via Wilson and Scherrer equations as depicted in Eq. (4.1). The d spacing was obtained from the machine data at the highest peak and was supported by Bragg’s equation in Eq. (4.2), the full width at half maximum (FWHM) was computed, the microstrain (ε) was

Table 4.8 XRD measurement data. Samples Microstrain (ε) 3 1022

FSPed Al7075 FSPed Al7075/ CCSA Al7075

FWHM, ~ Crystallite size, C Crustal ( ) (nm) plane

d spacing (Å)

2θ ( )

5.0381 4.1142

0.213 0.174

41.2 38.6

111 111, 211

2.364 2.369

38.1 5.8912 37.9 6.7115

4.2535

0.180

48.7

111

2.364

38.1 4.2164

Dislocation density (δ) (Lines/ m2) 3 1014

Applications of coconut shell ash/particles in modern manufacturing

91

computed based on Williamson hall formula using Eq. (4.3), and also dislocation density (δ) which was computed with Eq. (4.4) [31,32]. C5

kƛ βcosθ

nƛ 2sinθ βcosθ ε5 4 1 δ5 2 C d5

(4.1) (4.2) (4.3) (4.4)

where, θ is the Bragg’s angle; ƛ is the wavelength, n is the 1, and βis the FWHM: Diffraction pattern, phases, and crystal structure were being analyzed by XRD in this study. Fig. 4.9 represents XRD structural pattern with varying crystal phases embedded. Three samples were tested which are parent material Al7075 with peaks of color pink, processed parent material FSPed Al7075 with peak of color red, and the fabricated AMC under investigation FSPed Al7075/CCSA with peaks of color blue, the highest peak (111) located at the position of in 2θ values. It was established from the results of XRD analysis that all the tested samples have common peaks which are (111), (200), (220), (311), and (222) and in addition to these peaks, the fabricated Al7075/CCSA have the following peaks to its own (100), (110), and (212). Meanwhile the intensity of the parent material AL7075 was 2500 cps, the processed parent material intensity was recorded to be 3500 cps while the fabricated AMC has its intensity at 6000 cps making it have the highest intensity which dictates the influence of CCSA on the aluminum metal matrix composites. It was revealed from Table 4.8 that the CCSA has excellent influence on the structural component of fabricated aluminum alloy matrix composite in a way that the crystalline size was recorded smallest 38.6 nm as against the processed parent material FSPed Al7075 with 41.2 nm while the unprocessed parent material Al7075 had 48.7 nm. The dislocation density (δ) for the fabricated AMC FSPed Al7075 had the highest value with 6.7115 3 1014 (Lines/m2) while the processed but unreinforced parent material has 5.8912 3 1014 (Lines/m2) whereas the parent material had the least value of 4.2164 3 1014 (Lines/m2) indicating that the reinforcement played a key role in the density of the material.

92

Figure 4.9 XRD structural pattern for the tested samples.

Omolayo M. Ikumapayi et al.

Applications of coconut shell ash/particles in modern manufacturing

93

4.8 Conclusion From the above literatures reviewed, experimental study, results obtained, and the discusions, it has been established that coconut shell particles finds applications in the metal, polymer, and ceramic matrix composites; in the concrete reinforcement, aggregate, and as filler; in the activated carbon or as charcoal; in the energy and fuel generation; in the water purification and heavy metals removal. Variability in the elemental and chemical compositions, chemical contents of coconut shell particles were documented, as well as mechanical and physical properties of coconut shell. It was further established from the experimental analysis carried out that CCSA is suitable for the fabrication of AMC via FSP. In this study, it was revealed that the ranges of average surface roughness value, Ra was 2. 93 3.01 μm with a mean value of 2.98 μm and this is far lower than when no particle was used as reinforcement which gave a range between 11.24 and 12.05 μm with a mean value of 11.61 μm. From this analysis, the addition of CCSA improved the surface of the fabricated FSPed Al7075/CCSA excellently. It was noted that parent material Al7075 has 2500 cps intensity, the fabricated FSPed Al7075 has 3500 cps intensity while the fabricated aluminum metal matrix composite Al7075/CCSA had 6000 cps intensity. It was further noted that CCSA perform excellent structurally when crystallite size for FSPed Al7075/CCSA had 38.6 nm and the processed parent material FSPed Al7075 with 41.2 nm while the unprocessed parent material Al7075 had 48.7 nm.

Conflict of interest The authors declared that there is no known conflict of interests.

References [1] Ikumapayi OM, Akinlabi ET. Data showing the effects of vibratory disc milling time on the microstructural characteristics of coconut shell nanoparticles (CS-NPs). Data Br 2019;22:537 45. Available from: https://doi.org/10.1016/j.dib.2018.12.067. [2] Leman AS, Shahidan S, Senin MS, Hannan NIRR. A preliminary study on chemical and physical properties of coconut shell powder as a filler in concrete. IOP Conf Ser

94

Omolayo M. Ikumapayi et al.

Mater Sci Eng 2016;160:012059. Available from: https://doi.org/10.1088/1757899X/160/1/012059. [3] Kanojia A, Jain SK. Performance of coconut shell as coarse aggregate in concrete. Constr Build Mater 2017;140:150 6. Available from: https://doi.org/10.1016/j. conbuildmat.2017.02.066. [4] Oyedepo OJ, Olanitori LM, Akande S. Performance of coconut shell ash and palm kernel shell ash as partial replacement for cement in concrete. J Build Eng 2015;2:18 24. [5] Nadir Y, Sujatha A. Durability properties of coconut shell aggregate concrete. KSCE J Civ Eng 2018;22:1920 6. Available from: https://doi.org/10.1007/s12205-0170063-6. [6] Bello SA, Hassan SB, Agunsoye JO, Kana MGZ, Raheem IA. Tribology in industry synthesis of uncarbonised coconut shell nanoparticles: characterisation and particle size determination. Tribol Ind 2015;37:257 63. [7] Salleh Z, Islam MM, Yusop MYM, Idrus MAMM. Mechanical properties of activated carbon (AC) coconut shell reinforced polypropylene composites encapsulated with epoxy resin. APCBEE Procedia 2014;9:92 6. Available from: https://doi.org/ 10.1016/j.apcbee.2014.01.017. [8] Oluwole OI, Oluwaseun KL. Mechanical, abrasion and water absorption characteristics of coconut shell ash and charcoal based polyester composites. West Indian J Eng 2016;16:51 67. [9] Caccin M, Giacobbo F, Da Ros M, Besozzi L, Mariani M. Adsorption of uranium, cesium and strontium onto coconut shell activated carbon. J Radioanal Nucl Chem 2013;297:9 18. Available from: https://doi.org/10.1007/s10967-012-2305-x. [10] Son S-J, Choi J-S, Choo K-Y, Song S-D, Vijayalakshmi S, Kim T-H. Development of carbon dioxide adsorbents using carbon materials prepared from coconut shell. Korean J Chem Eng 2005;22:291 7. Available from: https://doi.org/10.1007/ BF02701500. [11] Song C, Wu S, Cheng M, Tao P, Shao M, Gao G. Adsorption studies of coconut shell carbons prepared by KOH activation for removal of lead(ii) from aqueous solutions. Sustain 2014;6:86 98. Available from: https://doi.org/10.3390/su6010086. [12] Said M, Machunda RL. Defluoridation of water supplies using coconut shells activated carbon: batch studies. Int J Sci Res 2014;3:2327 31. [13] Joseph CG, Anisuzzaman SM, Abang S, Musta B, Quek KS, Wong XL. Adsorption performance and evaluation of activated carbon from coconut shell for the removal of chlorinated phenols in aqueous medium. Medziagotyra 2017;23:389 98. Available from: https://doi.org/10.5755/j01.ms.23.4.16221. [14] Raju SS, Rao GS. Assessments of desirability wear behaviour on al- coconut shell ash - metal matrix composite using grey - fuzzy reasoning grade. Indian J Sci Technol 2017;10:1 11. Available from: https://doi.org/10.17485/ijst/2017/v10i15/113826. [15] Aku SY, Yawas DS, Apasi A. Evaluation of cast Al-Si-Fe alloy/coconut shell ash particulate composites. Gazi Univ J Sci 2013;26:449 57. [16] Siva Sankara Raju R, Panigrahi MK, Ganguly RI, Srinivasa Rao G. Investigation of tribological behavior of a novel hybrid composite prepared with Al-coconut shell ash mixed with graphite. Metall Mater Trans A Phys Metall Mater Sci 2017;48:3892 903. Available from: https://doi.org/10.1007/s11661-017-4139-1. [17] Bello SA, Agunsoye JO, Adebisi JA, Anyanwu JE, Bamigbaiye AA, Hassan SB. Potential of carbonised coconut shell as a ball-milling interface for synthesis of aluminium (1xxx) nanoparticles. Ann Fac Eng 2017;15:149 57. [18] Sareena C, Ramesan MT, Purushothaman E. Utilization of coconut shell powder as a novel filler in natural rubber. J Reinf Plast Compos 2012;31:533 47. Available from: https://doi.org/10.1177/0731684412439116.

Applications of coconut shell ash/particles in modern manufacturing

95

[19] Agunsosoye JO, Isaac TS, Samuel SO. Study of mechanical behaviour of coconut shell reinforced polymer matrix composite. J Min Mater Charact Eng 2012;2012:774 9. Available from: https://doi.org/10.4236/jmmce.2012.118066. [20] De Oliveira PF, Marques MDF V. Comparison between coconut and curaua fibers chemically treated for compatibility with PP matrixes. J Reinf Plast Compos 2014;33:430 9. Available from: https://doi.org/10.1177/0731684413516392. [21] Balan AK, Mottakkunnu Parambil S, Vakyath S, Thulissery Velayudhan J, Naduparambath S, Etathil P. Coconut shell powder reinforced thermoplastic polyurethane/natural rubber blend-composites: effect of silane coupling agents on the mechanical and thermal properties of the composites. J Mater Sci 2017;52:6712 25. Available from: https://doi.org/10.1007/s10853-017-0907-y. [22] Sarki J, Hassan SB, Aigbodion VS, Oghenevweta JE. Potential of using coconut shell particle fillers in eco-composite materials. J Alloy Compd 2011;509:2381 5. Available from: https://doi.org/10.1016/j.jallcom.2010.11.025. [23] Arena N, Lee J, Clift R. Life cycle assessment of activated carbon production from coconut shells. J Clean Prod 2016;125:68 77. Available from: https://doi.org/ 10.1016/j.jclepro.2016.03.073. [24] Endut A, Abdullah SHYS, Hanapi NHM, Hamid SHA, Lananan F, Kamarudin MKA, et al. Optimization of biodiesel production by solid acid catalyst derived from coconut shell via response surface methodology. Int Biodeterior Biodegrad 2017;124:250 7. Available from: https://doi.org/10.1016/j.ibiod.2017.06.008. [25] Gunasekaran K, Annadurai R, Kumar PS. A study on some durability properties of coconut shell aggregate concrete. Mater Struct Constr 2015;48:1253 64. Available from: https://doi.org/10.1617/s11527-013-0230-2. [26] Ikumapayi OM, Akinlabi Esther T, Majumdar JD. Influence of carbonaceous agrowastes nanoparticles on physical and mechanical properties of friction stir processed AA7075-T651 metal matrix composites. Surf Topogr Metrol Prop 2019;7:1 17. Available from: https://doi.org/10.1088/2051-672X/ab3aae. [27] Li H, Chen P, Wang Z, Zhu F, Song R, Zheng Z. A tensile properties, microstructures and fracture behaviors of an Al-Zn-Mg-Cu alloy during ageing after solution treating and cold-rolling. Mater Sci Eng A 2019;742:798 812. Available from: https://doi.org/10.1016/j.msea.2018.03.098. [28] Hao Z, Fu X, Men X, Zhou B. Study on tensile and fracture properties of 7050T7451 aluminum alloy based on material forming texture characteristics. Mater Res Express 2019;6. Available from: https://doi.org/10.1088/2053-1591/aaf304. [29] Hartmann M, Böhm S, Schüddekopf S. Influence of surface roughness of tools on the friction stir welding process. J Weld Join 2014;32(6):12. Available from: https:// doi.org/10.5781/JWJ.2014.32.6.22. [30] Ikumapayi OM, Akinlabi ET. Efficacy of α-grade Titanium alloy powder (Ti-6Al2Sn-2Zr-2Mo-2Cr-0. 25Si) in surface modification and corrosion mitigation in 3.5% NaCl on friction stir processed armour grade 7075-T651 Aluminum alloys insight in defence applications. Mater Res 2019;1 20. Available from: https://doi.org/ 10.1088/2053-1591/ab1566. [31] Pandey V, Singh JK, Chattopadhyay K, Srinivas NCS, Singh V. Influence of ultrasonic shot peening on corrosion behavior of 7075 aluminum alloy. J Alloy Compd 2017;723:826 40. Available from: https://doi.org/10.1016/j.jallcom.2017.06.310. [32] Offor PO, Okorie BA, Ezema FI, Aigbodion VS, Daniel-mkpume CC. Synthesis and characterization of nanocrystalline zinc sulphide thin films by chemical spray pyrolysis. J Alloy Compd 2015;650:381 5. Available from: https://doi.org/10.1016/ j.jallcom.2015.07.169.

CHAPTER FIVE

Fractography analysis and constitutive modeling for dynamic plasticity of austenite stainless steel (ASS 304) at hot-working temperatures A. Anitha Lakshmi1, Ch. Srinivas Rao2 and Tanya Buddi1 1

Department of Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India 2 Department of Mechanical Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India

5.1 Introduction Austenitic stainless steel is broadly used in broad applications in the area of nuclear power plants, marine applications, and heat exchangers due to its outstanding properties. Excellent corrosion resistance is due to less carbide precipitation which is because of the presence of lower percentage of carbon composition, that is, 0.08% by weight. High resistance to elevated temperatures is due to presence of chromium and nickel by composition. It is easily sensitive to work hardening due to very less stacking fault energy and nonmagnetic nature [1]. In particular temperature ranges and strain rates these steels testimony dynamic strain aging (DSA) or Portevin-Le Chatelier (PLC) effect [2]. DSA occurs when solute atoms are large enough such that instead of locking the dislocation they follow along dislocation during its flow and gets collected at the core. This behavior is represented by serrations, that is, can see tooth-like undulating zig-zag outline in the stress
strain graph [3]. Constitutive models give detailed description of strain, punch strain rate, and blank temperaturedependent flow curve conduct of sheet metals and alloys. The models selected represent increase in resistance to plastic deformation at increasing temperatures and low strain rates causing improvement in the flow stress. Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00005-1

© 2020 Elsevier Ltd. All rights reserved.

97

98

A. Anitha Lakshmi et al.

Researchers modified unique constitutive models to precisely expect the flow curve behavior by considering the effect of forming process parameters [4]. In the past few decades a meaningful amount of work was done on titanium, magnesium, and tantalum alloys at hot working to link the process parameters with flow stress through phenomenological constitutive models, physical constitutive models, and semi-empirical models. A widespread constitutive stress
strain correlation equation in relation of strain-hardening exponent (n-value) and the strain-rate sensitivity exponent (m-value) to describe the work-hardening phenomenon was anticipated in 1957 by the researchers Fields and Bachofen (FB) [5]. Cheng et al. [6] used FB model to study the mechanical properties of alloy sheet AZ31 magnesium at the elevated hot working temperatures and strain rates. They observed that the alloy AZ31 magnesium sheet had an obviously recrystallization plasticity behavior at higher temperature and low strain rates. Hence basic FB model was inexact to illustrate the work softening behavior. Added Quan et al. [7] revised the existing equation by addition of the softening parameter suggested by Zhang [8] in the equation. The change was well suited for prediction of work softening behaviors of 7075 aluminum alloy. Johnson
Cook (JC) constitutive model is a phenomenological flow stress model based on working conditions sheet temperature, strain induced, and punch strain-rate. The JC model is widely used for various varieties of materials over different ranges of strain-rate and temperatures. The JC model is used by most of the researchers due to its easiness of few experiments and fewer material constants. It has been testified in various works that the JC model could not predict results accurately when applied to materials subjected to high strains. The JC model is improved by considering the effects of forming temperature and strain-hardening behavior. This model has been adapted to forecast the flow stress curve combining the effect of the strain rate and temperature. Due to its simplicity and accuracy for engineering applications, the phenomenological constitutive model including the Arrhenius term proposed primarily by Jonas et al. [9] has been commonly adopted in routine to explain the relationship among flow behavior of steel and various forming process parameters. This model showed a good correlation between Al
Zn
Mg
Cu alloys and Ni
Ti shape memory alloys’ for both predicted and experimental flow behavior. Arrhenius-type formula is used under different deformation conditions to predict the flow behavior of Fe
22Cr
25Ni
3.5W
3Cu
1.5Co steel [10]. The results indicated

Fractography analysis and constitutive modeling

99

good correlation and generalization by integrating strain correction with polynomial matching of the fifth order. Upon revising the basic model, the elevated-temperature flow activity of different materials with varying composition is related. For the estimation of flow pressure in a wrought magnesium alloy and 42CrMo iron, strain-dependent variable and strain-rate compensation are introduced in Sine-hyperbolic constitutive equation [11,12]. In 1992, Khan and Huang (KH) [13] suggested a constitutive viscoplastic model to predict coarse grain Al 1100 behavior at a wide range of strain levels. The basic model did not consider the temperature influence. Khan
Huang
Liang (KHL) introduces the next change in the design, taking into account the combined effect of stress, strain frequency, and temperature to determine work-hardening behavior of the function. Khan and Liang [14] defined the KHL template parameter range for antalum, tantalum alloy 2.5% tungsten, and AerMet 100 steel in the year 2000. The FEM is a common tool to identify the optimal cycle parameters. The response of the material under the defined loading conditions can be simulated by inserting a Constitutive equation that describes the materials’ flow behavior. The reliability of FEM simulations are based on the precision of the deformation tensile behavior described by the constitutive numerical equations for the specific material sheet. A suitable constitutive model, their parameters are needed for predicting the flow behavior for ASS 304 [15,16], at hot working temperatures. The main objective of this chapter is to describe the impact of strain induced, punch strain rate, and deformation sheet temperature on the tensile flow stress curve performance for ASS 304 at hot working temperatures. After investigating the high-temperature deformation characteristics, a suitable mathematical model was developed using the experimental stress
strain data collected by performing hot working tensile tests. Four constitutive material model, namely revised Fields
Backofen (m-FB), revised Johnson
Cook (m-JC), revised Arrhenius (m-Arr.), and KHL, are therefore designed to expect the ASS 304 flow curve behavior at hot working temperatures. Khaleel and Nitin Kotkunde in their previous works have developed constitutive models for (ASS) 316 [15,16]. Flow curve prediction constructed on m-Arr. is pretty precise within the nondynamic strain ageing region (973
1173K temperature range and 1025, 1024, 1023, and 1022 s 21 strain rates). Nevertheless, in the DSA area these models were unable to accurately forecast flow curve due to the zig-zag pattern in the flow curve. In addition, to understand the material properties in accordance with micrographs, fractography of fractured

100

A. Anitha Lakshmi et al.

tensile specimen was done. In the current work, experimental data has been evaluated by conducting isothermal uniaxial tensile tests at hot working temperatures (700 C
900 C) in intervals of 50 C at constant strain rates (1024, 1023, and 1022 s21) along three orientations (0, 45, and 90 degrees) with respect to the rolling direction. The observed stress
strain values are then used to determine the flow stress curve, strain induced, strain rate, and deformation temperature related constitutive equation. The material model’s suitability is measured by evaluating of correlation coefficient, standard deviation value, and average absolute error.

5.2 Material and experimental details In the present research, 1.0-mm thick alloy sheet ASS 304 was used. Table 5.1 shows the composition of the material used. Wire-cutting electro-discharge machining process is used to machine the samples out of the raw material sheet for great accuracy, finish, etc. The specimen size is as per standards of ASTME8/E8M-11 subsize. Tensile processing is conducted on a computer-coordinated UTM (50 kN) at isothermal conditions (Fig. 5.1). Software revisions were competently done and variable crosshead speed was confirmed to give constant strain rate. Fig. 5.1 also represents enlarged view for control panel and split furnace with resistance heating to heat specimen up to 1000 C. The furnace is round opening type with two controllers one for left half and second for the right half. The heating element is made of kanthal, characterized by high resistivity and capability to withstand high surface load. They can be used at maximum element temperature of 1425 C (2600 F). The pull rods for the high-temperature testing are made of Inconel 715 super alloy. Generally, the spectrum of strain rate for static tension test with hydraulic or screw driven machine is considered between 1025 and 1021 s21 [17]. Uniaxial tensile testing and development of constitutive model of ASS 304 is done in the temperature range of 50 C
650 C [18
20]. To study deformation behavior of the Table 5.1 Chemical composition of the as received ASS 304 steel sheets (in weight percent). Element Fe Cr Ni Mo Si Mn Cu Co C

(Wt.%) composition 67.69 6.61 0.79 2.41 1.29 0.37 0.22 0.20 0.019

Fractography analysis and constitutive modeling

101

Figure 5.1 Computerized UTM with enlarged view of high-temperature contact type extensometer and three zone resistance heating split furnace.

material at elevated temperatures experiments are conducted from 700 C to 900 C at an interval of 50 C at strain rates 1024, 1023, and 1022 s21 in three orientations R0, R45, and R90. Fig. 5.2, displays the representative fractured test workpiece at varying range temperatures. For fractography examination the fractured surface of the specimen is used. A computerized machine is used for measuring and recording the load
displacement curve which is compiled into true stress
true strain plots. Elastic region is deducted from the true stress versus true strain plotted curve to obtain true stress and true strain curve.

5.3 Microstructure examination and fractography Sample is prepared for microstructural observation by following a sequence of processes like rough grinding, wet polishing, emery polishing,

102

A. Anitha Lakshmi et al.

Figure 5.2 Representative successfully tested specimen of ASS 304 at various temperatures.

and finally application of etchant. It is examined under different magnifications using optical microscope and micrographed using standard technique, bright field illumination. The metal microstructure (Fig. 5.3) comprised of equiaxed grains with high number of annealing twins, which is the outcome of static recrystallization and grain growth during heat treatment [15,16]. Neither structures dislocation (DSs) nor low angle boundaries (LABs) are observed. These changes at different magnifications exposed the two distinct microconstituents, namely ASS 304 alloy are alpha (BCC) and gamma (FCC) phases. In the transformed matrix the alpha (α) stage (light) grains are well scattered in the gamma (β) (dark phase). The alpha grain’s volume fraction is largely scattered with uneven dimensions and shape which is greater than beta phase’s volume fraction. The features of fracture can be analyzed by fractography. By conducting fractography the nature of failure and formability can be analyzed. A SEM (S-3400N, 15 kV) is used to thoroughly examine the fractured surface of the fully deformed tensile test samples. The observation samples are cut parallel to fractured surface. At a range of magnifications, the surfaces of fracture are studied to establish the fracture approach and to describe the inherent properties of the tensile fracture surface during uniaxial tensile testing. The SEM images were obtained for the fracture surface of all the specimens at five temperatures and in three orientations at 0.001 strain rate. The various SEM images and the EDS reports are shown in Figs. 5.3
5.12. If the main cause of failure is strain, ASS 304 alloys collapse through a procedure known as microvoid coalescence. Microvoid

Fractography analysis and constitutive modeling

103

Figure 5.3 Optical micrographs showing the key micro constituents in ASS 304 (A) high magnification of 500 3 showing grain size. (B) high magnification of 10,000 3 showing α-phase and β-phase. (C) Overall morphology at 250 3 . (D) Energy-dispersive X-ray spectroscopy (EDS) analysis of inclusion portion.

nucleates in regions where dispersed strain discontinuity, such as those associated with second-phase grains, inclusions, seed edges, and dislocation pile-ups. The microvoids grow, coalesce, and eventually form a continuous layer surface of fracture as the stress increases in the material. Cup-like depressions are called dimples, and the form of fracturing is described as dimple breakup. If various nucleating sites are triggered and neighboring voids combine (coalesce) before they can expand to a larger size, tiny dimples of different sizes and shapes are created. Forming of dimples of shallow shape can involve microvoids to be connected by shear through slip bands. In the surface fracture, which specifies ductile fracturing, where large number of tiny form and volume dimples and microvoids are found. A large distribution of deep size depressions of various dimensions and shapes have been identified for the broken samples in three separate rolling directions at 700 C. The dimples shown in Fig. 5.4B R45 and Fig. 5.4C R90 show an elongated horseshoe shape and are shallower than dimples obtained in Fig. 5.4A in R0 direction. This result implies that shear fracture emerges in the R45 and R90 direction and causes the decrease of ductility.

104

A. Anitha Lakshmi et al.

Figure 5.4 SEM images taken for the fracture surface of 1 mm thickness of ASS 304 at 700 C. (A) Fracture surface for rolling direction R0 at 5000 3 magnification. (B) Fracture surface for diagonal direction R45 at 5000 3 magnification. (C) Fracture surface for transverse direction R90 at 5000 3 magnification.

This can be analyzed from the experimental results as shown in Table 5.2, which represents the ductility in terms of percentage of elongations. It shows that elongation in R0 direction is more compared with other rolling directions. In Fig. 5.5 more dimples and large void size is seen in R0 and R45 direction microstructures compared with R90 direction which can be verified in Table 5.2 by greater percentage of elongation in R90 direction. In Fig. 5.6 at 800 C the microstructures in R45 direction shown in Fig. 5.6B shows large voids compared with R0 and R45 shown in Fig. 5.6A,C direction which shows from Table 5.2 that percentage elongation in R45 direction is less compared with R0 and R90 direction. In Fig. 5.7 at 850 C the microstructures in R45 and R90 direction shown in Fig. 5.7B and C shows large voids compared with R0 shown in

Fractography analysis and constitutive modeling

105

Figure 5.5 SEM images taken for the fracture surface of 1 mm thickness of ASS 304 at 750 C. (A) fracture surface for rolling direction R0 at 5000 3 magnification. (B) Fracture surface for angular direction R45 at 5000 3 magnification. (C) Fracture surface for perpendicular direction R90 at 5000 3 magnification.

Fig. 5.7A direction which shows from Table 5.2 that percentage elongation in R45 and R90 direction is less compared with R0 direction. At 900 C as shown in Fig. 5.8, the size of the voids is decreasing with increase in no of voids indicating ductile nature as evidenced in Table 5.2. At hot working temperatures, that is, at 700 C formation of dimples occur where carbide precipitation begins at 750 C which increase in more precipitation with further increase in temperature up to 900 C has been observed through SEM micrographs as shown in Fig. 5.9. The dimples diminish with increase in temperature from 700 C, with the formation of voids with increase in depth and decrease in size, resulting in more number of small voids at 900 C. EDS represents types of chemical elements present in the fractured surface. The EDS report reflects trace of some of the chemical elements present in the fractured surface. These reports confirm the alloying elements

106

A. Anitha Lakshmi et al.

Figure 5.6 SEM images taken for the fracture surface of 1 mm thickness of ASS 304 at 800 C. (A) fracture surface for rolling direction R0 at 5000 3 magnification. (B) Fracture surface for angular direction R45 at 5000 3 magnification. (C) Fracture surface for perpendicular direction R90 at 5000 3 magnification.

such as Cr, Ni, Si, Mn, Mo, Co, etc. Figs. 5.10
5.12 clearly show that the EDS reports confirm that inclusion is evident in the layer of the fracture. The majority of the composition involves chromium and carbide. It could be chromium carbide as shown in Tables 5.3
5.5.

5.4 Constitutive models Constitutive equations predict the flow curve behavior of the material. These are used to model the response of the material under defined loading conditions as material data input to FE codes. Performance of numerical simulation is highly dependent on consistency of the material behavioral deformation described by constituent equations. Preferably, constituent models must have a required number of constants (material) and forecast flow curve with

Fractography analysis and constitutive modeling

107

Figure 5.7 SEM images taken for the fracture surface of 1 mm thickness of ASS 304 at 850 C. (A) Fracture surface for rolling direction R0 at 5000 3 magnification. (B) Fracture surface for angular direction R45 at 5000 3 magnification. (C) Fracture surface for perpendicular direction R90 at 5000 3 magnification.

acceptable accurateness and consistency over a varied temperature range and stress level. In the current chapter five modified constituent model equations, namely JC, ZA, m-Arr., KHL, and m-FB were developed to predict ASS 304 flow stress behavior in the hot forming regions. All models developed in the study are based on the MATLAB version R2010b.

5.5 Constitutive model (m-FB) modified Fields
Backofen The flow stress model equation to forecast the flow stress using the FB model is σ 5 Kεn ε_ m

(5.1)

108

A. Anitha Lakshmi et al.

Figure 5.8 SEM images taken for the fracture surface of 1 mm thickness of ASS 304 at 900 C. (A) Fracture surface for rolling direction R0 at 5000 3 magnification. (B) Fracture surface for angular direction R45 at 5000 3 magnification. (C) Fracture surface for perpendicular direction R90 at 5000 3 magnification.

where, n is the strain-hardening exponent, K is the strength coefficient, and m is the constant strain rate sensitivity exponent. An improved model of FB model was established by incorporating a softening equation term (bT 1 sε) into Eq. (5.1) hence the m-FB model is stated as σ 5 Kεn ε_ m ðbT 1 sεÞ

(5.2)

where, s5

dinσ dinε

(5.3)

where, b is the product constant and s is the softening factor of the ASS due to the increase of the stress. In Eq. (5.3) the material parameters are determined using nonlinear unconstrained optimization to reduce error. Parameters K, n, and m differ from temperature to strain frequency. The

Fractography analysis and constitutive modeling

109

Figure 5.9 SEM images taken for the fracture surface of 1 mm thickness of ASS 304 at R90 orientation. (A) Fracture surface at 10,000 3 magnification for 700 C. (B) Fracture surface at 10,000 3 magnification for 750 C. (C) Fracture surface at 10,000 3 magnification for 800 C. (D) Fracture surface at 10,000 3 magnification for 850 C. (E) Fracture surface at 10,000 3 magnification for 900 C.

110

A. Anitha Lakshmi et al.

Figure 5.10 EDS report for fractured surfaces at different temperatures of ASS 304 steel of thickness 1 mm at 0.001 s21 in rolling direction R0 (A) 700 C, (B) 750 C, (C) 800 C, (D) 850 C, and (E) 900 C.

temperature and strain variance of the parameters are empirically interpreted as γ K 5 α 1 βln_ε 1 (5.4) T C (5.5) n 5 A 1 Bln_ε 1 T E m 5 C 1 Dln_ε 1 (5.6) T In addition, these quantitative interactions are used to forecast flow stress using the m-FB method, while integrating the strain level and temperature dependence of the flow stress in the estimation of flow stress (Table 5.6).

Fractography analysis and constitutive modeling

111

Figure 5.11 EDS report for fractured surfaces at different temperatures of ASS 304 steel of thickness 1 mm at 0.001 s21 in rolling direction R45 (A) 700 C, (B) 750 C, (C) 800 C, (D) 850 C, and (E) 900 C.

5.6 Constitutive model (KHL) Khan
Huang
Liang The equation to predict the flow stress using KHL model is given by Eq. (5.7) 
 
C
 ε_ ln_ε n1 n0 τm 2T m σ 5 A 1 B 12 εp (5.7)  lnD0 Tm 2Tref ε_ where, σ is the true stress (Cauchy) and εp is the true plastic strain. The melting, prevailing, and the reference temperatures are represented by Tm, T, Tref, respectively. D0 5 1026 s21 known as rate of deformation (a con stant used to nondimensionalize the strain rate term and ε_ 5 1022 s21

112

A. Anitha Lakshmi et al.

Figure 5.12 EDS report for fractured surfaces at different temperatures of ASS 304 steel of thickness 1 mm at 0.001 s21 in perpendicular direction R90 (A) 700 C, (B) 750 C, (C) 800 C, (D) 850 C, and (E) 900 C.

(reference strain rate, Tref at a reference temperature, usually temperature, at which material constants like A, B, and n0 are determined). ε_ is the strain rate. n0, n1, C, and m are additional material constants. For ASS 304, the melting temperature was taken to be 1400 C. The preliminary temperature of 700 C was taken as the initialtemperature  for experiments. At reference temperature and strain rate when ε_ε_ 5 1 the flow stress given by Eq. (5.7) will reduce to σ 5 A 1 Bεnpo

(5.8)

Taking natural logarithm on both side yields, lnðσ 2 AÞ 5 no lnε 1 lnB

(5.9)

113

Fractography analysis and constitutive modeling

Table 5.2 Representing experimental results of percentage of elongation of ASS 304 ranging from 700 C to 900 C at 0.001 s21 in intervals of 50 C. Temperature ( C) Rolling direction % Elongation

700

R0 R45 R90 R0 R45 R90 R0 R45 R90 R0 R45 R90 R0 R45 R90

750

800

850

900

55.2 41.4 51.7 64.1 61.6 66.2 71.7 67.9 70.9 74.1 68.4 73.9 76.5 65.3 76.4

Table 5.3 Weight % for EDS report of fractured surface at different temperatures for R0 orientation. Elements Weight %

C O Si Cr Mn Fe Co Ni Mo Na Cl

700 C

750 C

800 C

850 C

900 C

12.02 4.68 0.96 15.97 0.80 56.79

25.57 17.7 0.73 12.01 0.65 36.11 0.32 3.31 0.52 1.49 0.99

12.19 21.94 0.57 15.64 1.79 45.02 0.39 2.41 0.06

11.46 24.17 0.75 14.31 1.68 43.10 0.25 2.8 0.05 0.88 0.55

22.09 25.66 1.38 8.21 0.96 35.97

5.43 1.13 0.76

1.71 0.46 0.94 1.08

At the present condition A is the yield stress, the slope of the line is n0, and B is obtained from intercept to the vertical axis. At yield point the strain is relatively small, so Eq. (5.7), at reference temperature, can be approximated as σy 5 AeClnð_εÞ

(5.10)

114

A. Anitha Lakshmi et al.

Table 5.4 Weight % for EDS report of fractured surface at different temperatures for R45 orientation. Weight % 700 C 750 C 800 C 850 C 900 C

C O Si Cr Fe Co Ni Cu Mo

2.53 12.5 0.18 16.34 55.28 5.35 7.55 0.26

1.73 9.02 0.97 16.99 59.4 2.85 7.85 0.92 0.26

2.8 13.46 0.45 18.77 54.65 3.28 6.03 0.48 0.09

1.9 18.95 0.1 19.58 51.8 5.12 2.51

2.93 21.18 0.27 15.01 53.58 4.58 2.25

0.03

0.18

Table 5.5 Weight % for EDS report of fractured surface at different temperatures for R90 orientation. Weight % 700 C 750 C 800 C 850 C 900 C

C O Si Cr Fe Co Ni Cu Mo

14.47 3.22 18.15 51.78

2.32 16.29 0.4 16.93 56.52

12.38

6.15 1.4

hence, ln

1.2 10.58 0.27 23.58 53.2 4.72 5.9 0.54 0.01

σ  y 5 Clnð_εÞ A

1.63 21.42 0.41 17 52.08 4.62 2.7 0.12 0.02

0.99 16.21 0.22 25.47 48.29 4.73 3.06 0.79 0.24

(5.11)

From the slope of the line equation constant C is calculated corresponding to Eq. (5.11). where, yield stress is σy At reference temperature material constant n1 denoted in Eq. (5.7) can be specified as   ε2A ln σ=eCln_ n 0 Bε  n1 5  (5.12) ln_ε ln 1 2 lnD 0 At different temperatures and strain rates the value of n1 obtained and constrained optimization is applied to obtain n1. Similarly, m in Eq. (5.7) can be determined from

Table 5.6 Material constants for modified m-FB constitutive model. α β γ A B C

R0 R45 R90

2 266.7194 2 309.0749 2 279.1167

3.9157 3.0957 3.7513

4.4888e5 4.9212e5 4.6334e5

2 0.4857 2 0.6684 2 0.4628

0.0191 0.0140 0.0177

845.4040 1.0188e3 823.86

D

E

F

B

s

1.0545 1.0704 1.0571

0.0373 0.0372 0.0371

2 451.9405 2 473.2827 2 458.359

0.0207 0.0212 0.0210

1.0412 2.2870 0.7164

116

A. Anitha Lakshmi et al.

Table 5.7 Material constants for KHL constitutive model. Orientations A B n0 n1

C

m

0.0786 0.0914 0.0623

6.5490 11.2765 9.094

R0 R45 R90

94.06 97.3693 101.1640

291.3360 463.1791 312.8112

0.4245 0.6646 0.4732

0.8724 0.6316 1.0777

 ln 1 2 Kσ m5 lnðT  Þ where;

(5.13)

"

#

 ε_ C ln_ε n1 n0 εp K 5 A 1 B 12  lnD0 ε_

Also, the value of m is obtained through constrained optimization. The average values of n1 and m were to be taken from the formulae given by Eqs. (5.12) and (5.13) but the correlation has been affected and therefore a stronger set of material constants n1 and m is computed using unconstrained nonlinear optimization to minimize error. Table 5.7 describes the product constant values for the KHL model.

5.7 Johnson
Cook (JC) model The flow stress with respect to [21,22] m-JC model, is stated as: 



σ 5 ðA 1 Bεn Þð1 1 Cln_ε Þð1 2 T m Þ

(5.14)

At reference temperature (Tref) and reference strain rate (ε_0 ), σ denotes for flow curve, letter A denotes for yield stress curve at B for strain hardening coefficient, symbol ε_ is strain rate   ε for plastic strain, symbol  which is dimensionless ε_ 5 ε_ε_0 with strain rate ε_ and at temperature (homologous) T , where, T 5

T 2 Tref Tm 2 Tref

absolute temperature (current) (T) and melting temperature Tm; for ASS 304. For ASS 304, the melting temperature was taken to be 1400 C.

117

Fractography analysis and constitutive modeling

Table 5.8 Material constants for JC constitutive model. Orientations A (MPa) B (MPa) n

C

m

R0 R45 R90

0.0647 0.0891 0.0604

0.4796 0.3820 0.5687

94.06 97.3693 101.1640

291.3360 463.1791 312.8112

0.4245 0.6646 0.4732

It should be noticed that independently the influence of the strain rate and temperature was assumed by the initial JC design. However, the experiments suggested a sum total effect of temperature and strain rate on the material’s flow stress [16,23]. This chapter uses modified JC mathematical model flow curve where in the old model, a revision is suggested considering both the strain rate, temperature effect. Modified equation of m-JC is set out in Eq. (5.15). 



σ 5 ðA1 1 B1 ε 1 B2 ε2 Þð1 1 C1 ln_ε Þexpðλ1 1 λ2 ln_ε ÞðT 2 Tr Þ

(5.15)

where, A1 ; B1 ; B2 ; C1 ; λ1 and λ2 are the new model material constants; the definitions of terms are similar to main JC model and are the material constants. The present scenario with reference to temperature considered is 923K and strain rate (reference) is 1024 s21. Lin et al. [24] proposed method to compute material constants is used. Table 5.8 summarizes the product constants for the m-JC model.

5.8 Constitutive equation (m-Arr.) type At elevated temperatures Arr. type model [21] denotes relation between stress flow, strain rate, and temperature. An equation of exponential (Zener
Hollomon) type where the Hollomon parameter represents the couple impact of temperature (current), strain rates on the material deformation.
 Q Z 5 ε_ exp (5.16) RT The m-Arr. equation is denoted below:
 Q n ε_ 5 A½sinhðασÞ exp 2 RT

(5.17)

118

A. Anitha Lakshmi et al.

As per hyperbolic law and reshuffling, the flow curve stress can also be written as a function of Zener
Hollomon parameter Eq. (5.18). 8 "
 #1=2 9
 = 1 < Z 1=n Z 2=n σ 5 ln 1 11 (5.18) ; α : A A But in this constitutive equation impact of strain has not been considered. The relationship between strain and flow curve stress is done by Xiao and Guo [29] as denoted below: σ 5 β 0 εβ 1 expð2 β 2 εÞ

(5.19)

where, β 0 ; β 1 and β 2 are constants. Now, by combining Eqs. (5.18) and (5.19) the final constitutive formula that satisfactorily explains the impact of strain rate temperature and strain on steady state flow stress is established as follows: 8 9
1=n "
2=n #1=2 = < β Z Z σ 5 0 εβ 1 expð2 β 2 εÞln 1 11 (5.20) : ; A A α The material constants A, α, n, Q, β 0, β 1, and β 2 are computed using stress versus strain data from tests conducted at varied temperatures (deformation) and strain rates. β 0, β 1, and β 2 are calculated at each strain rate and temperature. A trial equation connecting strain rate, temperature to β values is represented in Eq. (5.20); which connects the β values to Zener
Hollomon parameter (Z), depends on blank temperature and strain rate. Procedure developed by Xiao and Guo [29] is used to determine the constants. β 5 A 3 lnZ 1 B

(5.21)

The Arrhenius-type Ti-6Al-4V alloy constitutive model [23] is developed. The model has been established for monitoring compression at varied temperatures where the alpha phase-to-beta-phase transformation takes place. The variables of the Arrhenius model, that is, A, n, and Q, depend on strain condition. The model material constants are computed by enforcing polynomial fit. These model constant parameters are assumed to be not a function of strain in this research and different strain equation of exponential type for compensation is multiplied. The constants determined for m-Arr model are listed in the Tables 5.9 and 5.10.

119

Fractography analysis and constitutive modeling

Table 5.9 Material constants m-Arr. constitutive model. Orientations α (MPa21) N Q (kJ/mol)

R0 R45 R90

0.0038 0.0038 0.0038

6.1082 6.3321 6.3173

A (s21)

3.5794e5 3.6436e5 3.6738e5

4.459e15 7.4586e15 1.465e16

Table 5.10 Material constants for m-Arr. type constitutive model. Orientations β1 β2 β3

R0 R45 R90

A

B

A

B

A

B

0.0577 0.0745 0.0644

2 0.4393 2 0.9750 2 0.6811

0.0195 0.0204 0.0183

2 0.4766 2 0.5059 2 0.4432

2 0.0139 0.0216 0.0119

0.4248 2 0.6367 2 0.3761

5.9 Zerilli
Armstrong (m-ZA) model Mathematically flow stress of modified ZA model [21,22] is represented as given below, 

σ 5 ðC1 1 C2 εn Þexpf 2 ðC3 1 C4 εÞT  1 ðC5 1 C6 T  Þln_ε g

(5.22)

where, flow stress denoted by σ, equivalent plastic strain denoted as ε,  strain rate denoted as ε_ for, T 5 T 2 T ref, where current temperature is T, C1, C2, C3, C4, C5, C6, and n are the material constants, reference temperature is T ref (Tref 700 C as in JC model). Model m-ZA includes effects of strain hardening (isotropic), strain rate hardening, temperature (softening), and cumulative impact for temperature, strain, and strain rate measuring flow curve stress at high temperatures. Model constants were calculated using Kotkunde et al. [23] method. The list of the calculated constants is represented in Table 5.11.

5.10 Constrained optimization The least square method is enforced to obtain final material model constant values from 15 different strain values. This method involves trying to limit value optimization by reducing the average absolute errors

120

A. Anitha Lakshmi et al.

Table 5.11 Material constants for ZA constitutive model. Orientations C1 (MPa) C2 (MPa) C3 C4 C5

C6

R0 R45 R90

94.06 691.7799 0.0029 0.0090 0.1054 5.74e-4 0.498 97.3693 659.2269 0.0028 0.0075 0.0855 5.2719e-4 0.4835 101.1640 647.0943 0.0031 0.0072 0.0918 6.493e-4 0.4851

(Δ) between the observational (σexp) and the expected flow stress (σp). The formula is as follows: i5N σi 2 σ i 1X exp p Δ5 N i51 σiexp

(5.23)

where, the experimental flow stress is σexp, the predicted flow stress is σp, and the total number of data points being considered is N. The predictability of constitutive equations [25, 26, 29] is analyzed by generic statistical variables such as correlation coefficient R and mean absolute error (almost). The coefficient of correlation is a widely employed analytical instrument which provides information on the magnitude of the linear relationship between the observed and expected values. It can be expressed mathematically as follows: Pi5N i i i51 ðσ exp 2 σ exp Þðσ p 2 σp Þ R 5 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi (5.24) Pi5N i 2 Pi5N i 2σ Þ2 ðσ 2σ Þ ðσ exp p exp p i51 i51 where, for σexp and σp the average values are represented as σexp and σp are of.

5.11 Result and discussion The predictive potential of constitutive models was measured by the coefficient of regression, the mean actual error, and its standard deviation. While R’s quality may be high; the model’s output is not important because the model may appear to be skewed toward higher or lower information values [23]. Therefore, an average absolute error (almost), calculated by comparison of the relative error, is an unbiased indicator to assess the model’s predictability. Consequently, the predictive capacity of constitutive models was analyzed by the coefficient of correlation (R), the

Fractography analysis and constitutive modeling

121

average absolute error (A), and its standard deviation (S). The appropriateness of these designs is also measured on the origin of the amount of model constants which are to be measured and type of evaluation process followed. Such numerical parameters are mentioned in Table 5.9 and the amount of material constants to be calculated for all versions. Figs. 5.13 and 5.14 show a graphical comparison between the experimental and the predicted values in two representative settings for all models. Another atmosphere is low temperature and low frequency of stress, while the other conditions are high temperature and large level of stress. From the charts, m-Arr. model predictions are similar to tests values, while m-JC model predictions differ slightly from experimental values. Taking into account the coefficient of correlation both models denote a very high accuracy of fitness as the value of R measured is greater than 0.9. Figs. 5.13
5.15 denote correlation coefficient in relation to observed and expected values for five constitutive models. Quality of R can be skewed to greater and least values [21]. Consequently, standard deviation and delta quantifying parameters are used to verify the prediction exactness. Model m-Arr. system has a 3.5% average variance and a 2.9% standard deviation in rolling path R0. Compared with other models, the drawback of m-Arr model is that it requires evaluation of 10 material constants, which increase in the time and the complexity of computation. However, phenomenological models among the five models established are, m-JC, m-Arr., FB, and KHL models, that is, which do not take into account the physical conditions of material for expecting flow curve, where m-ZA model is a physical model and reflects the physical facets of materials such as thermodynamic theory and dislocation movement of atoms which are activated thermally and slip kinetics. So physical models, therefore are better compared with phenomenological models [8]. Even though the number of constants has to be assessed m-ZA is 7; the final expectations relate constants being set. Also, the statistical measuring values are lower compared with the m-ZA model. Thus, by considering all the factors, that is, numerical calculations, physical facets of flow curve forecasts, more number of constants, and difficulty intricated in deducing the constants, model m-ZA is a chosen model among the models (five) undertaken in the current chapter. Tables 5.12
5.14 show various constitutive models at 0-, 45-, and 90-degree rolling direction of sheet, respectively (Figs. 5.16 and 5.17). In terms of the correlation coefficient of m-Arr, the ZA models display a high appropriateness as the value R in all situations is greater than 0.98,

Figure 5.13 Assessment of experimental versus predicted data for models at 700 C temperature, 0.0001 s21 (A) R0 direction, (B) R45 direction, and (C) R90 direction.

Figure 5.14 Assessment of experimental versus predicted data for models at 900 C temperature, 0.01 s21 (A) R0 direction, (B) R45 direction, and (C) R90 direction.

124

A. Anitha Lakshmi et al.

Figure 5.15 The experimental and predicted correlation coefficient values in direction of R0 for models (A) m-JC, (B) m-ZA, (C) m-Arr, (D) FB, and (E) KHL.

Table 5.12 Statistical parameters for R0. R delta

Std dev

Number of constants

m-JC m-ZA m-Arr KHL FB

11.1534 6.48 2.9982 8.0883 5.7164

5 7 10 6 11

0.9482 0.9845 0.9918 0.9468 0.9417

42.1335 7.6885 3.5558 19.2278 9.7609

125

Fractography analysis and constitutive modeling

Table 5.13 Statistical parameters for R45. R delta

Std dev

Number of constants

m-JC m-ZA m-Arr KHL FB

8.7587 7.2263 4.6525 10.3916 5.7645

5 7 10 6 11

Table 5.14 Statistical parameters for R90. R delta

Std dev

Number of constants

m-JC m-ZA m-Arr KHL FB

12.5758 5.9207 3.4928 9.8530 5.4784

5 7 10 6 11

0.9035 0.9801 0.9851 0.9644 0.9557

0.9327 0.9875 0.9896 0.9994 0.9416

56.1166 6.6652 5.7234 14.3853 9.0744

34.2088 6.5876 4.4314 22.7029 8.9464

Figure 5.16 The experimental and predicted correlation coefficient values in direction of R45 for models (A) m-JC, (B) m-ZA, (C) m-Arr, (D) FB, and (E) KHL.

126

A. Anitha Lakshmi et al.

Figure 5.17 The experimental and predicted correlation coefficient values in direction of R90 for models (A) m-JC, (B) m-ZA, (C) m-Arr, (D) FB, and (E) KHL.

taking into account the average absolute error (all) and its standard deviation (S), m-Arr. Forecasting the system is more reliable than forecasting the ZA method. In addition, the prediction of JC model and m-FB model is not suitable for the prediction of ASS 304 flow stress in the hot forming region. Based on the discussion above, m-ZA constitutive model best predicts ASS 304 flow stress behavior in the superplastic region.

Fractography analysis and constitutive modeling

127

5.12 Conclusion The current study involves the analysis of microstructure, fracture, and the design of constitutive models to predict ASS 304 alloy flow stress. A comparative study was conducted to evaluate the efficiency of the model m-JC, the model m-Arr., the model m-ZA, the model FB and the model KHL to predict flow stress behavior at a temperature range of 700 C
900 C at 1024, 1023, and 1022 s21 strain rates. The key findings of this chapter are: The surface of the tensile fractography exposed at the macroscopic level are equally rough transgranular area and a strong population of microvoids and narrow dimples of different size and shape. In the fracture layer, which suggests ductile fracturing, the forming of huge number of tiny shoe-shaped and volume pits and microvoids is examined. Results of the observation and fractography show that the ductility of tensile specimens is more parallel and perpendicular to the direction of rolling. In the three R0, R45, and R90 rolling directions, m-JC model predictions have more nonconformity from the experimental results and less relationship among all other models. Hence m-JC model is least model suitable for estimation of flow behavior of flow stress curve of ASS 304 alloy at hot working temperatures. All the assumed constitutive models demonstrate very good agreement with high amount of fitness experimental results. They were constructed on the combination of statistical measurements values, number of constants used, physical facets assumed, and deducing difficult. Hence by concluding it can be said that physical model m-ZA is the utmost ideal model among available models for predicting flow behavior of ASS 304 alloy flow stress at hot working temperatures. Future work involves formability study of ASS 304 by integrating the models in FEM simulation of stretching process.

Acknowledgment Authors would like to acknowledge the utilization of SEM equipment under FIST grant File No: SR/FST/College-029/2017.

References [1] Singh N, Singh S. A review: properties and applications of different grades of austenitic stainless steels and the effect of various factors on the tensile behavior of these steels. Int J Sci Res Manag (IJSRM) 2015;3(11):3665
73.

128

A. Anitha Lakshmi et al.

[2] Gupta AK, Krishnamurthy N, Singh Y, Prasad KM, Singh SK. Development of constitutive models for dynamic strain aging regime in Austenitic stainless steel 304. Mater Des 2013;45:616
27. [3] Singh SK, Mahesh K, Gupta AK. Prediction of mechanical properties of extra deep drawn steel in blue brittle region using artificial neural network. Mater Des 2010;31 (5):2288
95. [4] Gupta AK, Singh SK, Reddy S, Hariharan G. Prediction of flow stress in dynamic strain aging regime of austenitic stainless steel 316 using artificial neural network. Mater Des 2012;35:589
95. [5] Fields DS, Bachofen WA. Determination of strain hardening characteristics by torsion testing. ASTM Proc Am Soc Test Mater 1957;57:1259
72. [6] Cheng YQ, Zhang H, Chen ZH, Xian KF. Flow stress equation of AZ31 magnesium alloy sheet during warm tensile deformation. J Mater Process Technol 2008;208:29
44. [7] Lennon AM, Ramesh KT. The influence of crystal structure on the dynamic behavior of materials at high temperatures. Int J Plasticity 2004;20:269
90. [8] Khan AS, Huang S. Experimental and theoretical study of mechanical behavior of 1100 aluminum in the strain rate range 10 2 5
104 s 2 1. Int J Plasticity 1992;8:397
424. [9] Jonas JJ, Sellars CM, McTegart WJ. Strength and structure under hot-working conditions. Int Metall Rev 1969;14:1
24. [10] Lakshmi AA, Rao CS. Tanya Buddi, Prediction of Superplasticity of Austenitic Stainless Steel-304 at Hot Working Temperatures. Materials Today: Proceedings 2019;18:2814
22. [11] Haq AU, Kavit AK, Rao T, Buddi T, Baloji D, Satyanarayana K, Singh SK. Evaluation and optimization of material properties of ASS 316L at elevated temperatures using Response Surface Methodology. Materials Today: Proceedings 2019;18: 4589
97. [12] Harshini D, ul Haq A, Buddi T, Kumar KA, Lakshmi AA. Comparative study on mechanical behavior of ASS 316L for low and high temperature applications. Materials Today: Proceedings 2019;19:767
71. [13] Khan AS, Liang RQ. Behaviors of three BCC metals during non-proportional multi-axial loadings: experiments and modeling. Int J Plasticity 2000;16:1443
58. [14] Dieter George E. Mechanical metallurgy. In: Metric SI, editor. Materials science and engineering. McGraw-Hill; 2000. p. 295
6. [15] Khaleel MA, Johnson KI, Lavender CA, Smith MT, Hamilton CH. Specimen geometry effect on the accuracy of constitutive relation in a superplastic 5083 aluminum alloy. Scr Mater 1996;34(9):1417
23. [16] Kotkunde N, Krishnamurthy HN, Puranik P, Gupta AK, Singh SK. Microstructure study and constitutive modeling of Ti
6Al
4V alloy at elevated temperatures. Mater Des 2014;54:96
103. [17] Kosaraju S, Singh SK, Buddi T, Kalluri A, Ul Haq A. Evaluation and Characterization of ASS316L at sub-zero temperature. Advances in Materials and Processing Technologies 2020;1
11. [18] Gupta AK, Krishnamurthy HN, Puranik P, Singh SK, Balu A. An exponential strain dependent Rusinek
Klepaczko model for flow stress prediction in austenitic stainless steel 304 at elevated temperatures. J Mater Res Technol 2014;3(4):370
7. [19] A. Anitha Lakshmi, Ch. Srinivasa Rao, M. Srikanth, K. Faisal, K. Fayaz, Dr. Puspalatha, Swadesh Kumar Singh. Prediction of mechanical properties of ASS 304 in super plastic region using artificial neural networks, Materials today: proceedings 5 (2):3704-3712.

Fractography analysis and constitutive modeling

129

[20] Dharavath B, ul Haq A, Buddi T, Singh SK, Naik MT. Comparative study of ASS 316L on formability at room temperature and super plastic region. Advances in Materials and Processing Technologies 2020;1
12. [21] Xiao Y-H, Guo C. Constitutive modelling for high temperature behavior of 1Cr12Ni3Mo2VNbN martensitic steel. Mater Sci Eng: A 2011;528:5081
7. [22] Cai J, Li F, Liu T, Chen B, He M. Constitutive equations for elevated temperature flow stress of Ti
6Al
4V alloy considering the effect of strain. Mater Des 2011;32:1144
51. [23] N. Kotkunde, A.D. Deole, A.K. Gupta, S.K. Singh, Comparative study of constitutive modeling for Ti
6Al
4V alloy at low strain rates and elevated temperatures, Materials & Design 55, 999-1005. [24] Lin YC, Chen X-M, Liu G. A modified Johnson-Cook model for tensilebehaviors of typical high-strength lloy steel. Mater Sci Eng: A 2010;527:6980
6. [25] Zener C, Hollomon JH. Effect of strain rate upon plastic flow of steel. J Appl Phys 1943;15:15
22. [26] Rusinek A, Rodríguez-Martínez JA, Arias A. A thermo-viscoplastic constitutive model for FCC metals with application to OFHC copper. Int J Mech Sci 2010;52:120
35. [27] Rajesh KVD, Buddi T, Kanth PR, Satyanarayana K. Microstructural and corrosion resistance study on plasma arc welded joints of AISI 304 and AISI 316. Advances in Materials and Processing Technologies 2020;1
17. [28] Anitha Lakshmi A, Srinivasa Rao Ch, ul haq A, Kotkunde N, Subbiah R, Kumar Singh S. Forming Limit Diagram Of AISI 304 Austenitic Stainless Steel At Elevated Temperature: Experimentation And Modelling. International Journal of Mechanical Engineering and Technology (IJMET) 2018;9(12):403
7. [29] Lu J. Microstructure evolution in 304L stainless steel subjected to hot torsion at elevated temperature Brigham Young University BYU Scholars archive. Metal Ital 2015;11/12:19
28.

CHAPTER SIX

Laser transmission welding of dissimilar plastics: analyses of parametric effects and process optimization using grey-based Taguchi method Bappa Acherjee Department of Production Engineering, Birla Institute of Technology, Ranchi, India

6.1 Introduction Laser transmission welding process, due to its distinctive process benefits, has been steadily developed and extensively used in multiple engineering applications. Laser transmission welding is used in a wide variety of applications in automotive, aerospace, biomedical, electrical, electronic, packaging industries, etc. [1,2]. The laser transmission welding process is noncontact, noncontaminating, and flexible. This process produces highquality weld joints with narrow and localized heat affected zone, imposing minimal mechanical and thermal stresses to the welded part [3]. In the laser transmission welding, a laser transparent and a laser absorbent plastic part is joined together. A laser beam targeted on the overlapping thermoplastic parts, passes through the top transparent plastic part and is absorbed near to the interface between the two mating parts by the laser absorbing bottom plastic part. The laser absorbing bottom plastic part usually contains laser absorbing additives or pigments such as carbon black which transform the laser energy into heat [4]. The heat thus produced is dissipated owing to thermal conduction to the deeper layer of the bottom part and neighboring layers of the top transparent part. A thin layer of plastic in both parts starts to melt when heated to a temperature above the melting point or melting

Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00006-3

© 2020 Elsevier Ltd. All rights reserved.

131

132

Bappa Acherjee

range. Molecular diffusion happens at the molten interface and a weld forms after cooling [5,6]. The functionality of the laser transmission welding process is highly dependent on proper evaluation of the optical and physical characteristics of plastics. The optical and physical properties of plastics rely on polymer structure, colorants, characteristics of constituents, prewelding condition of plastics, etc. [7,8]. Reflection, transmission, and absorption of laser energy during laser transmission welding depends on the composition of the polymer matrix [9]. Carbon black and titanium oxide, respectively, are the most commonly used color pigments to produce black and white opaque plastic components [10]. Laser energy requirement is heavily correlated with the absorptive part’s carbon black content [4]. Increasing fiber glass content in plastic matrix improves its tensile strength but reduces the weld strength [10]. With growing fiber glass content, the laser transmission through plastic part reduces as fiberglass tends to scatter light through inner reflection and refraction [11,12]. The maximum weld strength obtained for the carbon fiber reinforced polymer is slightly greater than the unreinforced polymer. However, compared with the unreinforced sample, this needs a considerably higher energy input [1]. The addition of impact modifier in the polymer matrix significantly decreased the transmission of laser [8]. The thickness of the plastic part also affects optical properties, especially for semicrystalline and crystalline materials [1]. Laser transmission in crystalline polymers depends on part thickness because the incoming radiation can be readily scattered in bulk material which reduces the laser energy [13]. During laser transmission welding, laser power, welding speed, and beam spot diameter are the separately controllable welding parameters governing the temperature field in the weld area [14,15]. Clamping pressure is used to keep the workpieces in the correct place and to guarantee intimate contact between the surfaces of the coupling [9]. In this research work, Taguchi method in combination with grey relational analysis is used for optimization of welding parameters for laser transmission welding of acrylic to acrylonitrile butadiene styrene (ABS). The weld qualities namely: weld strength and weld width are optimized simultaneously. Analysis of variance method is used to quantitatively evaluate the importance of the welding parameters on selected weld qualities. The mechanisms for the phenomenon observed during the experimental study are also discussed in addition to parametric optimization.

Laser transmission welding of dissimilar plastics

133

6.2 Grey-based Taguchi method Taguchi method of robust design is a powerful statistical tool where the level of process parameters and experimental plan is so chosen that eliminate variation of the final product quality due to noise factors and promote the quality stability [16]. The experiments are carried out in this method according to a specially designed experimental matrix, known as the orthogonal array [17,18]. The experimental values are used in all experimental runs to calculate the quality loss values for each quality characteristic. Quality loss is a product-related loss because of the deviation in the functionality of the product from its target. The quality loss function can be of several types depending on the nature of the quality characteristics such as lower-the-better, higher-the-better, and nominal-the-best. Further transforms the value of the loss function into a signal-to-noise (S/N) ratio. The “signal” is the desirable value and the “noise” is the undesirable value, and the S/N ratio expresses the dispersion around the desired value. Irrespective of the quality characteristics, the better quality characteristic corresponds to the larger S/N ratio. This is valid only for the optimization of a single quality characteristic. However, higher-thebetter quality of one quality characteristic may influence the product quality during optimizing the multiquality features because another quality characteristic may require lower-the-better feature. Thus, multiquality optimization is much more complicated than single-quality optimization problem. In order to fix this issue, this research implements the grey relational analysis integrated with Taguchi method. A situation between these extremes is regarded grey, representing black as absence of data and white as complete of data, neither of these idealized circumstances ever happening in actual world issues. Instead of trying to discover the best solution, grey analysis offers methods to determine a good solution, a suitable solution to issues in the actual world. The grey relational theory is first proposed by Deng in 1982 [19]. This technique has been shown to be useful in coping with a method that includes poor, incomplete, and uncertain data to address multiobjective optimization problems. The dimensions of variables considered during analysis are generally different in grey relational analysis, and their difference in magnitude is large. The original data are therefore normalized in order to make their magnitude one and dimensionless. Linear normalization of experimental

134

Bappa Acherjee

results is performed in the range of 0 1 for each response, which is called the grey relational generation. For higher-the-better quality features, the normalized results, xij, can be expressed as [20]: xij 5

yij 2 minj yij maxj yij 2 minj yij

(6.1)

For lower-the-better quality features, the normalized results, xij, can be expressed as [20]: maxj yij 2 yij (6.2) xij 5 maxj yij 2 minj yij where, yij is the ith quality feature in the jth experiment. The greater the normalized results, the better is the quality and the best-normalized result should be 1. Next, to express the relationship between the ideal and actual normalized results, grey relational coefficients are calculated. It is possible to express the grey relational coefficient, ξij, as [21]:



mini minj
x0 i 2 xij
1 ζmaxi maxj
x0 i 2 xij




(6.3) ξ ij 5
x0 i 2 xij
1 ζmaxi maxj
x0 i 2 xij
where, x0i is the ideal normalized result for the ith quality feature, that is the best normalized result 5 1. ζA [0,1] is a distinguishing coefficient, incorporated in equation to weaken the effect of maximaxj|xi0 xij| when it becomes too large and thereby broaden the significance of the relational coefficient. It is generally set to 0.5 if all parameters of the process are weighted equally [19]. Then, by weighted averaging the grey relational coefficient corresponding to each quality characteristic, the grey relational grades are calculated. The overall assessment of the of multiple quality characteristics is carried out based on the grey relational grade, which is calculated as [21]: γj 5

m 1X wi ξij m i51

(6.4)

where, γj is the grey relational grade for the jth experiment, wi is the weight factor for the ith quality characteristic, and m is the number of quality characteristics. The level with the highest grey relational grade is the optimal level of the process parameters. Grey relational analysis transforms the complicated multicriteria optimization problem into a single grey relational grade optimization, thus, simplifying the optimization process.

Laser transmission welding of dissimilar plastics

135

6.3 Experimental work Work materials used in this research work are transparent acrylic (polymethyl methacrylate) and laser absorbing ABS plastic plaques. The dimension of each plaque is 80 mm 3 35 mm 3 4 mm. ABS plaques are made to absorb laser by adding carbon black to the polymer matrix by 0.1% weight. A Coherent diode laser system includes an integrated fiber array laser diode bar mounted on an air-cooled sink with all required drive and control electronics is used for experimental work. The laser system has a maximum optical power of 30 W and operates at a wavelength of 809.40 nm. The workpieces are moved by mounting them on a CNC X Y table which is connected to computer interface via a motion control system. The stand-off distance between the laser optics and the workpiece surface is regulated by using the Z-axis motor driven carriage. In the clamp pressure system used in this study, a 50 mm stroke length 2-ton hydraulic jack with a manual hydraulic pump and a jack holder is used. On the top plate in the center of the hydraulic jack holder, a slot of appropriate sizes is sliced to offer the laser light a passage. For repetitive work, a welding fixture is designed to keep the lapping area constant for each run and to avoid misalignment between the welding parts. Fig. 6.1 is a picture of laser welding setup used for the experimental works.

Figure 6.1 Laser welding setup used for the experimental works.

136

Bappa Acherjee

Four distinctly controllable process parameters considered as input parameters, for conducting the experiments, are laser power, welding speed, stand-off distance, and clamp pressure. Trial experiments are performed by varying one parameter at a time while maintaining a constant value for the rest of the parameters to select the parameter range. Working range is decided by visual inspection of weld seam for a smooth appearance and lack of any noticeable defects. Table 6.1 shows the process parameters chosen and their levels, units, and notations. Taguchi method for four-level four-factors is used to implement the orthogonal array experiment scheme. A Taguchi L16 orthogonal array is used in this work and experiments are carried out according to the composition of the orthogonal array. Fig. 6.2 shows a PMMA-ABS sample in lap joint configuration which is welded using laser transmission welding process. The weld quality measured using two important weld quality characteristics namely: weld strength and weld width. Weld strength of the welded Table 6.1 Selected process parameters and their levels, units, and notations. Notation Parameter Level

A B C D

Power (W) Welding speed (mm/s) Stand-off distance (mm) Clamp pressure (MPa)

1

2

3

4

12 7 32 1.5

14 10 36 1.9

16 13 40 2.3

18 16 44 2.7

Figure 6.2 Laser transmission welded PMMA-ABS sample.

137

Laser transmission welding of dissimilar plastics

Table 6.2 Experimental array with measured results of weld strength and weld width. Experiment Welding parameters Weld Weld no. strength width (N/mm) (mm) A (W) B (mm/s) C (mm) D (MPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4

1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

1 2 3 4 2 1 4 3 3 4 1 2 4 3 2 1

1 2 3 4 3 4 1 2 4 3 2 1 2 1 4 3

34.88 57.33 60.81 45.32 52.10 41.19 55.28 57.19 62.67 69.47 45.71 57.14 77.10 72.87 55.91 44.47

3.27 3.67 3.74 3.46 4.16 3.26 4.02 3.66 4.90 4.83 3.23 3.56 5.32 4.51 3.93 3.25

specimens are determined using lap-shear pull test. For the lap-shear pull test of welded samples, a microprocessor controlled Instron universal testing machine is used. The weld strength is evaluated as the maximum load to failure per unit weld length (N/mm). For measuring weld seam widths, an Olympus STM 6 measuring microscope with submicron accuracy is used. At least three weld width measurements are taken at distinct locations along the weld line, and by averaging these three readings, the average weld width (mm) is calculated. Table 6.2 presents the experimental array with experimental results of weld strength and weld width for all experimental runs on average of the three replications.

6.4 Parametric analysis The effects of different process parameters on weld strength and weld width are plotted in Figs. 6.3 and 6.4, respectively. It is seen from Fig. 6.3 that weld strength improves with laser power. Increasing laser power increases the intensity of the laser beam and thus melts more quantity of

138

Bappa Acherjee

Main effects plot for means Data means A

65

B

C

D

Mean of means

60

55

50

45

40 1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

3

4

Figure 6.3 Main effects plots of welding parameters on weld strength.

Main effects plot for means Data means A

B

C

D

4.4

Mean of means

4.2 4.0 3.8 3.6 3.4 3.2 1

2

3

4

1

2

3

4

1

2

3

4

1

2

Figure 6.4 Main effects plots of welding parameters on weld width.

material, which in turn improves the strength of the weld by increasing the weld seam dimensions. It is observed from Fig. 6.3 that with welding speed and stand-off distance, the weld strength rises to a certain value and then begins to decrease. Increasing welding speed resulting in decreased laser

139

Laser transmission welding of dissimilar plastics

material interaction time, which lowered heat input to the weld area and thereby the weld strength. Stand-off distance controls the laser beam spot area and thereby power density. The weld strength is limited at very highpower density, resulting in decomposition of the material and the lack of fusion resulting in a very small power density. Increasing clamping pressure promotes contact conduction and the flow of molten material in the weld zone, thereby increasing strength, as shown in Fig. 6.3. However, some of the molten material may be expelled at the ends at very elevated clamp pressure from the opening of the weld line, which may result in reduced strength. It is evident from Fig. 6.4 that weld width increases with laser power and stand-off distance and decreases with an increase in welding speed. Increasing laser power ensures more heat input at weld zone causing wider weld pool, resulting in increase in weld width. An increase in welding speed leads to a decrease in interaction time with heat source, resulting in narrow weld. Increasing stand-off distance widens the area of the beam spot and therefore the heat is applied to a wider region, increasing the weld width. Clamp pressure shows a positive trend for weld width up to first three levels as shown in Fig. 6.4, thereafter affects adversely. The clamp pressure effect on weld width, however, is found to be marginal. The analysis of variance (ANOVA) is used to assess the error variance and to determine the significant process parameters. Using statistical software, MINITAB 17, the findings of ANOVA provided in Tables 6.3 and 6.4 are obtained. Fisher’s ratio (F-value) is used in ANOVA to determine whether the parameter affects the selected weld quality significantly. The associated P-value of less than .05 indicates that the parameters at a confidence level of 95% are statistically significant [3]. According to the results of ANOVA given in Table 6.3, stand-off distance has a leading effect on total variation in weld strength, followed by laser power, welding speed, and clamp pressure. From the results of ANOVA furnished in Table 6.4, it is observed that stand-off distance has the leading effect resulting in the Table 6.3 Analysis of variance for weld strength. Sources Sum of squares Degrees of freedom Mean squares F-value P-value

A B C D Error Total

448.87 178.96 1184.02 136.83 66.01 2014.68

3 3 3 3 3 15

149.62 59.65 394.67 45.61 22.00

6.80 2.71 17.94 2.07

.075 .217 .020 .282

140

Bappa Acherjee

Table 6.4 Analysis of variance for weld width. Sources Sum of squares Degrees of freedom Mean squares F-value P-value

A B C D Error Total

1.2955 1.9671 3.0843 0.0622 0.0419 6.4509

3 3 3 3 3 15

0.4318 0.6557 1.0281 0.0207 0.0140

30.94 46.98 73.67 1.48

.009 .005 .003 .377

variation of the source for weld width followed by welding speed, laser power, and clamp pressure.

6.5 Multiobjective optimization Grey relational analysis is implemented to convert the multiquality attributes into a single performance index, and then optimal parametric combination to maximize that single performance index is determined using Taguchi method. The normalization of experimental results is performed first to achieve consistency between results of different responses by converting them to dimensionless quantity of order one. Weld strength is characterized by higher-the-better quality, and weld width is characterized by lower-thebetter quality. The experimental results are normalized using Eqs. (6.1) and (6.2), respectively, for the higher-the-better and lower-the-better quality characteristics and the normalized results are furnished in Table 6.5. The higher the normalized results, the better the weld quality and the best normalized results should be 1. For each experimental run of the Taguchi orthogonal array presented in Table 6.5, the grey relational coefficients are calculated using Eq. (6.3). In this research, for calculating the grey relational coefficients, the value of ζ is taken as 0.5. The grey relational grades corresponding to each experimental run are calculated using Eq. (6.4) and are summarized in Table 6.5. The weight ratio of both the quality features is set as 1:1 in calculating the grey relational grades, that is, each feature is of equal significance or comparative weight. The greater the grey relational grade, the better is the overall quality features (i.e., the best compromise between the conflicting quality characteristics). Exp. no. 11 has among the 16 studies the best overall quality features, in this work, because it matches to the highest value of grey relational grade.

141

Laser transmission welding of dissimilar plastics

Table 6.5 Results of grey-based Taguchi analysis. Exp. Normalized data Grey relational no. coefficient

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Weld strength

Weld width

Weld strength

Weld width

0.000 0.532 0.614 0.247 0.408 0.149 0.483 0.528 0.658 0.819 0.257 0.527 1.000 0.900 0.498 0.227

0.981 0.789 0.756 0.890 0.555 0.986 0.622 0.794 0.201 0.234 1.000 0.842 0.000 0.388 0.665 0.990

0.333 0.516 0.564 0.399 0.458 0.370 0.492 0.515 0.594 0.735 0.402 0.514 1.000 0.833 0.499 0.393

0.963 0.704 0.672 0.820 0.529 0.972 0.569 0.708 0.385 0.395 1.000 0.760 0.333 0.449 0.599 0.981

Grey relational grade

Order

0.648 0.610 0.618 0.609 0.493 0.671 0.531 0.612 0.489 0.565 0.701 0.637 0.667 0.641 0.549 0.687

5 10 8 11 15 4 14 9 16 12 1 7 3 6 13 2

Because the experimental design is orthogonal, the influence of each welding parameter on the grey relational grade can be segregated at different levels. The mean grey relational grades for laser power, welding speed, stand-off distance, and clamp pressure are calculated for the respective levels and summarized in Table 6.6. The optimal parametric setting can be determined from the data presented in Table 6.6. The parametric level with highest grey relational grade for each of the process parameters are the optimal condition for respective parameters to maximize the overall quality feature, that is, grey relational grade. According to the response table for grey relational grade, the optimal setting of welding parameters is to keep laser power at first level (A 5 12 W), welding speed at third level (B 5 13 mm/s), stand-off distance at second level (C 5 36 mm), and clamp pressure at fourth level (D 5 2.7 MPa) to maximize welding strength and simultaneously minimize welding width. After choosing the optimum setting of the welding parameters, the final step is to use the optimum parameter setting to verify the improvement of the quality characteristics. A confirmation experiment is conducted by performing a test with optimum setting of welding parameters and the result is tallied with the prior best experimental result of Exp. no. 11 (i.e., order

142

Bappa Acherjee

Table 6.6 Response table for grey relational grade. Welding parameters Grey relational grade

Power, A Welding speed, B Stand-off distance, C Clamp pressure, D

Level 1

Level 2

Level 3

Level 4

Delta

Rank

0.6360 0.5745 0.5724 0.6143

0.5767 0.6218 0.6769 0.5797

0.5981 0.6362 0.5901 0.5909

0.6215 0.5997 0.5929 0.6473

0.0593 0.0618 0.1045 0.0676

4 3 1 2

Table 6.7 Confirmation test results. Initial parameter setting (Order 15)

Initial best parameter setting (Order 1)

Level A2B1C2D3 A3B3C1D2 Weld strength (N/mm) 52.10 45.71 Weld width (mm) 4.16 3.23 Grey relational grade 0.493 0.701 Improvement of the grey relational grade 5 0.224

Optimal parameters setting (by grey-based Taguchi method)

A1B3C2D4 62.74 3.43 0.717

ranking 1), and an arbitrarily chosen experimental run, Exp. no. 5 (order ranking 15). Table 6.7 presents the outcomes of the confirmation test. Improvement of the overall quality feature, grey relational grade, is found to be 0.224 (31.95%) at the optimum levels of parameter settings when both the responses are enhanced. The overall quality feature is improved by 0.016 (2.28%) at optimum levels of parameter settings when compared with the experimentally determined best parametric condition.

6.6 Conclusion In this study, the Taguchi technique in conjunction with grey relational analysis is used to optimize welding parameters for laser transmission welding of acrylic to ABS. Weld strength and weld width are regarded as yield welding characteristics, which are optimized at the same time. To explore the impact of welding parameters on weld characteristics, parametric trend analysis is also conducted. Weld strength and weld width is seen to improve with laser power. It is observed that the weld strength

Laser transmission welding of dissimilar plastics

143

increases to a certain value with welding speed and stand-off distance and then starts to decline. This phenomenon is related to the limiting value of power densities between lack of fusion and decomposition of material. With stand-off distance it is noticed that weld width rises, and it reduces with a rise in welding speed. However, the impact of clamp pressure on both the weld qualities is found to be marginal. Stand-off distance has a major impact on complete weld strength variation, followed by laser power, welding speed, and clamp pressure. The effect of stand-off distance is the main source of variation of weld width followed by the welding speed, laser power, and clamp pressure. Compared with the initial best parametric situation, the overall quality function is enhanced at optimum setting of welding parameters acquired by grey-based Taguchi technique.

References [1] Berger S, Oefele F, Schmidt M. Laser transmission welding of carbon fiber reinforced thermoplastic using filler material - a fundamental study. J Laser Appl 2015;27: S29009. [2] Wippo V, Rettschlag K, Surjoseputro W, Jaeschke P, Suttmann O, Ziegmann G, et al. Laser transmission welding of semi-interpenetrating polymer networkscomposites. J Laser Appl 2017;29:S022407. [3] Acherjee B, Kuar AS, Mitra S, Misra D. Empirical modeling and multi-response optimization of laser transmission welding of polycarbonate to ABS. Lasers Manuf Mater Process 2015;2(3):103 23. [4] Acherjee B, Kuar AS, Mitra S, Misra D. Effect of carbon black on temperature field and weld profile during laser transmission welding of polymers: a FEM study. Opt Laser Technol 2012;44(3):514 21. [5] Russek UA, Aden M Pöhler J. Laser beam welding of thermoplastics experiments, thermal modelling and predictions. In: Proceedings of the 3rd international WLT conference on lasers in manufacturing, Munich, Germany; 2005. p. 85 89. [6] Acherjee B, Kuar AS, Mitra S, Misra D. Laser transmission welding of polycarbonates: experiments, modeling, and sensitivity analysis. Int J Adv Manuf Technol 2015;78(5-8):853 61. [7] Acherjee B, Kuar AS, Mitra S, Misra D. Finite element simulation of laser transmission thermoplastic welding of circular contour using a moving heat source. Int J Mechatron Manuf Syst 2013;6(5/6):437 54. [8] Kagan VA, Bray RG, Kuhn WP. Laser transmission welding of semi-crystalline thermoplastics: part I: Optical characterization of nylon-based plastics. J Reinf Plast Compos 2002;21(12):1101 22. [9] Baylis B. Welding thermoplastic elastomers to polypropylene with a diode laser. In: Proceedings of the 21st international congress on applications of lasers & electrooptics, Scottsdale, Arizona; 2002. [10] Kagan VA, Chambers A, Bray R. Forward to better understanding of optical characterization and development of colored polyamides for the infra-red/laser welding, part II Family of colored polyamides. J Reinf Plast Compos 2003;22(7):593 603. [11] Grewell D, Rooney P, Kagan VA. Relationship between optical properties and optimized processing parameters for through-transmission laser welding of thermoplastics. J Reinf Plast Compos 2004;23(3):239 47.

144

Bappa Acherjee

[12] Jaeschke P, Wippo V, Suttmann O, Overmeyer L. Advanced laser welding of highperformance thermoplastic composites. J Laser Appl 2015;27:S29004. [13] Bachmann FG, Russek UA. Laser welding of polymers using high power diode lasers. Proc SPIE 2002;4637:505 18. [14] Abed S, Laurens P, Carrétéro C, Deschamps JR, Duval C. Diode laser welding of polymers: microstructures of the welded zones for polypropylene. In: Proceedings of the 20th international congress on applications of lasers & electro-optics, Jacksonville, Florida, LMP Section G, Paper P527; 2001. [15] Lakemeyer P, Schöppner V. Simulation-based investigation on the temperature influence in laser transmission welding of thermoplastics. Weld World 2019;63(2):221 8. [16] Acherjee B, Kuar AS, Mitra S, Misra D. A sequentially integrated multi-criteria optimization approach applied to laser transmission weld quality enhancement—a case study. Int J Adv Manuf Technol 2013;65(5-8):641 50. [17] Phadke MS. Quality engineering using robust design. Englewood Cliffs, NJ: Prentice-Hall; 1989. [18] Ross PJ. Taguchi technique for quality engineering. New York: McGraw-Hill; 1998. [19] Deng JL. Control problems of grey systems. Syst Control Lett 1982;5:288 94. [20] Çayda¸s U, Hasçalık A. Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristic. Opt Laser Technol 2008;40:987 94. [21] Hsiao YF, Tarng YS, Huang WJ. Optimization of plasma arc welding parameters by using the Taguchi method with the grey relational analysis. Mater Manuf Process 2008;23(1):51 8.

CHAPTER SEVEN

Investigations on effect of thickness and rolling direction of thin metal foil on forming limit curves in microforming process Gyan Patel and Ganesh Kakandikar School of Mechanical Engineering, Dr. V. D. Karad MIT World Peace University, Pune, India

7.1 Microforming Sheet metal forming is a process in which punch force is applied to sheet metal to change its geometry/profile rather than removal of any material. Hattalli and Srivatsa [1] defined metal forming as a process in which either the sheet is bent, stretched, or formed into desired complicated shapes. Many defects like tearing, wrinkling, and necking are observed in sheet metal forming. Surface strain measurement is required to know the thickness strain and in turn different ductile damage criteria. Razali and Qin [2] worked on recent developments in forming, which includes submillimeter sized parts termed as microforming. Razali and other researchers explicitly discussed various issues related to micromanufacturing and microforming. For microforming different setup is required, which is normally used with universal testing machines. The physics of process completely changes when moved from macro- to microlevel, so the failure criteria also. Microforming requires more precision equipment’s as compared with process at macrolevel. Razali et al. [3] developed high precision feeder for microsheet forming, without use of any mechanical transmission. Design was arrived at by performing motion analysis and feeding simulations. Greater feeding accuracy and repeatability was achieved, which was challenging task at 5% 15% of the strip thickness. Saotome et al. [4] experimented on microdeep drawability of steel sheet for different thickness, with indigenously designed and developed setup. They used relative punch diameter as important parameter in Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00007-5

© 2020 Elsevier Ltd. All rights reserved.

145

146

Gyan Patel and Ganesh Kakandikar

investigations ranging from 10 to 100. Ordinary drawability was obtained for very thin sheet steels without a large amount of blank holder pressure. Zaid [5] reviewed different defects and mechanism to prevent them in drawing process. These include radial clearance percentage, punch, and die profile radii. The maximum drawing force decreases with increase of the die profile radius and increases by increase of the punch profile radius was outcome of experiments. The same insights are helpful for design of microforming system. Agrawal et al. [6] studied parameters affecting wrinkling in drawing process and also prediction of minimum blank holding force for same. Methodology is based on a combination of upper bound and energy approaches. Predicted wrinkling tendency seems to be reasonably accurate considering the geometrical and process constraints. Forming limit diagram (FLD) is an important tool for sheet metal forming analysis. It represents graphical combination of major strain and minor strain for all circles in circle grid analysis or elements in numerical simulations. These strains can be measured by surface strain measurement. There are many approaches for plotting FLD as experimental, numerical, and analytical. Ahmadi et al. [7] researched on FLDs. The effect of different parameters like the work-hardening exponent (n), and the plastic strain ratio (r), on these diagrams have been evaluated and simulated using ABAQUS/ Standard for Low Carbon and Ultra Low Carbon steels. Ramzia et al. [8] plotted FLDs numerically for copper thin sheets using the threedimensional (3D) simulations of the micro-Marciniak tests. Microforming limit curves in terms of strains and stresses are plotted in the major/minor strain space, respectively. They also investigated the effect of the initial grain size on the forming limit curves. In literature mainly two experimental approaches have been widely used by researchers, Marciniak test (flat punch test) and Nakajima test (hemispherical punch test). Dabade and Shinge [9] plotted FLDs for mild carbon steel using hemispherical punch test. The die and punch are made up of High Carbon High Chromium Steel. Bhargava et al. [10] also plotted FLD for AA5182 aluminum alloy. The formability of aluminum is low as compared with automotive steel. Still it is one of the promising material to be applied in automotive due to light weight. It has been found that effect of mesh size is prominent in simulation experiments. Bhargava et al. [11] plotted FLD for advanced high strength steels (AHSS) using strain path diagram. AHSS is a promising material for automotive applications due to its high strength-to-weight ratio compared with other steels. They proposed new strain localization criterion to predict FLD, which is well in agreement

Investigations on effect of thickness and rolling direction of thin metal foil on forming

147

with experimental results. These criteria can be applied to microforming with proper verification of material behavior. But generating FLD for microthin sheet is more complicated, it requires more precision. Literature reveals that, there has been few researchers, who contributed in this area. Sudarsana et al. [12] developed FLD for 200 µm thin steel sheet, and also discussed effect of circular grid size, sheet orientation, punch size, and deformation speed. Subsize limiting dome height (LDH) test setup was developed to deform rectangular specimens of different widths using a 30 mm hemispherical punch. It was found that punch diameter marginally affects limiting strains. Similarly Sahu and Mishra [13] developed FLD for 30, 50, and 90 µm thin brass sheets using LDH test. The test was carried for both as-received and annealed specimen. Mechanical behavior is influenced on part miniaturized during both tensile and LDH tests. Dore et al. [14] used commercial software ABAQUS for FEM forming simulation of dome test to estimate the maximum punch force needed for successful testing. A force and position sensors are integrated in the design as instrumentation to measure the force and dome height at different stages of deformation. Although few efforts have been put there is lot of things needed to be explored in microforming. The research work presents FLDs developed using hemispherical punch test according to ASTM-2218-14 test. Uniaxial, plane, and biaxial strain specimens are used in the test. Experimental setup has been designed and developed for microdeep drawing. Limiting dome height tests were performed on 40 and 90 µm thin brass sheets for three different rolling directions (0, 45, and 90 degrees). The effect of thickness as well as rolling direction on FLDs has been discussed in the results.

7.2 Experimental investigations 7.2.1 Limiting dome height test—specimen For generating forming limit curve mainly three strain points are required: uniaxial strain, plane strain, and biaxial strain. Three different specimen needs to be designed for these three strain paths. Geometry and dimensions of these specimens is shown in Fig. 7.1. Surface strain measurement is required to measure the major and minor strain at any point on

148

Gyan Patel and Ganesh Kakandikar

Figure 7.1 Specimen for uniaxial, plane, and biaxial strain path.

specimen. Circular grid is required on foil for surface strain measurement as shown in below. So, three specimens for uniaxial, plane, and biaxial strain paths having dimension of 25 mm 3 50 mm, 40 mm 3 50 mm, and 50 mm 3 50 mm along with 1-mm diameter circular dot with center distance of 2 mm. Electric discharge machine wire-cut and screen printing is simultaneously used for cutting of specimen and generating circular grid on foil.

7.2.2 Experimental setup The experimental setup was designed and developed for microdeep drawing process. The setup for limit dome height test has punch with diameter of 15 mm and die diameter of 16 mm. The material used was mild steel. The setup has closed die arrangement, with internal blank holder to ensure controlled flow of material into die as shown in Fig. 7.2. Fluid film lubrication has been applied at all interfaces of die, punch, and workpiece to ensure friction coefficient below 0.10. This tool setup was used with universal testing machine FSA M100. All experiments were performed at 2.5 mm/min cross head speed.

7.2.3 Surface strain measurement During experimentation, when the dome shapes for different strain paths were manufactured in standard cupping test, it is observed that localized necking is initiated in all cases. Circular dots on brass sheet are converted into ellipse at necking points, as shown in Fig. 7.3. Length of major and minor axis is used to measure surface strains and in turn thickness strain. From these measurements percentage true strains were calculated. Optical microscope was used to measure minor and major axis of ellipse. The record of measured strains for two different thicknesses of foils 40 and 90 µm and for every foil strain in different rolling directions is presented in Table 7.1.

Investigations on effect of thickness and rolling direction of thin metal foil on forming

149

Figure 7.2 Experimental setup of limiting dome height test.

FLC-0° 0.5 0.4 0.3 0.2 0.1 –0.2

–0.1

0

0

0.1

0.2

Figure 7.3 FLD for 40 µm thickness and 0-degree rolling direction.

7.2.4 Forming limit diagrams Forming limit curves are plotted by using measured strain values from experimentation. Fig. 7.3 represents FLD for 40 µm and 0-degree rolling direction. Fig. 7.4 represents FLD for 40 µm and 45-degree rolling direction and Fig. 7.5 represents FLD for 40 µm and 90-degree rolling direction. It is evident from the records that for the plane strain path, minor strain slightly deviates from expected value and turns to be 0.015, 0.013, and 0.018 for 0-, 45-, and 90-degree rolling direction, respectively. For 45-degree rolling direction, it is quite nearer to expected value than other two cases. Major strain is maximum for 0-degree rolling direction and minimum for 90-degree rolling direction. Similarly forming limit

150

Gyan Patel and Ganesh Kakandikar

Table 7.1 Measured strains for different thicknesses and rolling directions. Thickness Rolling direction Specimen Major strain Minor strain

40 µm

0 degree

45 degrees

90 degrees 90 µm

0 degrees

45 degrees

90 degrees

Uniaxial Plane Biaxial Uniaxial Plane Biaxial Uniaxial Plane Biaxial Uniaxial Plane Biaxial Uniaxial Plane Biaxial Uniaxial Plane Biaxial

0.263 0.210 0.273 0.263 0.176 0.280 0.226 0.128 0.250 0.300 0.230 0.277 0.269 0.190 0.310 0.272 0.152 0.267

2 0.123 0.015 0.170 2 0.103 0.013 0.155 2 0.107 0.018 0.173 2 0.09 0.010 0.157 2 0.091 0.010 0.167 2 0.098 0.02 0.160

FLC-45° 0.3

0.2

0.1

–0.15

0 –0.05

0.05

0.15

Figure 7.4 FLD for 40 µm thickness and 45-degree rolling direction.

curves are plotted for 90 µm thickness for all three rolling directions in Figs. 7.6 7.8. For 90 µm thickness also, for plane strain path major strain is maximum for 0-degree rolling. Direction as 0.16 and reduces to 0.12 for 45 degrees and 0.068 for 90 degrees. Minor strain slightly deviates from expected value for only 90-degree rolling direction.

Investigations on effect of thickness and rolling direction of thin metal foil on forming

151

FLC-90° 0.3

0.2

0.1

–0.2

–0.1

0

0

0.1

0.2

Figure 7.5 FLD for 40 µm thickness and 90-degree rolling direction. FLC-0°

–0.2

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 –0.1 0

0.1

0.2

Figure 7.6 FLD for 90 µm thickness and 0-degree rolling direction. FLC-45° 0.35 0.3 0.25 0.2 0.15 0.1 0.05 –0.2

–0.1

0

0

0.1

0.2

Figure 7.7 FLD for 90 µm thickness and 45-degree rolling direction.

7.2.5 Effect of rolling direction on forming limit curve It is evident that forming limit curves for same thickness of material varies with rolling direction. Figs. 7.9 and 7.10 represent effect of rolling direction on forming limit curves of both thickness materials. For 40 µm thickness forming limit curve for 0 degree is more safety zone as compared with 45- and 90-degree rolling direction. The 90-degree rolling direction

152

Gyan Patel and Ganesh Kakandikar

FLC-90° 0.3 0.25 0.2 0.15 0.1 0.05 –0.2

–0.1

0

0

0.1

0.2

Figure 7.8 FLD for 90 µM thickness and 90-degree rolling direction. FLD-40 µm 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 –0.2 –0.1 0

0 degree 45 degree 90 degree 0.1

0.2

Figure 7.9 Forming limit curves: 40 µm thickness for different rolling directions. FLD-90 µm

–0.2

–0.1

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0

0 Degree 45 degree 90 Degree

0

0.1

0.2

Figure 7.10 Forming limit curves: 90 µm thickness for different rolling directions.

specimen has lowest safety zone. Uniaxial strain point and biaxial strain point have almost same value for 0- and 90-degree rolling direction in both thicknesses. Plane strain point has more variation for different rolling direction for both thicknesses. Same response is seen with 90 µm.

7.2.6 Effect of foil thickness on forming limit curve Comparison of forming limit curves for different thickness with same rolling direction concludes that safe zone increases with increase in thickness of brass

Investigations on effect of thickness and rolling direction of thin metal foil on forming

153

foil. Difference between FLC for both thicknesses is very less because of low thickness difference. For 0-degree rolling direction difference of major strain in plane strain point is 0.020 (2%), similar for 45 degree is 0.013 (1.3%) and 90 degree is 0.024 (2.4%). Difference between FLC for both thicknesses can be referred by difference of plane strain point. So, formability of 90 µm thin brass foil is more than 40 µm thin brass foil (Figs. 7.11 7.13). FLD-0º 0.35 0.3 0.25 0.2

40-micron

0.15

90-micron

0.1 0.05 –0.2

–0.1

0

0

0.1

0.2

Figure 7.11 Comparison of forming limit curves: 40 and 90 µm thickness for 0degree rolling directions. FLD-45º 0.35 0.3 0.25 0.2

40-micron

0.15

90-micron

0.1 0.05 –0.2

0

–0.1

0

0.1

0.2

Figure 7.12 Comparison of forming limit curves: 40 and 90 µm thickness for 45degree rolling directions. FLD-90º 0.3 0.25 0.2 0.15

40-micron

0.1

90-micron

0.05 –0.2 –0.1

0

0

0.1

0.2

Figure 7.13 Comparison of forming limit curves: 40 and 90 µm thickness for 90degree rolling directions.

154

Gyan Patel and Ganesh Kakandikar

7.3 Conclusions The results of experimental investigation performed on thin brass file in microforming to plot forming limit curves can be concluded as • Uniaxial and biaxial strain points are similar for every rolling direction, for both thicknesses of thin brass foil. Plane strain point has more variation as compared with uniaxial and biaxial strain point. • Thin brass foil with 0-degree rolling direction has high safe zone compared with 45- and 90-degree rolling directions. Foil with 90-degree rolling direction has least safe zone. • From FLC of 40 and 90 µm thin brass foil for every rolling direction, 90 µm thin foil has safer zone as compared with 40 µm. • It is concluded that, formability is high for thicker foils and for 0degree rolling direction.

References [1] Hattalli VL, Srivatsa SR. Sheet metal forming processes - recent technological advances. Mater Today Proc 2018;5(1):2564 74. [2] Razali AR, Qin Y. A review on micro-manufacturing, micro-forming and their key issues. Procedia Eng 2013;53:665 72. [3] Razali A, Qin Y, Zhao J, Harrison C, Smith R. Development of a new highprecision feeder for micro-sheet-forming. J Manuf Sci Eng 2011;133(6):061025 1-7. [4] Saotome Y, Yasuda K, Kaga H. Microdeep drawability of very thin sheet steels. J Mater Process Technol 2001;113(1 3):641 7. [5] Zaid AIO. Deep drawing mechanism, parameters, defects and recent results: state of the art. IOP Conf Ser Mater Sci Eng 2016;146(1):1 10. [6] Agrawal A, Reddy NV, Dixit PM. Prediction of wrinkling and determination of minimum blankholding pressure in multistage deep drawing. J Manuf Sci Eng 2011;133(6):061023 1-8. [7] Ahmadi S, Eivani AR, Akbarzadeh A. Experimental and analytical studies on the prediction of forming limit diagrams. Comput Mater Sci 2009;44(4):1252 7. [8] Ramzi BH, Sebastien T, Fabrice R, Gemala H, Pierrick M. Numerical prediction of the forming limit diagrams of thin sheet metal using SPIF tests. Procedia Eng 2017;183:113 18. [9] Dabade UA, Shinge VR. Experimental investigation on forming limit diagram of mild carbon steel sheet. Procedia Manuf 2018;20:141 6. [10] Bhargava M, Tewari A, Mishra S. Strain path diagram simulation of AA 5182 aluminum alloy. Procedia Eng 2013;64:1252 8. [11] Bhargava M, Tewari A, Mishra SK. Forming limit diagram of advanced high strength steels (AHSS) based on strain-path diagram. Mater Des 2015;85:149 55. [12] Sudarsan C, Banker KH, Hazra S, Bhagat R, Panda SK. Experimental investigations on forming limit diagram of ultra thin SS 304 steel: effect of circular grid size, sheet orientation, punch size and deformation speed. Adv Mater Process Technol 2018;05 (01):1 14.

Investigations on effect of thickness and rolling direction of thin metal foil on forming

155

[13] Sahu J, Mishra S. Limit dome height test of very thin brass sheet considering the scaling effect. J Phys Conf Ser 2016;734(3):032114 1-4. [14] Dore M, Ramos R, Matin P, Stinnett M. Learning experience in designing a dome test setup for sheet metal formability characterization. In: Conference: 2017 ASEE annual conference & exposition; 2017. p. 1 29.

CHAPTER EIGHT

Evaluation and characterization of rolling of brass at cryogenic conditions Swadesh Kumar Singh, Satyanarayana Kosaraju, Jayahari Lade, V. Dinesh Varma and M. Sandeep Gokaraju Rangaraju Institute of Engineering and Technology (GRIET), Hyderabad, Telangana, India

Nomenclature UTS YS %EL UTM EDM ANOVA DOF SS MSS P% A B C

Ultimate tensile strength Yield strength Percentage elongation Universal tensile machine Electric discharge machine Analysis of variance Degree of freedom Sum of squares Mean of sum of squares Percentage contribution Temperature Orientation Velocity

8.1 Introduction Copper zinc (Cu Zn) alloy is widely used as an industrial material because of its excellent characteristics such as high corrosion resistance, nonmagnetism, and good machinability [1]. To improve the machinability of the alloy a little concentration of lead is also added [2]. Copper being a vital Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00008-7

© 2020 Elsevier Ltd. All rights reserved.

157

158

Swadesh Kumar Singh et al.

and major part of these types of alloys the formability of the brass can be varied with its variable change in percentage composition. It has also been observed that many elements are also added into the alloy as solid solution strengtheners to improve the overall properties of brass but on the contrary it is seen that large quantities of these have resulted in built up of coarse and brittle intermetallic compounds in the matrix [3]. Brass alloy being a material of good properties but has few issues when it is used for conventional welding, for example, it is very reactive to oxygen at high temperatures, and it is also having high thermal conductivity which dissipates the heat from the welding area and loss of strength in the fusion zone due to Zn evaporation and high distortion [3]. The characteristics and structural wresponses of the material must be established in order to address the key issues concerning design enhancement. Generally, it is well known that, once an accurate and precise understanding of the selected material is achieved then structural responses can be easily evaluated. In that concern, deformation behavior is decisive especially in the success or failure of the material. Liquefied natural gas (LNG) is stored and shipped efficiently at lower temperatures. Therefore, the selected material must ensure safety and should withstand dynamic loading conditions as they are subjected to repetitive impact loads from time to time [4]. In the present scenario there is been an increasing trend for materials which can withstand cryogenic temperatures [5 10]. In line with this trend many alloys of copper are being tested at cryogenic temperatures for properties which can be used in applications like jet’s, sensitive electronic equipment, and many more [11 13]. In this work we have studied the mechanical properties of brass at cryogenic temperatures and formulated a formula for predicting properties at various other temperatures and in addition we have also done ANOVA. In the present work, uniaxial tensile tests were conducted on brass in DAK system equipment. A total of 27 experiments were performed based on full factorial design of experiments, by selecting three controlling factors (process parameters) namely crosshead velocity, orientation, and temperature. A full factorial design helps to study the combined effects of the factors (process parameters) on a response. In addition to that mathematical model was used for predicting the responses like ultimate tensile strength (UTS), yield strength (YS), and elongation using process parameters at different intervals. A confirmation test was also conducted in order to verify the validity of the model. Furthermore, analysis of variance (ANOVA) was also carried out to examine the most significant factors for UTS, YS, and n in tensile testing process.

Evaluation and characterization of rolling of brass at cryogenic conditions

159

8.2 Materials and methods 8.2.1 Work piece preparation The work material used in the present work brass supplied in the form of 0.6-mm thick cold rolled sheet from the retailer. As per the system and ASME standards for cryogenic conditions testing 0.6 mm sheet is required. The sheets were then machined as per ASTM-E8M standard shown in Fig. 8.1 using a wire cut electric discharge machine (WEDM) to obtain a given tolerance and orientation shown in Fig. 8.2. The chemical composition of the as received material is shown in Table 8.1.

8.2.2 Experimental plan As per manufacturer recommendations, pilot tests were conducted and feasible range of parameters for a system were selected as shown in Table 8.2. A total of 27 experiments were planned accordingly to the full factorial design using design of experiments. Table 8.3 shows design matrix of actual

Figure 8.1 ASTM-E8M tensile test.

Figure 8.2 Tensile specimen orientation standard specimen.

160

Swadesh Kumar Singh et al.

Table 8.1 Chemical composition of investigated brass wt.%. Element Cu Zn Pb

Bi

Ag

Weight (%)

0.0006

0.006

98.8

1.15

0.0010

Table 8.2 Process parameters and their levels. Factors Units Level 1 

Temperature (A) Orientation (B) Velocity (C)

2 50 0 3

C Degrees mm/min

Level 2

Level 3

2 25 45 5

0 90 7

Table 8.3 Design matrix. Std Run Temperature

Orientation

Velocity

A

B

C

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

0 0 0 45 45 45 90 90 90 0 0 0 45 45 45 90 90 90 0 0 0 45 45 45 90 90 90

3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7

3 2 1 3 2 1 3 2 1 3 2 1 3 2 1 3 2 1 3 2 1 3 2 1 3 2 1

1 1 1 2 2 2 3 3 3 1 1 1 2 2 2 3 3 3 1 1 1 2 2 2 3 3 3

1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3

18 12 14 13 09 10 22 03 07 17 11 20 06 26 16 25 04 08 01 24 02 21 15 23 05 27 19

0 2 25 2 50 0 2 25 2 50 0 2 25 2 50 0 2 25 2 50 0 2 25 2 50 0 2 25 2 50 0 2 25 2 50 0 2 25 2 50 0 2 25 2 50

Evaluation and characterization of rolling of brass at cryogenic conditions

161

and the coded variables were arranged as follows: A—temperature, B— orientation, and C—velocity, respectively. The experiments are conducted randomly as shown in design matrix (“Run” column in Table 8.3).

8.2.3 Experimental setup To study the deformation characteristic under cryogenic conditions, a custom built mechanical testing machine was used as shown in Fig. 8.3 in schematic form and in Fig. 8.4 in experimental setup. A universal testing machine (UTM) equipped with cryogenic chamber (lower limit of 270 C)

Figure 8.3 Schematic representation of UTM.

Figure 8.4 Experimental setup.

162

Swadesh Kumar Singh et al.

was used to conduct unidirectional isothermal tensile test. The equipment is equipped with DAK closed loop servo-hydraulic dynamic testing system of 5-ton capacity with series 9000 digital controller. Liquid carbon dioxide was used as the coolant to generate cryogenic conditions. It was equipped with an inlet and outlet hose to connect the liquid carbon dioxide cylinders which was automatically controlled to maintain the constant temperature during the experiment.

8.3 Results and discussion The material properties are calculated at three different temperatures ranging from 0 C to 250 C at an interval of 25 C. In addition we had three different crosshead speed and three different orientations with respect to the rolling direction. The orientation we have taken are 0, 45, and 90 degrees and the crosshead velocities vary from 3 to 7 mm/min in intervals of 2. From experimental results it is noticed that temperature is playing a crucial role in determining the strength of the material as flow stress is primarily influenced by variation in temperatures. Flow stresses are reported to be increasing with reduction in temperatures which is due to uniform macroscopic distribution. This phenomenon occurs due to mobility of dislocation during in the initial stages of deformation. It is important to note the trend that the strength of the material is increasing with temperature and crosshead speeds, and on the contrary percentage elongation (%EL) is decreasing. Further, from the Figs. 8.5 8.7, it is understood that as the crosshead velocity increases, the UTS and YS are increasing due to increased flow of material than the dislocation movement and higher stress is required to accelerate it. On the other hand, the %EL has a decreasing effect as expected. Similarly, both UTS and YS have increased with decrease in temperature. At lower temperatures, the internal energy of an atom decreases. As a result, atoms lose their thermal agitation energy and vibration movement decreases in intensity which in turn hamper the movement of dislocations present in the materials and higher stress is required to facilitate the movement of dislocations. It is also observed that the %EL has been decreasing parallel with decrease in temperature which can contribute to decrease in vibration

Evaluation and characterization of rolling of brass at cryogenic conditions

163

Figure 8.5 Variation of UTS with velocity for different variables.

Figure 8.6 Variation of YS with velocity for different variables.

energy in the atoms of the materials which resist the force that is applied on them and cause a small amount of elongation in the material till the force reaches a limit and then failed. On the other side, elongation in the material is behaving inversely with increase in crosshead velocity which can be attributed to the increase in rate of elongation which decrease in temperature.

164

Swadesh Kumar Singh et al.

Figure 8.7 Variation of %EL with velocity for different variables.

8.4 Analysis of variance and regression equation ANOVA was introduced by Sir Ronald Fisher [14]. This analysis was carried out for a level of significance of 5%, that is, for 95% level of confidence using Minitab statistical software. The purpose of ANOVA is to investigate which parameter significantly affects the performance characteristics [15]. Tables 8.4, 8.5, and 8.6 show the results of ANOVA for UTS, YS, and %EL, respectively. In the study only significant factors are considered (i.e., P-value , .05) for calculating the percentage contribution and is labeled as “%C” in all the cases of UTS, YS, and %EL. From the Tables 8.4 8.6 it is clear that for UTS, YS, and %EL temperature is most significant performance characteristics compared with other characteristics. Regression analysis is also carried out to know which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. Regression analysis produces a regression equation where the coefficients represent the relationship between each independent variable and the dependent variable. In the present work, regression equations for UTS, YS, and %EL are generated through Minitab statistical software by considering the significant variables only from Tables 8.4 Table 8.6. R-squared value for UTS is 99.38, YS is 94.47, and for n is 91.02 which shows the statistical measure of how close the data are to the fitted through the regression equation.

165

Evaluation and characterization of rolling of brass at cryogenic conditions

Table 8.4 ANOVA UTS. Source DF Adj SS

Model A B C A A Error Total

4 1 1 1 1 22 26

3186.59 28.60 27.13 81.07 103.61 19.83 3206.42

F-value

P-value

%C

Remarks

884.00 31.73 30.11 89.96 114.97

.000 .000 .000 .000 .000

11.9 11.2 33.7 43.1

Significant Significant Significant Significant Significant

Regression equation for UTS: UTS 5 248.067 2 0.1818A 1 0.02728B 1 1.061C 1 0.006649A A.

Table 8.5 ANOVA YS. Source DF

Adj SS

F-value

P-value

%C

Remarks

Regression A B C Error Total

1898.33 1586.35 68.37 243.62 111.09 2009.42

131.00 328.42 14.15 50.44

.000 .000 .001 .000

83.6 3.6 12.8

Significant Significant Significant Significant

3 1 1 1 23 26

Regression equation for YS: YS 5 80.03 2 0.3755A 1 0.0433B 1 1.839C.

Table 8.6 ANOVA %EL. Source DF

Adj SS

F-value

P-value

%C

Remarks

Regression Temperature Orientation Velocity Velocity  velocity Error Total

49.324 16.436 5.690 7.549 4.932 4.869 54.193

55.71 74.26 25.71 34.11 22.28

.000 .000 .000 .000 .000

47.5 16.4 21.8 14.3

Significant Significant Significant Significant Significant

4 1 1 1 1 22 26

Regression equation for %EL: %EL 5 21.01 1 0.03822A 2 0.01249B 2 2.823C 1 0.2267C C.

8.5 Conclusions An attempt has been made to explore the influence of temperatures, directionality, and velocity on the UTS, YS, and %EL of brass sheets and the results are summarized as follows: • As crosshead velocity increases, the UTS and YS increases. • With increase in orientation considerable increase in UTS and YS was observed.

166

• • • •

Swadesh Kumar Singh et al.

Decreasing trend was observed in %EL, as crosshead velocity increases. With increase in orientation decreasing trend was observed in %EL. From the ANOVA tables, it is clear that temperature is the most influencing performance characteristics than other characteristics in case of UTS, YS, and %EL. R-squared value for the models found for UTS is 99.38, YS is 4.47, and %EL is 91.02 which shows that how close the data are to the fitted using the regression equation.

References [1] Hussein RM, Abd OI. Influence of Al and Ti additions on microstructure and mechanical properties of leaded brass alloys. Indian J Mater Sci 2014;2014:909506. [2] Imai H, Kosaka Y, Kojima A, Li S, Kondoh K, Umeda J, et al. Characteristics and machinability of lead-free P/M Cu60 Zn40 brass alloys dispersed with graphite. Powder Technol 2010;198(3):417 21. [3] Atsumi H, Imai H, Li S, Kondoh K, Kousaka Y, Kojima A. The effect of solid solutionizing Ti element on microstructural and mechanical properties of extruded Cu-40Zn-Ti ternary alloy. Trans JWRI 2011;40(1):67 71. [4] Park WS, Chun MS, Han MS, Kim MH, Lee JM. Comparative study on mechanical behavior of low temperature application materials for ships and offshore structures: part I—experimental investigations. Mater Sci Engineering: A 2011;528(18):5790 803. [5] Liu Q, Wang F, Wu W, An D, He Z, Xue Y, et al. Enhanced mechanical properties of SiC/Al composites at cryogenic temperatures. Ceram Int 2019;45(3):4099 102. [6] Fink M, Fabing T, Scheerer M, Semerad E, Dunn B. Measurement of mechanical properties of electronic materials at temperatures down to 4.2 K. Cryogenics 2008;48 (11-12):497 510. [7] Brennhaugen DD, Georgarakis K, Yokoyama Y, Nakayama KS, Arnberg L, Aune RE. Tensile properties of Zr70Ni16Cu6Al8 BMG at room and cryogenic temperatures. J Alloy Compd 2018;742:952 7. [8] Yan JB, Xie J. Experimental studies on mechanical properties of steel reinforcements under cryogenic temperatures. Constr Build Mater 2017;151:661 72. [9] Sert A, Celik ON. Characterization of the mechanism of cryogenic treatment on the microstructural changes in tungsten carbide cutting tools. Mater Charact 2019; 150:1 7. [10] Xu Z, Roven HJ, Jia Z. Mechanical properties and surface characteristics of an AA6060 alloy strained in tension at cryogenic and room temperature. Mater Sci Eng A 2015;648:350 8. [11] Ageladarakis PA. Tensile and fracture toughness tests of CuNiSi at room and cryogenic temperatures. Abingdon: Joint Eur. Torus; 1999 (No. JET-R-99-01). [12] Kumar P, Rasu NG, Routh B. Flow and fracture behavior of copper with different strain rate at room temperature. Int J Mech Eng Technol 2017;8(10):140 6. [13] Cai B, Ma X, Moering J, Zhou H, Yang X, Zhu X. Enhanced mechanical properties in Cu Zn alloys with a gradient structure by surface mechanical attrition treatment at cryogenic temperature. Mater Sci Eng A 2015;626:144 9. [14] Montgomery DC. Design and analysis of experiments. New York: John Wiley & Sons.; 2017. [15] Ross PJ, Ross PJ. Taguchi techniques for quality engineering: loss function, orthogonal experiments, parameter and tolerance design. New York: McGraw-Hill; 1988 (No. TS156 R12).

CHAPTER NINE

Multiaxis CNC programming and machining T. Vishnu Vardhan and B. Sridhar Babu 1

CMR Institute of Technology, Hyderabad, India

9.1 Numerical control of machine tools This is an automation process to control the functions of machine tools with numbers, letters, and some symbols. The program developed with alpha-numerals fed to numerical control (NC) machine tool will provide the required movements of table, tool selection, path, speed, feed, and other versatile information. A better control on NC machines can be achieved by automated functions as mentioned 1. Start/stop and speed control of machine tool spindle 2. Tool traverse into desired locations for positioning tool tip in exact location 3. Control of motion slides 4. Tool change in spindle The capabilities that are expected from the machine tool to give the final work piece with accuracy and good surface finish are 1. Firm and secure holding of cutting tool and job. 2. Proper and sufficient power supply to facilitate cutting action. 3. Controlled degree of precision to enable the displacement of cutting tool and work piece to produce high degree of surface finish. The multiaxis machining involves different cutting tools to remove the material to obtain the desired shape or feature in the form of final part/product. In multiaxis machining the tools can perform cutting action by moving in four or more directions. The mechanical construction of complex machines which can be operated even with more than 10 axes and control actions can be done with cam plates and other simple mechanical components. The main actions such as tool movements, part Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00009-9

© 2020 Elsevier Ltd. All rights reserved.

167

168

T. Vishnu Vardhan and B. Sridhar Babu

placement, and rotation of tool/part will be controlled by the levers and cam plates. The level of complexity increases with all these attachments and the size of the machine setup also increase as the number of axes is more. The CNC machines have provided more flexibility and greatly reduced the setup time in production [1]. Each axis of movement either for the work piece or for the tool are implemented by moving tables. Therefore based on the requirements the same number of axes differs in the movements. A typical 5-axis machine with work piece translation in X, Y, and Z axes along with cutting tool traverse two rotational axes can be seen in industry. Automatic conversion of 3-axis to 5-axis tool-paths in CAM environment is possible with advanced softwares. Earlier to the use of these softwares the design data transfer essential in production process was tedious and require more man power and have utilized more time and incurred material wastage [2]. The main components of multiaxis machines are 1. The physical capabilities 2. The CNC drive system 3. The CNC controller The specifications those will be indicated in the machine manual are the physical capabilities of the machines such as the spindle speed, orientation, torque, etc. [3]. The servo motors are the CNC drive systems whereas the data transfer, data storage, and process execution are the functions of CNC controllers. Multiaxis machines provide a better surface finish with increased tool life. The complex parts with curves and internal holes can be produced due to capabilities of tangential machining. Number of setups can be minimized with the use of multiaxis machines; errors can be greatly minimized and thus can produce sound quality parts [4].

9.2 Integrating CNC and automation The shop capability in terms of productivity can be enhanced with advanced programming and process automation [5]. The cost associated with labor can be also reduced. There will be no need for compromise in obtaining automated machining of the parts with high accuracy and speed. CNC machine cells are essential as the single machine tool is not

Multiaxis CNC programming and machining

169

sufficient for required part production. The different machine tools such as drills, lathes, mills, electrical, and chemical machining can be used in manufacturing cells to produce the parts which require different processes [6]. The tool wear and thermal expansion of CNC machines are the important parameters that should be addressed properly to obtain sound finishing cuts. The thermal expansion algorithms are now available and on integration with machines, these algorithms can predict the tool position in out of tolerance. In automating the setup, warning indicators also can be arranged to check and perform measurements on tool and decision will be taken for tool change if necessary. The increased CAD/CAM system capabilities, availability of different solid modeling formats, enhanced possibilities of computer integration to connect machines, robotic arms, sensors, Ethernet, machine vision, etc., have helped in increasing the production with automation strategies.

9.2.1 5-Axis machining The 5-axis machining requires one time setup for the most of the typical parts production [7]. These machines have the capability of tool axis direction change, utilizing shorter tools which can reach undercut zones. Their adaptability in to machine shops of all sizes offer the cost related benefit which cannot be obtained only with the standard machines. Now a days 5-axis machines are available in market with latest technology where the complete methodology of machining is delivered with single function call. The 5-axix machines have two rotational axes in addition to standard linear movement in X, Y, and Z directions. The standard ISO used the notation A for rotation about X, B for rotation about Y, and C for rotation about Z axes.

9.3 Flow of commands for 5-axis machine The following process will give a better understanding on how to obtain complex shape generation through multiaxis machines. The below mentioned steps as shown in Table 9.1 can be combined in to a single composite function. A special feature available in CAM known as freeform is used for the selection of machining areas. For the end user understanding, this option

170

T. Vishnu Vardhan and B. Sridhar Babu

Table 9.1 Flow of commands for composite function in multiaxis machines.

Step Use different color codes for machining 1 areas and areas to be avoided from machining Step Identify path to be followed by cutting 2 tool Step Identify tool orientation 3 Step Tool transition between cutting passes 4

Identification of machining areas and nonmachining areas only Deliver machining pattern Flexibility in selecting tool/part orientation in 5-axis setup Movement of the tool in selected zones

will provide different color codes for both machining/nonmachining areas. The feature form machining provides a flexibility of surfaces blending, addition or removal so that the feature can be reopened and modified further as per the requirement. This edited information should be updated in tool path indicated as step 2 in Table 9.1. Various patterns can be used in multiaxis machining which aids in tool-path definition. Some of the tool-path contours are parametric patterns which utilizes surface natural flow entities for machining. The other method is projecting the lines onto the separate surface for machining. As the tool-path is selected from CAD model, the smoothness of the CAD image will show the effect on toolpath. The schematics shown in Figs. 9.1 and 9.2 are for the turbine blade model to be machined using 5-axis machine. The point position and model representation are done in CAD software and simulation of machine tools followed by post processing program. As and when the design has been approved, the process sheet will be developed with NC program inclusion to produce the part as per design data. The vital information pertaining to scheduling, shop floor controls tool fixtures, and other setups will be given as inputs to complete the machining process. This process is shown in Fig. 9.3.

9.4 CNC programming validation The details such as machine tools horsepower, RPM, and velocity are key parameters of spindle/turret in creating the motion axes definitions [9]. The validation of the CNC programs is a process that integrates

Multiaxis CNC programming and machining

171

Figure 9.1 Schematic diagrams of the model [8].

Figure 9.2 Schematic diagrams point position [8].

various functions that may result in the establishment of standards, edition the programs, and setting the set of rules for obtaining the expected output of the product with high level of accuracy. In practical it is evident that the first time CNC program development is an investment and editing and debugging the same for further is cumbersome. The complications that could arise in the process of CNC program creating, validation, and utilization are 1. Diversity of CNC machines attending the production process. The diversity may be the controls, accessories, and capabilities. 2. The program uses hundreds even thousands of code lines depending on the complexity of the geometry required to obtain. Editing the same level of program also require more time.

172

T. Vishnu Vardhan and B. Sridhar Babu

Figure 9.3 Steps in processing NC programs.

3. CNC programmer’s and machinist’s ability. 4. Participation of different CNC programmers for developing CNC programs for same machine tool leads to increased level of difficulty in understanding and processing by the machinists on CNC machine tools. The documentation types also differ from each and may lead to misinterpretation of content some times. 5. The CNC programs developed by the CNC programmer also indicate the specific cutting tools. The manufacturer may replace those specified cutting tools with new cutting tools. To incorporate this change of cutting tool, the CNC programmer has to edit the program and validate the same before setting up the production process. 6. The capacity issues are common and they have to be also addressed. Some times to produce the same part, same CNC program have to be used for multiple models of CNC machines. The maintenance issues also recommend the above process to increase the production rate.

Multiaxis CNC programming and machining

173

7. Machinists, CNC programmers may edit the existing program but reprogramming also needed some times as per engineering change notices. 8. Accommodating the CAM software developments in the form of minor/major changes, updating of versions, appending with different CAM versions also require sufficient time to pace up with existing methods. The CNC programmer and machinist shall understand the document that the CNC program gives the specific sequence of machining as per the process drawings. This document becomes a reference document and it cannot be changed without the notice of the management team responsible for it. The same CNC program will be utilized for further over a period of certain years in different shifts; the machinist in every shift shall assure the correctness of CNC program along with specified tool list and setup instructions. This precaution may help the team in understanding the complications that may arise in future are not due to CNC programming as a root cause but it can be solved by the engineers and machinists, and can avoid the consuming hours of CNC programmer. In case of high volume production, the CNC program developed as a perfect one can be locked at machine control to stop further editing. In most of the organizations it may not be possible to follow the rigid CNC program validation. So, the individual machinists store the programs written on their own versions either directly on machine tool control or on a storage device. When the production goes in shifts the program may be edited by the machinists from shift one to another shift. This sort of editing the original CNC program may negate the CAM system performance. The quality risks are high that saps the productivity due to editing of CNC programs. It has non-value activities leads to bottle necks in the program department. The validation of CNC becomes appropriate and lies in-line with other procedures of program development when the following points are incorporated. 1. New employees can be trained on technical standards required to follow CNC programs thus making them productive. 2. CNC programmers and team of support staff cannot be utilized for activities that may affect production. One such activity is changing the CNC program which already existed. 3. Reduction of unnecessary risks in the process of production.

174

T. Vishnu Vardhan and B. Sridhar Babu

4. Tool changing in CNC machines constantly for a specific CNC program thus various tools made available for processing will reduce the purchasing cost. 5. Avoiding the full exploitation of CAM system for increasing the productivity. 6. Reducing the human and machine time for unnecessary changes.

9.5 Continuous improvement without editing the CNC program The focus to foster continuous improvement without editing the CNC programs used in a specific process through 1. Refinement and fine tuning of tool wear offset value, tool direction, and timing used. 2. Focusing on each cutting tool replacement timings with enhanced inspection methods and frequency of inspections. 3. Making system ready with automatic backup tooling. 4. Construction of machine tool setup with alternate fixtures.

9.5.1 Complex tool path programing in multiaxis machining centers Complex tool paths are required for producing parts such as turbine blades, certain tooth surfaces, etc. The system utilizes analytical curves with their definitions in floating ranges. Tool paths are calculated in such a way that they can improve the accuracy of calculation levels by decreasing the calculation time for multiaxis machining centers. High-speed machining and custom-made tools have become the features of present technology of multiaxis machines that can produce complex parts with less time allocation for programming and machining. Efficient software packages are available now in the market to handle and implement high speed multiaxis machines to process complex surfaces. The algorithms developed in the specialized CAD/CAM systems are featured with parametrical processing functions to calculate base areas of each surface to be processed, proceeding further for NC programming.

Multiaxis CNC programming and machining

175

9.5.2 Cutting tool path definition in multiaxis machine tools The part geometry, advancing angle, and machining allowances defined parametrically in multiaxis machines will influence the cutting tool path definition. It is preferred to develop the NC programs by positioning center line of cutting tool as reference. When dealing with corners, the surface quality depends on angular positioning of cutting tool, and other cutting parameters. To justify all these concerns special set of algorithms are developed which further can establish the relationships between these factors to provide the solutions for tool inclination and advancing angles.

References [1] Grigoriev SN, Kutin AA. Advanced method of NC programming for 5-axis machining. Procedia CIRP 2012;1:102 7. [2] Zivonic S, Slavokovic N, Kokotovic B. Machining simulation of virtual reconfigurable 5-axis machine tool. Int J Eng 2017;15:189 94. [3] Li Y, Zhao W, Lan S, Ni J, Wu W, Lu B. A review on spindle thermal error compensation in machine tools. Int J Mach Tools Manuf 2015;95:20 38. [4] Suh SS, Lee JJ, Kim SK. Multiaxis machining with additional- axis NC system: theory and development. Int J Adv Manuf Technol 1998;14:865 75. [5] Joshi AM. Computer aided process planning for multi-axis CNC machining using feature free polygonal CAD models. Graduate Theses and Dissertations; 2015. [6] Grigoriev S, Kutin A, Turkin M. Advanced CNC programming methods for multiaxis precision machining. Key Eng Mater 2014;581(2014):478 84. [7] Lo C-C. Feedback interpolators for CNC machine tools. J Manuf Sci Eng 1997;119:587 92. [8] Yang L, Feng J. Research on multi-axis CNC programming in machining large hydraulic turbine’s blades based on UG. Procedia Eng 2011;24(2011):768 72. [9] Chen ZC, Wasif M. A generic and theoretical approach to programming and postprocessing for hypoid gear machining on multi-axis CNC face-milling machines. Int J Adv Manuf Technol 2015;81(2015):135 48.

CHAPTER TEN

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana Emmanuel Baffour-Awuah1, Stephen Akinlabi2 and Tien-Chien Jen1 1

Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa Department of Mechanical & Industrial Engineering Technology, University of Johannesburg, Johannesburg, South Africa

2

10.1 Introduction The millennium development goals (MDG) target 7c was set with the aim of halving the percentage of global population without access to improved water source in rural and urban communities between 1990 and 2015 [1]. Between 2002 and 2008 the global population lacking improved drinking water fell from over 1 billion to 884 million [2]. Although the MDG7c (i) was achieved by 2010 a significant inequality among nations and continents did exist [3]. By 2013 there was conspicuous unevenness among the countries. While some countries had achieved many goals, others had achieved nothing. For instance, while China and India had achieved high successes Benin had achieved none at all [4 6]. In spite of the inequalities that existed as at 2015 among nations, Ghana had achieved its target of MDG7c by halving population without access to improved water source [7]. In the UN classification model, improved water source including household connections, boreholes, protected dug well, protected spring, and public standpipe. Unimproved water source include rivers or ponds, bucket, unprotected well, and unprotected spring. The rest are render-provided water, tanker truck water, and bottled (and sachet) water [8]. This classification needs more than desired, as challenged by some researchers, by grouping sources of water as either improved or unimproved [9,10]. This justification has come to the fore considering the introduction of “sachet water” in the early 1990s in Ghana juxtaposing the positive achievement of the MDG7c goal by Ghana in 2015. Various studies in Ghana have indicated the safe and Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00010-5

© 2020 Elsevier Ltd. All rights reserved.

179

180

Emmanuel Baffour-Awuah et al.

healthy nature of both sachet and bottled water particularly when contrasted with quality of river, stream, ponds, unprotected well, and tanker truck water among others [11 15]. It is no gainsaying, therefore, the fact that the introduction of sachet water and bottled water has contributed to the achievement of improved and safe drinking water in the country. Packaging of sachet and bottled water has, nevertheless, brought about issues that must be grappled with. For example, besides waste management issues, the material used for packaging these sources have direct environmental consequences. Polyethylene (PE), the major packaging material, has toxic ingredients which when enter the environment has detrimental effects on both humans and animals. Its environmental harm to both the environment and living organisms has been well documented in literature and various scholarships. This work dilates on the application of recycling as a means of tackling the detrimental effects of PE used in sachet water packaging. The recycling industry in Ghana is small and young [16,17] and therefore needs innovations in terms of technology to deal with this menace. One of the techniques that can be used to deal with the detrimental effects of the use of PE is recycling. Recycling can be effective and efficient if issues relating to legislation as well as management of PE waste and recyclates are appropriately managed. Since various types of recycling techniques are available, there is the need to adopt the most suitable technology that can economically, technically, and commercially cope with the Ghanaian condition and situation. For example, should the country adopt thermal, mechanical, chemical, or biological recycling technique? Does the technology and technical competence in the country cope with thermal recycling or otherwise? Although recycling generally has some disadvantage, it is a better option than other available techniques such as land filling or incineration. In spite of the more popular methods of dealing with plastics and other wastes, some less popular techniques such as biodegradation and candidate plastic-fiber composites are potentially available. Advancing research into these recycling techniques, particularly candidate PE composite formation can have a brighter future to the global and developing community, particularly Ghana. The sustenance of MDG7c by countries that achieved the goal and the future sustainability thereof is of paramount importance. For this reason it is high time the nation paid attention to the Sustainable Development Goal (SDG 6 target a c), Agenda 2030, in terms of availability and accessibility of safe drinking water by considering PE fiber composite technology as a complimentary innovative way toward environmental pollution control and environmental waste management.

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

181

10.2 Sachet water in Ghana Introduction of sachet water in West Africa coincided with the adoption of the MDG in 1990 as a preferred water source [13,18]. Many scholarships have documented that sachet water has become relatively the most popular and patronized water source since its introduction in West Africa, particularly Ghana and Nigeria, as a result of its numerous advantages. These include its effective, potable, mobile, reliable, and affordable characteristics [18,19]. The seriousness and commitment to which these two countries appear to have given to the MDG7c have also contributed to the fast rate at which the commodity has permeated through every nook and cranny of both rural and urban communities. While Stoler et al. [18] report of sachetwater use in rural communities having more patronage, Kassenga [20] and GSS [21] have evidence to show that sachet water is well patronized by the urban rich. The introduction and patronage of sachet water is a panacea to a challenge to government toward provision of safe water availability and accessibility through the private sector. It is intimated by that with increasing population and urbanization, public water infrastructure has been unable to support the demand of safe drinking water in Ghana. Although governments have tried to increase availability and accessibility to potable water, sachet water continues to gain popularity and patronage. The genesis of municipal water facilities in Ghana started during the colonial regime in 1928 when the country was referred as Gold Coast. Before then rivers, streams, ponds, and wells were the available and accessible water sources. The colonial masters imported water from Europe for consumption [18,22]. As an innovative and inexpensive technological commodity, vended water dates back to the early 1970s as water in earthenware and later in large aluminum buckets. It was in the form of water in cups and patronized by people in urban areas particularly at lorry parks, markets, and railway stations, according to one elderly octogenarian interviewed. This mode of vendedwater delivery advanced into plastic bottled water, although untreated and open. The unsealed and open plastic bottled water gradually went into obscurity in the late 1980s. Water packaging in small PE plastic films reared its revolutionary head, gradually in the late 1980s; and became more acceptable by the urban communities in the early 1990s. However by the middle of 1990s sachet water was hitting hard in the market partly due to sanitary reasons and the advent of Chinese technology with state-of-the-art

182

Emmanuel Baffour-Awuah et al.

technology to ensure mechanical, chemical, and photochemical treatment, as well as heat-sealing. By 2005, sachet water had become a generally accepted mode of water source, not in Ghana alone but many African countries [13,18,22]. Ghana achieved enhanced improvement from 1990 in terms of safe drinking water, having achieved the target. However, much needs to be done. As rural communities and towns become urbanized with increase in population, the urban populations may continue to grapple with safe, available, and accessible drinking water. The situation may be worsened by the wanton exploitation of gold in rural areas, forest regions, water basins as well as rivers and streams. The National Ghana Water Company Limited (GWCL) which is in charge of water distribution of over 80% of city residents may not be in the position to fulfill its mandate of providing potable water to 100% of urban communities in this regard. Connecting pipes to communities and individual households does not ensure potable water. For this and other reasons aforementioned, GWCL has usually resorted to water rationing which is fraught with incessant predictability and intermittency [18]. In addition to deficiency of water allocation in urban areas, water rationing also depend on social class in terms of suburbs and communities as well as individual piping connectivity; contributing to sachet-water patronage [22]. There is therefore no doubt that sachet water has become an ubiquitous primary water source in such communities as posited by Stoler et al. [18]. In rural areas where illegal mining, usually referred as “galamsay” has destroyed many streams and rivers sachet water may be the only source of drinking water.

10.3 Challenges of water PE-packaging In spite of the benefits of sachet and bottled water in general and its contribution toward meeting the MDG on safe drinking water in particular, the patronage of the product has brought about both environmental and health challenges. Although health challenges may be domestic, the effect on the environment could be both domestic and global. For over half a century, plastics have played a significant role in the packaging industry globally and water packaging is no exception. Particularly in developing countries, the menace brought about by waste generation as a result is demonstrated in waste disposition into the environment. For example, close to 8 million tons

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

183

of plastic waste enters the earth’s oceans annually. In India, over 5.6 million tons of plastic waste is generated with ever-increasing quantities on annual basis. Out of this quantity about 60% is recycled, leaving the remaining to other methods of disposition, and some also ending up in the ocean (Hardesty and Wilcox, 2015), [23]. In Europe and the United States, less than 10% of plastic waste is recycled. In the Nordic region which includes Norway, Sweden, Finland, Iceland, Faroe Island, and Aland about 600,000 tons of plastic packaging and 56,000 tons of PE bottles enter the market annually. While 284,000 tons of plastic packaging waste is collected separately, 161,000 tons is recycled. The story of Accra, the capital of Ghana is similar. Over 730,000 tons of municipal waste is generated annually, out of which between 12% and 20% is contributed by plastic waste. According to a report of the Accra Plastic Waste Management Program, empty plastic waste account for 40% out of 120 metric tons of waste recycled daily. Thus, waste water sachets contribute immensely in solid waste generation in Ghana. Considering that these packaging materials are made of PE, the role of PE in polluting the environment cannot therefore be underestimated. It is estimated that the daily municipal waste generation in Accra is 2000 metric tons of which 510 metric tons are plastic waste. It can be inferred that a significant volume of empty water sachet enters the environment directly; some may do so indirectly through incineration or landfilling. Whether waste water sachets are incinerated or enter landfills, the effects on the environment are detrimental. For those that directly enter the environment a larger proportion may end up in the ocean through municipal drainage systems and flood water movement. Although sachet water has several advantages over other sources of water it is regarded as an environmentally unsustainable source of water due to unwanted stream of PE waste it generates. The detrimental effects of sachet waste have been documented by many authors. Burning of plastics, including sachet-water waste, has been practiced over millenniums as a cheap way of disposing waste. However the fumes that enter the atmosphere, out of this practice, contain noxious gases as well as greenhouse gases. These include nitrogen oxides and sulfur oxides, which are ingredients to acid rain and may wither botanical species and also degenerate the quality of building and civil structures, ornamental products, and any material sensitive to acidic environments. Carbon dioxide, an ingredient that supports global warming, is a threat to global climatic conditions. Global warming may lead to, extreme weather conditions such as flooding, drought, hurricanes, and desertification. Burning plastics such as PE may also release heavy

184

Emmanuel Baffour-Awuah et al.

metals such as antimony into the atmosphere and eventually co-mingle with rain water. Antimony has been found to be an endocrine disruptor and the consequence, therefore, when enters the body can be detrimental to the endocrine system particularly estrogen. Estrogen malfunction and dysfunction may lead to defects in reproductive system of mammals and humans. PE sachets also cause environmental menace in and around landfills. Land filling is another technique used in disposing waste and garbage in both rural and urban settings. Although waste sachet-water PE may land in landfills as thrash; the longer period with which they may take to decompose or degrade has been a problem to grapple with by both environmentalists and urban planners. Land filling has several disadvantages. In the first place, it takes millions of dollars to clean up litter and thrash from point of generation to the final site of landfill. Secondly, it requires tax-payers money in gathering and evaluating litter, and thrashes to enhance the esthetic nature of landfill sites. By courtesy of wind, sachet bags in landfills may also find its way outside the landfill domain, scattering around the closest, and sometimes farthest, vicinity; to the detriment of botanical landscape. Finally, landfill sites may suffer from overloading due to waste generation in settlement areas or lack of appropriate location to site new landfills or both. The consequence is that waste sachet bags become accumulated and find their way in nearby streams, highways, and farmlands. It is estimated that in the United States alone, approximately 100 billion PE bags are manufactured annually at the expense of 2 million barrels of crude oil; Globally, between 500 and 1 trillion plastic bags are dumped into the environment. Twenty five percent of PE being bags used in western countries such as the United States, Europe, and Canada, are manufactured in Asia; and 17 million barrels of crude oil to transport this product from Asia to their destination countries; [24]. As petroleum-based products, PE is manufactured from crude oil, natural gas, and not too long ago, kerogen. During manufacturing the source of energy is usually also obtained from petroleum products. Thus, the source of energy and the raw materials for manufacturing plastics are themselves sources of pollution to the environment. The generation of noxious gases, fumes, and particulates go a long way to pollute the environment. Effluents generated in the process may also cause environmental pollution. Heavy metals, such as cadmium, antimony, mercury, lead (stabilizer and pigment), cadmium (pigment), antimony (catalyst for flame retardant), selenium, etc., may be injected into the environment. Thus considering the quantum of PE bags produced annually, and the volume that enters the environment

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

185

as waste, the contribution of those chemicals to the environment needs too much to be desired. The portion of PE that lends to the so called plastic soup, “an island of plastics in the ocean” has been a nuisance to both esthetics of natural habitat as well as its inhabitants as marine plants and animals (Disadvantages of Plastic Bags, 2017). The so called “plastic soup” is almost twice the size of continental United States located near Australia. The Independent newspaper stated that more than 50 million plastic bags find their way into the Pacific Ocean every year (Disadvantages of Plastic Bags, 2017). What makes plastics in the environment more critical, and for that matter PE, is the ability to remain in the environment between 400 and 1000 years before decay or degradation; and that the plastic soup close to Britain is about 80% that found in Australia (Disadvantages of Plastic Bags, 2017; New, 2017). It is estimated that between 60% and 95% of marine debris is composed of plastics [25], forming plastic dust eventually. In the process, toxic chemicals such as bio-toxin polychlorinated biphenyls (PCBBs) and BPAs among others are also released into these plastic islands. Toxic chemicals released this way may be ingested by microorganisms, both plants and animals. They may eventually end up in macromarine creatures and finally ingested by humans who rely on them as food [26]. Thus through the food chain plastic toxins may end up in humans and cause health threat to various organs [26,27]. Indiscriminate disposal of sachet PE waste may also clog gutters and other municipal drainage systems causing flooding. In the ocean they are a great threat to marine organisms such as whales, turtles, and birds through toxification or suffocation or both. The Californians Against Waste Organization and the Marickville Council of Australia estimates that over one hundred thousand marine whales, turtles, and birds die each year through these processes. According to Gregory [28], it has been found that these animals die out of starvation and malnutrition due to digestive tract blockage of plastic debris and materials. The presence of plastic materials debris and dust in the ocean may lead to emaciation, degeneration of reproductive capacity, reduction in overall quality of life, and eventually loss of life or extinction as far as the life cycle of ocean organisms are concerned. Trucost [29] has computed the overall consumer goods sector cost of plastic marine debris to be approximately 4.7 billion US dollars annually. The sustainable use of sachet water as a means of solving public sector deficiency in dealing with safe water issues will be questionable if the limitations associated with it, as discussed above, are not passionately confronted.

186

Emmanuel Baffour-Awuah et al.

10.4 Recycling Recycling is the process or an act of changing the form, function, or the characteristics of a material considered as waste, into new objects or new materials [30,31]. It is a process involving re-melting and formation of a material considered waste into new products of economic value [32]. With reference to conventional waste disposal methods such as landfilling and incineration, recycling is an alternative means that help reduce greenhouse gases and acid rain formation during plastic manufacturing. Thus, during plastic production from petroleum, recycling helps lessen volumes of potentially useful materials and reduce the application of new raw materials. With such technique, energy consumption as well as air and water pollution is also reduced. As the third and last item on the waste management hierarchy of “Reduce, Reuse, and Recycle,” recycle focuses at replacing new raw materials in economic environments. It also redirects materials considered as waste back into nation’s economics [33,34]. According to Zikmund and Stanton, recycling is characterized with a “reverse distribution” process which is organized through a “backward” stream whereby objects and materials considered waste are packaged and sent back to the manufacturer [35]. The recycling process is, therefore, uniquely strange from marketing perspective since it is rather the final consumer who rather converts role as they recycle waste materials and objects. For this reason, the rates of recycling in developing countries tend to be higher than in middle and high-income countries [35]. For example, in India, recycling of plastics is about 60% the total but 10% in Europe and the United States (Mahapatra, 2013). Recyclable materials or recyclates include different types of paper, glass, metal, cardboard, textiles, tires, and electronics organic wastes. Recycling may yield either a new product or the same material: For example, in the former, a used office paper may be converted into a new office paper; for the latter, lead may be salvaged from a discarded car battery. For the sake of this paper, recycling involving the former as applied to plastics in general and PE in particular are considered. In 2014, 63% plastics were recovered in South Africa, postconsumer generation being the highest [36]. South Africa recycles about 18% virgin plastic annually [37]; Australia 9.2%; and Europe 14.2% [38].

10.4.1 Recycling legislation For a well-structured and patronized recycling project to commence and flourish in any nation there is the need to establish policies and legal

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

187

framework to regulate the demand and supply sides of the product market. Legislation relating recycling of plastic waste must also be promulgated, for that matter, if any recycling program is to succeed. Two types of recycling legislation are available; supply and demand legislations [31]. From the supply perspective, before a recycling program can function, there should be a large, stable, efficient, and effective, thus reliable supply of recyclable materials. Raw materials, in this case, waste materials, should be available and accessible. For example, for a PE (from sachet water) recycling plant, people should patronize PE-packaged products, consume the content (water), and leave the PE as waste: this constitutes availability. The empty PE (sachet) should then reach the processing plant at the time of need for the conversion process to be undertaking, by whatever means possible: this is accessibility. From this perspective three legislative alternatives may be used to ensure supply reliability [31], namely refuse ban legislation, container deposit legislation, and mandatory recycling collection legislation. Banning the disposal of specific materials as waste can be a good approach of preventing consumers from throwing away empty water sachets, for example. By so doing consumers may be motivated to keep such waste materials and make them available to processing plants through various collectors: self-collectors or private collection agents. The challenge with this legislation is that, if adequate recycling services are not available, illegal dumping may be preferred by consumers, thus worsening the undesired existing situation. Container deposit legislation, another legislative tool, has been found to achieve 80% recycling rate and therefore relatively efficient. Under this legislation, a bought item, for example, sachet water, is surcharged so that when the empty sachet is returned the surcharge is refunded. Such surcharges are relatively very small. In order to achieve maximum effectiveness it may be prudent to consumers to pile empty sachets up before making them available to collectors so that a sizeable quantity or volume might be realized and sold at a particular point in time [39]. Within the mandatory collection legislative regime, communities, particularly, are required to meet specific recycling targets in terms of specified material waste that must be removed from the community’s waste stream within a stated period of time [31]. It must be stated that these legislative options are not mutually exclusive. As so desired, a combination of any of these three could be introduced into the national environmental and sanitation policy framework. At the same time a community may adopt a combination of any of these according to the dictates of the situation on the ground.

188

Emmanuel Baffour-Awuah et al.

Demand-side legislation is usually referred as government-mandated demand legislation. The aim is to encourage, increase and maintain demand for recycled materials. Four options are available, namely utilization rates, minimum recycled content mandates, recycled product labeling, and procurement policies. With utilization rates, options are allowed to meet recycling quotas at a particular time or period. Tradable credits may even be obtained with recycling contracts. This option enhances demand strategy by ensuring that recycling is part of manufacturers operations. Notwithstanding these advantages, the utilization rates method can be seen to be less flexible and also has high requirement for operations and marketing reporting. For these reasons the minimum recycled content mandate is more flexible. It requires that a specific proportion of new products must contain a specified amount of recycled materials or component. Like utilization rates option, minimum recycled content technique enhances demand directly by warranting that recycling becomes part of manufacturers’ industrial programs [31,40]. Government may impose legislation on manufacturers to label products that have recycled ingredients on product packaging; including specific quality, by weight or volume, of recycled material in the item. The aim is to encourage consumers who are environmentally conscious to make informed and educated choices provided they have the wherewithal to do so. This may indirectly encourage manufacturers to patronize the inclusion of recycled materials in their products through increase in demand by consumers. By labeling recyclates regarding where and how a product is recycled, through standardization, environmentally conscious customers may also be enticed and persuaded to better patronize products with recycled materials. The last of the four government regulation technique on the demandside to increase recycled material content in products is through procurement policies. Three options are available here: setting aside a specific amount of government budget to singularly purchase recycled items; a price preference policy whereby when recycled products are procured, a bigger budget is approved; and lastly, approving the purchase of items containing recycled or refined materials by state organizations, as much expedient as it may. Although these legislations are beautiful and may work at least, to some degree, it appears Ghana has not come to appreciate the role of government in this regard. If recycling is seen as a measure of ensuring sustainability of sachet water as a means of achieving the SDG6 it is high time both state institutions and civil society pressurize government to enact legislations to enhance the supply and demand of

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

189

recyclates with the aim of ensuring environmental sustainability. Promulgation of legislations alone may not lead to achieving results; implementation, supervision, and monitoring are crucial components to achieving positive results. Monitoring and supervision requires resource persons who are skillful and experienced. In this regard, human resource development and capacity building may be required through private and public institutions to obtain the desired results.

10.4.2 Recyclates The term recyclate is used to describe a raw material transported to a waste recycling facility or a material recovering plant for processing into a newly formed material or product [41]. For example, empty PE sachet and bottled water waste might be collected and delivered using various means of collection and delivered to a processing plant for remanufacturing into PE pellet materials or products [16,42,43]. In addition to the role legislation plays in achieving efficient and effective recycling programs, the quality of recyclates available to processing plants is equally essential. Plastic processing plants usually have target material and other recyclable materials. The quality of recyclate is principally characterized by the quality of waste raw materials composing the target material with reference to nonrecyclable and nontarget materials [44]. Since producers would technically process target and recyclable materials, by deduction, the higher the quality of target and recyclable materials the easier the processing process; and hence the higher quality of recycled materials or products manufactured. Thus a poor quality recyclate may be down cycled (lower quality products such as toys, buckets, and pipes) or end up in landfills or incinerators [44]. After three or four cycles plastics in general and PE in particular cannot be recycled anymore but used as fuel (final recycling) or discarded as permanent and complete waste material. Facilitating quality recyclates begin from waste producers. For example, if PE materials are separated from other plastic materials, it is easier to identify it if it is the target recyclable material. Collection procedure and systems may also determine the quality of recyclate. Additional effort is needed to separate recyclable target material if they are mixed with unwanted waste materials. If care is not taken untargeted and nonrecyclable materials may end up in the processing plant reducing the quality of materials and products produced. Transportation, compaction, and sorting mechanisms, systems, and facilities not properly designed and selected may contribute to quality recyclate.

190

Emmanuel Baffour-Awuah et al.

Raw material transportation and compaction may result in difficult separation of target and nontarget materials. Likewise, a nonthoughtful collection, transportation, and compaction processes may contribute to difficult sorting, thus ending up sacrificing quality recyclates. Wet waste raw materials may also sacrifice quality of recyclates. Hence storage of plastic waste materials for recycling should be taken into serious consideration [45]. The type and quality of recyclates therefore differ according to country, industry, and moment in time; in effect, technology [16,43,46,47]. For example, polypropylene (PP), PE, polyvinyl chloride (PVC), polyurethane (PUR), polyethylene terephthalate (PET), and polystyrene (PS) are mainly recycled in India [48]. While some developing countries recycle PE, PP, PS, and PVC. Recycling in Ghana mainly deals with PE, PP, and PET [37,48]. Collection of raw materials in Ghana is patronized by both the informal and informal sector; with the informal sector associated with quality recyclate challenges [16]. From manufacturer’s point of view basically, plastic raw materials are received by manufacturers; plastic-size reduced; washed; extruded; pelleted and bagged; and finally delivered [16,37]. Stages of recycling at plant premises in Africa may be modeled as shown in Fig. 10.1. The quality of recyclate has many merits [44]. One, better recyclates is a foundation for better recycling quality. Two, it enhances economic growth and national development through creation of employment opportunities, and enhancing economic value of collected waste materials. Three, it encourages investor confidence as well as business and consumer confidence with reference to waste and resource management. Four, it is beneficial to the environment by reducing, reusing, and keeping materials that would have landed in landfills and incinerators which also negatively affects the environment indirectly; and finally, it can increase income levels of households, Acquiring/receiving

Sorting

plastic waste

Sale/delivery

Bagging

Pelletrizing

Size reduction

Washing

shedding

/drying

Extrusion

Agglomeration

Figure 10.1 Stages of recycling plastics waste in Ghana and South Africa.

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

191

businesses, and local government set-ups. Quality recyclates may also indirectly but positively influence flood reduction and contribute help reduce public health risk such as malaria infections. Malaria alone costs about 735 million dollars to Ghana’s economy [16,49].

10.4.3 Recycling processes Generally, recycling processes begin with collection, then sorting, rinsing, extrusion, and pelletization (remanufacturing); packaging or bagging; and delivery. Three main waste collection methods are employed by communities: curbside collection, buy-back centers, and drop-off centers [31,33]. Curbside collection practices may be described as a rational space with one extreme end being the mixed waste collection method and other extreme end, the source separation technique. With mixed waste collection all collected waste are mixed with recyclable materials. This, therefore, requires sorting and cleaning of recyclates at a common point. The challenge is that recycling facilities have large quantities of recyclable waste to contend with; not excluding glass, paper, metals, etc. However, since sorting is done at a common sorting premise, recyclable materials are less tedious to be cleaned and sorted. Cost and energy required for educating the populace to separate waste at source is also minimized or prevented. On the other extreme end, source separation requires all recyclable materials to be separated cleaned and sorted before the point of collection. Operation cost for post-collection sorting and cleaning is, therefore, minimal while recyclates tend to be the most unadulterated. The challenges include thorough public education and higher operation cost if recyclate adulteration is to be prevented. Within the space is a popular method, singlestream (commingled), which requires that all recyclables are collected, in a mixed environment although separated from other waste materials. Although public education program is required as to which materials are recyclables; that is PE, PVC, or otherwise, it is reduced as compared with mixed waste collection method. Operational cost for sorting is also reduced. Buy-back centers are facilities that buy collected waste that has been cleaned, separated, and finally made available to be purchased by manufacturers. Government subsidies may be required to ensure this kind of industry and also to provide constant supply of the product [31]. Although it is the responsibility of government to deal with sanitation and environmental risks caused by garbage and litter, government subsidy should not be seen as an unwarranted or unnecessary expenditure when it comes to waste management issue.

192

Emmanuel Baffour-Awuah et al.

In the United States, for example, government subsidizes 20 US dollars per ton of material to ensure viability of buy-back facilities [33]. Drop-off technique is the cheapest of the collection methods. In the process, recyclate is sent to an installed, mobile, or remanufacturing plant facility by the waste originator. The disadvantage is that outcomes could be low and incalculable. It should be mentioned that the advent of advanced technology is changing the recyclate collection landscape in terms of technique and technical devices [33,50,51]. In Ghana sachet-water waste may be collected by individuals and sold to agents who then sell to manufacturing companies. The main technique used is the mixed waste collection method. In most cases, sachet-water waste may be collected at source, funeral grounds, parties, and such large scale occasions by waste pickers (referred as kachrawalas in India [48]). Waste may also be collected on streets and landfill sites or refuse dumps. The former is purer than the latter in terms of cleanliness of recyclate. Atsource collection by itinerant workers may also be conducted at households, shops, or offices (Kabaddiwalas in India) and resell to agents though this forms a small portion of the entire collection method [48]. Of late, some NGOs that deal with environmental issues appear to have become interested in placing collection bins at vantage points along streets and institutions encouraging sachet-water waste dumped alone and singularly for easy collection and minimal sorting procedures. It should be mentioned that various collection techniques which may be partly mixed waste collection and partly buy-back center at various proportions, within a curbside collection buy-back center technique space appear to be practiced in Ghana. For example, sachet-water waste may be collected from a refuse dump or landfill site (mixed waste collection) washed and packaged in a bag and sold to agents who then sell to the manufacturer (buy-back). Sorting of waste is done when commingled recyclates need to be recycled. It can be manual or automated (single-stream recycling), or both, throughout the entire sorting process [33]. In a typical automated recycling plant, commingled recyclates are usually transported to the facility in trucks. Large pieces of corrugated fiberboard and plastic bags are first removed by hand. The next stage involves separation of plastic and higher paper from metals and glass after which cardboard is separated from mixed paper. Cardboard and mixed paper are different in terms of quality since cardboard is a recycled product. Iron and steel are also separated from aluminum and tin cans using powerful magnetic spectra. The final sorting process involves sorting glass in terms of color using color filter automated mechanisms.

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

193

The benefit of this technique is that it helps reduce greenhouse emissions, conserves natural resources, reduces recyclable waste in landfills and incinerator, saves energy, and facilitates job creation [33,52,53]. Technology for sorting may vary within the complete manual and fully automatic spectrum. Technology in recycling industries in Ghana is deficient in advancement although current developments indicate entrepreneurs are making effort to upgrade the system [16]. Rinsing or washing is the simplest procedure in the entire recycling process before extrusion and pelletization (remanufacturing). Automated washing machines are employed in the process at facility. Washing may be done before crushing or shredding as in Ghana [16] or otherwise as in South Africa [37]. Sorting is effected in order to produce a homogeneous and pure recycled product. It may be done by color, resin, and grade (without regard as to whether recyclate is virgin, once recycled, or severally recycled). Manual sorting may recognize resins using sound when hit; appearance; smell after burning; and waste material reaction with specific solvents among others. Grade identification may also involve polymer hardness (recycled materials tend to be softer); and visual characteristics such as color and shininess. Biting with the teeth, as a technique, may be employed to determine the hardness of plastic waste. The health implication using such a technique somehow needs more to be desired [48]. It must be appreciated that manual sorting of waste sachet water is not as difficult since the shape of the sachet alone is enough for perfect identification. Grading may be done by feeling instead of biting. The informal sector may employ manual sorting. Remanufacturing processes include cutting, grinding, extrusion, and pelleting. During remanufacturing, virgin plastics may be mixed with recycled plastics in addition to various additives. Heating is accomplished during, and as a part of the extrusion process. Melting temperature may range between 150 C and 250 C for various polymer resins. Basically, an extruder consist of a screw within a cylinder that employs heat to melt the recyclate into a relatively homogeneous plastic strings (spaghetti-like shape) as it passes through. The hot plastic strings are then water-cooled and chopped into small pelletized product. Sink-floated, a process of immersing the ground recyclate in saline water may be employed before extrusion, to separate light and heavy fractions. While light fractions are pure, heavier fractions may contain other additives such as flame retardants, etc. [48]. It should be mentioned that obsolete and aged technology may affect the quality of recycled products produced in third world countries including Ghana [16,48].

194

Emmanuel Baffour-Awuah et al.

10.4.4 Method of sachet-water waste recycling Theoretically, sachet-water waste may be recycled using three common techniques, namely, mechanical recycling, feedstock recycling, and thermal recycling. Feedstock recycling includes monomerization; liquefaction; use as a blast furnace reducing agent; coke oven chemical feedstock by gasification; etc. Thermal recycling applications are found in cement kilns; refuse derived systems; solid recovered fuel (SRF); and refuse paper and plastic fuel (RPF). For the purpose of this discourse, mechanical recycling is discussed taking into consideration the objectives in context. The fundamental law for promoting the creation of a recycling-oriented society which was enacted in 2000 states that “the purpose of recycling is to restrict consumption of natural resources including petroleum and reduce to the minimum environmental burden through cyclical application of these resources” [43]. For this reason, any recycling method adopted must be seen to be reducing new resources as raw materials and further restrict environmental burden and boarding. Adopting a process depends on available technology and human resource to install, operate and maintain the systems involved. Mechanical recycling appears to be the only method adopted in Ghana. Technology currently available in the country well suits mechanical recycling although efforts are being made by investors to venture into other recycling techniques [16]. Mechanical recycling involves separation, sorting, size reduction, washing, extrusion, pelleting as well as bagging and delivery as earlier described under recyclate section of this work. PE-based waste such as empty mineral bottles and sachet-water waste may be turned into packaging materials, textiles, stationery, textile products, daily necessities, and the like. Beside extrusion and pelletization, formal and medium-to-large scale manufacturers may employ injection molding; blow molding, vacuum molding; and inflation molding to produce various products such as buckets and wash bowls; shampoo bottles; cups and trays; as well as films and shopping bags, respectively [43]. Investors in Ghana, who are largely small-to-medium scale manufacturers, may not have the technology to employ all these molding applications [16]. A model of recycling PE is shown in Fig. 10.2. Sachet-water waste may similarly be recycled and processed into the end products illustrated in the model, depending on availability of technology and human resource. The small scale informal sector only produce plastic pellets while the medium-tolarge scale manufacturers may go through all the recycling process to the production of end products.

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

Consumer

Recycling business

Textiles

Play your part in recycling resources

Recycling product manufacturing process

Pellets

Sheeting Ingestion molding

Compression

Raw cotton

Yarn

Formation into sheets

Vacuum molding

Workwear uniforms shirts

Fruit trays

Cleaning Molding

Assembly

Stationery office

Shredding

Selection

Bottles

Selection

Sewing

End product

Polyethylene plates

Municipality

Sorted collection

Melting/ spinning

195

Injection molding

Stretch blow molding

Detergent bottles for kitchen

Figure 10.2 From collection of PET bottles to recycling into new products. Source: Council for PET Bottling Recycling: in Trucost. Plastics and sustainability: a valuation of environmental benefits, costs, and opportunities for continuous improvement. American Chemistry Council. www.trucost.com; 2016.

10.4.5 Cost-benefit analysis of recycling Cost-benefit analysis of plastic recycling in general and PE in particular has been around job creation; capital and economic potential; as well as tax revenue and public health benefits [52]. In the United States, for example, more than 50,000 recycling establishments created over one million Jobs; and in New York City in 2006, an improved recycling program saved the city over 20 million dollars [52]. A study conducted by Linkup [54] outlined the numerous benefits of recycling. For example: although traditional textiles and manufacturing industries have lost appreciable number of jobs as a result of recycling, recycling continues to contribute in job creation while increasing its labor market share; and on a ton-to-ton basis, employment rates for recycling are high (10 times) than relying on landfills. According to various studies, in about 10 states in the United States, average waste disposal incomes and statewide average incomes are lower than recycling industry figures (States considered include California, Minnesota,

196

Emmanuel Baffour-Awuah et al.

Indiana, Washington, Jowa, Michigan, and North Carolina). Although jobs may be lost to the garbage collection and disposal industry as well as virgin materials manufacturing industry, only 13 jobs are lost in corresponding industries for every 100 jobs created due to recycled material processing and manufacturing; In spite of the fact that the rate of employment opportunities may stagnate within a specific period of time, constancy, or even slight reduction is comparatively better, as compared with virgin material industries. Plastic recycling in countries such as Japan, South Africa, India, and Ghana have also been established to contribute to job creation from collection of waste to manufacturing of end products [16,29,37,43,48]. In terms of capital investment and economic potential the Linkup [54] study outlined six benefits of recycling as follows. Despite that the recycling industry contributed only 2% of US gross domestic product (GDP) as reported by Velis [55], an amount of $4.6 billion was gained, increasing to $236 billion in 2007 which is more than twice the $100 billion garnered by the waste management industry. Although landfills and incineration have attracted capital investment from the private sector, latter development shows that the recycling industry been doing comparatively better presently with the exception of nonferrous metals, recycled plastics are next in terms of economic value of every ton of recyclate (recyclates include steel, nonferrous metals, paper and paperboard, electronics, and plastics). Recycling continues to receive increased and high investment rates in terms of facilities, equipment, and vehicles [Washington (the best positioned state in the States) in terms of recycling received such investments to the tune of $850 million by 2000]. In spite of the fact that the public sector lacks the ideal responsibility of investing in collection and processing activities to support private sector involvement in the industry, the success of the private sector in terms of industry achievement and economic benefits may have been largely due to the provision of public recycling programs. Material and infrastructure availability may also help establish opportunities for enhanced local investment in the recycling industry provided there is both political and economic will. However, the capital investment financial contribution and infrastructural development of the public sector of the industry in Ghana does not appear to be forth coming [16]. With the pursuance of one district-one factory (1D1F) policy in Ghana the government may intervene to provide guaranteed support in these areas to grow and develop the recycling industry. The Linkup [54] study finally outlines three benefits of recycling with reference to tax revenues and other public benefits. First, substantial amount can

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

197

be realized from recycling taxes to the benefit of both national government and local government authorities. For example in the United States in 2000, about $12.9 billion were galvanized from local, state, and federal tax revenues. Second, there could be substantial contribution of taxable revenues and wages to national, regional, state, and local economies. Such contributions are usually indirectly realized. Thirdly and finally, besides tax revenues, recycling contributes in diverse ways to national and local economies. These include benefits and cost savings accrued from greenhouse gas reductions; diversion and disposal cost savings; reduced pollution; and reduced energy consumption. When quantified, the benefits of recycling to the environment and public health can be immeasurable [55,56]. Benefits of recycling in terms of public health may include revenues accrued from sale of recycled materials; reduced necessity for subsidies for covering virgin materials extraction; costs; energy savings and higher income levels; the rest are: amount diverted from landfill and disposal fees, as well as carbon off sets.

10.5 The way forward The PE recycling industry in Ghana might be described as small and young, and therefore could be fraught with many challenges. Availability of recyclates which begin from waste collection; legislation to support the industry; and technology to facilitate the industry are some but the major challenges facing the industry. Quality recycled products are manufactured from quality recyclates. A good program of sachet-water waste collection can be a panacea to ensuring quality recycled products. In ensuring this objective a program that focuses on collection systems and recyclate adulteration; sorting facilities, which may include material selection and transparency; and benchmarking and standardization of recyclate quality. A program of such nature which encompasses waste management, should aim at encouraging the collection of recyclate by both private and public organizations. To ensure good quality recyclates before reaching the plant facility, curbside collection, buy-back centers, and drop-off centers should be introduced when appropriate since all these collection methods have distinguished advantages and benefits. As far as curbside collection is concerned source separation method could be more appropriate, economical, less time consuming, and

198

Emmanuel Baffour-Awuah et al.

savings of energy in sorting at the plant facility. Depending on availability, however, the other methods of curbside collection; commingled recyclables; and mixed waste collection may equally be adopted. Unarguably, the private sector is the main body responsible for waste collection in Ghana. Capital is very important in terms of equipment for waste collection and separation at the point of waste creation. Managing waste at this point, therefore, is capital intensive. As part of a program of this nature public sector involvement to create requisite financial infrastructure and technological infrastructure is more than pertinent. A stakeholder meeting with the appropriate public institutions such as the ministry in charge of environment and rural development to assess the appropriate required needs of firms (ZoomLion, a waste management organization in Ghana) and individuals, for example, will be a step in the right direction. It appears there are no regulations on plastic recycling in Ghana, and this is very unfortunate considering the fact that the plastic economy is an integral and inseparable component of the fourth industrial revolution. There is the need for established regulations on standardization and benchmarking if the fourth industrial revolution is to succeed in the country. It is well-known fact that regulations are not an end in itself; but rather implementation, compliance, and enforcement. Industry players and responsible public and academic institutions could come together and formulate standards and benchmarks with reference to household market; industrial disposal of waste; industrial quality control; recyclable product quality; equipment functional status inspection controls; and demand- and supply side product quality controls. In sum, total quality control should be the aim of benchmarking and standardization in the industry. Government may also entrust standardization and benchmarking responsibility to professional organizations such the Ghana Standards Board & Ghana Institution of Engineers to formulate such a document. As already indicated, bodies such as Ghana Standards Authority (GSA) and Ghana Institution of Engineers (GhIE) can also be entrusted with implementation, monitoring, and supervision of the regulations. It is a fact that plastic wastes are exported to other countries. This is partly due to unavailability of capital in terms of technology. Government can circumvent this unfortunate practice by providing financial avenues to entrepreneurs who are already in the recycling business and those who have the passion and acumen to venture into the business. Provision of soft loans, as well as availability and accessibility of such loans, will go a

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

199

long way to alleviate this practice. Adding value to this raw material may contribute positively in terms of job creation, tax revenues, and GDP growth levels to the Ghanaian economy. The contribution of tax revenues to local and national government economies could be quite significant. Investment in the recycling industry in terms of vehicles, equipment, and facilities could also be a means of equitable distribution of national resources in terms of financial circulation and economic systems. Particularly in the informal (collection) sector, individuals in the industry usually belong to the lower level income earners, perhaps lower class of the economy. Adequate investment and proper policies when adopted and implemented to the letter can be a means to absolving poverty. It is a truism that the engagement of sachet and bottled water by the Ghanaian society has brought about environmentally unsustainable conditions which need to be dealt with. It is also true that these sources of water cannot be banned since both the general public and the beverage industry have given a cold shoulder to the idea. Local government appear to be of the view that a better alternative should be put in place before a ban is thought about, which as a matter of course, is not available in the near future. Introduction of commensurate taxes to introduce and support cleanup programs have also appear to have been vehemently repulsed by the general public, including patrons of the product and the beverage industry. Although a fund has been introduced, the allocation of this resource is likely to encounter strenuous difficulties. As a necessary evil the society need to find ways of dealing with the negative aspects of the product. Adopting recycling could be one way by which waste that packaged water leaves in its trail could be handled. Recycling could therefore be in the best interest of the environment, public health and the economy of Ghana. As far as the informal sector is concerned equipment used in the industry can be very crude. This may affect product quality. Due to obsolete and first generation equipment used by the informal sector, challenges such as heterogeneous mixing, overheating that brings about plastic decomposition, as well as inadequate and excessive quantity of additives may be encountered. The end product could become deficient in terms of quality. Moreover, informal manufacturers may lack instruments and equipment for measurements to ensure the minimum quality assurance. Providing financial mechanisms to support, in this regard can help boost the plastic recycling economy. Regular training programs for stakeholders and waste generators, through waste collection to end product users will

200

Emmanuel Baffour-Awuah et al.

be a step in the right direction. The need for recycling should be a pronounced theme of such programs. In Ghana mechanical recycling appears to be the only type of plastic recycling method practiced. However, there are other techniques that are economically viable. Techniques such as feedstock and thermal recycling when introduced can help reduce the amount of plastics that end up in landfills, incinerators and oceans, lagoons ponds, and other natural sinks. Even with mechanical recycling, other options such as candidate composite formation, using PE and vegetal fiber such as palm fruit fiber, have not been explored although research in this area is a recent development and a potential toward waste management and environmental pollution control. A national program that focuses on exploration of the traditional methods such as feedstock and thermal recycling could be rethought. Funding research programs that also focuses on up-and-coming technologies such as biocomposite formation could expand the scope of recycling in Ghana. Such sponsorship programs could be funded by the public, private, public private partnerships, and international organizations that have environmental issues at heart. When designing laws to regulate recycling, the roles of consumers, businesses, municipalities, and government must be well clarified, specified, and explicit enough. In promulgating a law of this nature the roles, duties, and responsibilities and penalties of law defaulters such as exporters, dismantlers, shredders, manufacturers and importers, handling agents, and the like should be properly emphasized. Declaring a year as the beginning of plastic recycling-oriented society; introduction of material labeling; and identification marks to facilitating waste collection and sorting should be included in the law. Enforcement of the electronic gadget waste management law will also contribute immensely to the benefit of the entire economy.

References [1] United Nations Development Group. Indicators for monitoring the millinium development goals. New York, NY: United Nations; 2003. [2] WHO/UNICEF. Drinking water: equity, safety and sustainability. Geneva: World Health Organization; 2011. [3] WHO/UNICEF. Progress on drinking water and sanitation, 2012 update. Geneva: World Health Organizations; 2012. [4] Chen C, Ravallion M. More relatively-poor people in a less absolutely-poor world. Policy Research Working Paper 6114, The World Bank Development Research Group; 2012.

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

201

[5] Benin Quick Facts. The borgen project. https://borgenproject.org/10-facts-aboutpoverty-in-benin/; 2013 [accessed 10.09.2017]. [6] Halving Global Poverty. An update of the World Bank’s estimates of consumption: poverty in the developing world. Development Research Group, World Bank; 2012. [7] United Nations Programme. 2015 Ghana millennium development goals report. www.gh.undp.org; 2018 [accessed 10.09.2018]. [8] WHO/UNICEF Joint Monitoring Platform. 2017. UN sustainable development goals. Inter-Agency and Expert Group. washdata.org. [9] Onda K, LoBuglio J, Bartram J. Global access to safe water: accounting for water quality and the result access to safe water: accounting for water quality and the resulting impact on MDG progress. Int J Environ Res Public Health 2012;9:880 94. [10] Bain RES, Guntoy SW, Wright J, Yaug H, Pedoley S, Bartram JK. Accounting for water qualifying in monitoring the millennium development goal on access to safe drinking-water: lessons from five countries. Bull World Health Organ 2012;90:228 35. [11] Ahimah JK, Ofosu SA. Evaluation of the quality of sachet water vended in the New Juaben Munciipality of Ghana. Int J Water Resour Environ Eng 2012;4(5):134 8. [12] Cheabu BSN, Ephraim JH. Sachet water quality in Obuasi, Ashanti Region, Ghana. J Biol Agric Health Care 2014;4(5):37 42. [13] Little RJ. The state of sachets: Ghana’s private sector solution to a public infrastructure problem. PitzerSeniorTheses, Baper 62. http://scholarship.calaremont.edu/pitzer-theses/62; 2015 [27.07.2018]. [14] Nyeadi JD, Vidana N, Atongenzoya CA. Assessing the compliance of sachet water producers to regulatory standards in Ghana: a study of Tamale Metropolis. Int J Innov Res Dev 2014;3(6):426 36. [15] Wright J, Dzedzomenyo M, Wardrop NA, Johnston R. Effects of sachet water consumption on exposure to microbes contaminated drinking water: household survey evidence from Ghana. Int J Environ Res Public Health 2015;13:303. Available from: https://doi.org/10.3390/ijerph.13030303. [16] Addei E. The wealth of plastic recycling; A comparison between plastic recycling companies in Accra and one in Gauteng, South Africa, for improvement purposes. BA Thesis submitted to Department of Business Administration, Ashesi University, Ghana; 2016. [17] Guggsa TB. The cycle of solid waste: a case study on the informal plastic and metal recovery system in Accra. Sweden: Upsalla University, Department of Earth Sciences; 2012. [18] Stoler J, Weeks JR, Finks G. Sachet drinking water in Ghana’s Accra. Tema Metropolitan area past, present, and future. J Water Sanit Hyg Dev 2012;2:223 40. [19] Ezeokpube ND, Obiora CJ, Phil-Eze PO. Environmental problems of sachet waters waste disposal in Nsukka Urban, Enugu State, Nigeria. Civ Environ Res 2014;6(1):105 13. [20] Kassenga GR. The health-related microbiological quality of bottled drinking water sold in Dar es Salaam. Tanzania. J Water Health 2006;5:179 86. [21] GSS. Pattern and trends of poverty in Ghana (1991 2006). Accra, Ghana: Ghana Statistical Service; 2006. [22] Stoler J. The sachet water phenomenon in Accra: socioeconomic, environmental and public health implications for water security. In: Weeks JR, Hill AG, Stoler J, editors. What if neighbors' neighborhoods differ? The influence of neighborhood definitions of health outcomes in Accra. 2013. p. 181 90. [23] Jambeck JR, Geyer R, Wilcox C, Siegler TR, Perryman M, Andrady A, et al. Plastic waste inputs from land into the ocean. Science 2015;347(6223):768 71. Available from: https://doi.org/10.1126/science.1260352. [24] Natural Environment. Natural environment white paper implementation update report. Department for Environment, Food and Rural Affairs, UK. www.gov.uk/ defra; 2014 [accessed 27.07.2018].

202

Emmanuel Baffour-Awuah et al.

[25] Moore J. Synthetic polymers in the marine environment: a rapidly increasing, longterm threat. Environ Res 2008;108(2):131 9. [26] Baffour-Awuah E. Health implications of polluted tilapia consumption The perception of Fosu Lagoon fishermen in Cape Coast, Ghana. J Environ Earth Sci 2014;4(10):78 86. [27] Ryan, A.J. Plastic packaging is often pollution for profit. Eco Business. https://www. eco-business.com/opinion/plastic-packaging-is-often-pollution-for-profit/; 2017 [accessed 10.09.2017]. [28] Gregory M. Environmental implications of plastic debris in marine settingsentanglement, ingestion, smothering, hangers-on, hitch-hiking and alien invasions. Philos Trans R Soc 2016;B-364(1526):2013 25. [29] Trucost. Plastics and sustainability: a valuation of environmental benefits, costs, and opportunities for continuous improvement. American Chemistry Council. www.trucost.com; 2016. [30] The League of Women Voters. The garbage primer. New York, NY: Lyons & Burford; 1993. p. 35 72. [31] Black Dog Publishing. Recycle: a source book. Westerville: American Ceramic Society; 2006. [32] Charlesson A, Reich M. Resource efficient plastic recycling-Instruments of control and obstacles in relation to the producer responsibility. http://www.lansforsa00000 resursseffektivplastatervinning.pdfkrinar.se/globalasets/aaglobal/document/ovright/aamass/forskning/; 2002 [accessed 27.07.2018]. [33] Cleveland CJ, Morris CF. Handbook of energy chronologies, top ten lists, and word clouds. Burlington: Elsevier; 2013. [34] The Economist. The truth about recycling. Technology Quarterly. https://www. economist.com/technology-quarterly/2007/06/09/the-truth-about-recycling; 2017 [accessed 10.09.2017]. [35] Hoornweg D, Perinaz P. What a waste: a global review of solid waste management. worldBank. http://hall.handle.net/10986/17388; 2012 [accessed 27.07.2018]. [36] Plastics South Africa. Plastics recycling in South Africa. http://www.plasticsinfo.co. za/wpcontentt/uploads/2015/006/Executive-Summary-May-2015;-pdf; 2015 [accessed 27.07.2018]. [37] McKenzie M. Plastic recycling in South Africa. Urban Earth. http://wwwurbanearth.co.za/articles/plastis-recycling-southafrica; 2012 [accessed 27.07.2018]. [38] Green Times. Country leads the world in plastic recycling. The Green Times. http://thegreentimes.co.zacountry-leasthe-world-in-plastic-recycling; 2014 [accessed 27.07.2018]. [39] Sander K, Schilling S, Tojo N, Chris van Rossem C, Vernon J, George C. The producer responsibility principle of the WEEE Directive. European Council. http://ec. europa.eu/environment/waste/weee/pdf/final_rep_okopol.pdf; 2007 [accessed 10.09.2017]. [40] Recyclate. Web dictionary. https://www.thefreedictionary.com/recyclate; 2013 [accessed 27.07.2018]. [41] Freudenrich A. How plastics work. https://www.scribd.com/document/405411288/ How-Plastics-Work-docx; 2014 [accessed 27.07.2018]. [42] DEFRA. Quality action plan proposals to promote high quality recycling of dry recylates. Department of Environment, Food and Rural Affairs, UK. www.defra.gov. uk; 2013 [accessed 10.09.2017]. [43] Plastic Waste Management Institute. An introduction to plastic recycling. Japan: Plastic Waste Management Institute; 2009. [44] The Scottish Government. Recyclate quality action plan-consultation paper. https:// www.webarchive.org.uk/wayback/archive/20160121042659mp_/http://www.gov. scot/Resource/0040/00404123.pdf; 2012 [accessed 27.07.2018].

Recycling of polyethylene: an attempt to sachet and bottled water sustainability in Ghana

203

[45] The Highland Council. Charges for the collection and disposal of commercial waste and the hire of waste skips - 2011/12. Report by Director of Transport, Environmental and Community Services. http://docplayer.net/25344041-The-highland-council-transport-environmental-and-community-services-committee-18-november-2010.html; 2013 [accessed 10.09.2017]. [46] Haarman A. Towards sustainable plastic recycling in India: experiences from the field. India: Sustainable Recycling Industries; 2015. [47] Nkwachuku O, China C, Ikenna A, Lackson A. Focus on potential environmental issues on plastic world towards a sustainable recycling in developing countries. Int J Ind Chem 2013;4:34. [48] SRI. Towards sustainable plastic recycling in India: experiences from the field. India: Sustainable Recycling Industries; 2015. [49] Essabra-Mensah E. Malaria costs economy over US$735 million annually. Business and International Times. http://thebftonline.com/business/economy/16236/malariacosts-economy-overus735m-annually.html; 2015 [accessed 27.07.2018]. [50] Kreigler MA, Mulder ML, Glover AG, Pearce JM. Life cycle analysis of distributed recycling of post-consumer high density polyethylene for 3-D printing filament. J Clean Prod 2014;70:90 6. Available from: https://doi.org/10.1016/j.jclepro. 2014.02.009. [51] Miller L, Soulliere K, Sawyer-Beaulieu S, Tseng S, Tam E. Challenges and alternatives to plastics recycling in the automotive sector. Materials 2014;7:5883 902. Available from: https://doi.org/10.3390/ma7085883None. [52] Anonymous. Best recycling programs in the U.S. and around the world. www.cmfg. com; 2013. [53] United States Environmental Protection Agency. Jobs through recycling (JTR) initiative. Region 10: The Pacific Northwest. http://ysemite.epa.gov/r10/02cm.nsf/ 1e905ifc4619cec588256500005b5e90/aaeea44562988256515005750d!opeendoc; 2008 [accessed 10.09.2017]. [54] Linkup. Recycling and economic development: a review of existing literature on Job creation, capital investment and tax revenues. Linkup King Country Solid Waste Division. http://your.kingcounty.gov/solidwaste/linkup/index.asp; 2009 [accessed 27.07.2018]. [55] Velis CA. Global recycling markets - plastic waste: a story for one player China. Report prepared by FUELogy and formatted by D-waste on behalf of International Solid Waste Association - Globalisation and Waste Management Task Force. ISWA, Vienna; 2014. [56] Minnesota Pollution Control Agency. Minnesota’s recycling industries: economic activity Summary. State of Minnesota; 2002.

CHAPTER ELEVEN

Sustainability and survivability in manufacturing sector Ankita Awasthi1, Kuldeep K. Saxena2 and Vanya Arun1 1

College of Engineering and Technology IILM, Greater Noida, India Institute of Engineering and Technology, GLA University, Mathura, India

2

11.1 Introduction The concept of sustainability was coined between 1970s and 1980s. The need for sustainability arose due to series of events, environmental crisis, and disasters which took place during the decades of 1960 80 and brought the environmental crisis in the world. In 1987, definition of sustainability was proposed in Brundtland report which stated that unnecessary changes are occurring in atmosphere, soil, water, forest, and animal habitat [1]. Nature is rigid but at the same time it is also very fragile and we need to keep it in line and balanced. There are some threshold points which need to be avoided. If they are crossed then nature and its species which are being exploited will be in endanger. Today those threshold points are not far off. Sustainability means elimination of exploitation of nature without compromising the creativity and innovation for continuous development [2]. The sustainable development is one that meets the expectations of human desires without neglecting the existence and needs of futuristic generations. During the United Nation World Summit on sustainable development, which was held Johannesburg, South Africa in the year 2002, a declaration was passed and subsequently adopted which called for the implementation of holistic sustainable development by integrating three independent but mutually connected entities: • Environmental and ecological balance • Economic development • Social development These three entities are most indispensible terms which reinforce the sustainable development [3]. The approach to sustainable development is Modern Manufacturing Processes. DOI: https://doi.org/10.1016/B978-0-12-819496-6.00011-7

© 2020 Elsevier Ltd. All rights reserved.

205

206

Ankita Awasthi et al.

related with three P’s which means meeting the expectation of People, earning Profit, and saving the Planet earth without degrading the life and survivability. The manufacturing sector has a significant impact on country’s socioeconomic growth and development. As the population is increasing exponentially, the demand for goods and better services are on the high. According to demand-supply law, sellers and buyers of the goods and services interact in order to maintain the equilibrium of price, reduce inflation, and provide easy availability without neglecting the quality [3]. Thus manufacturing plays the most critical role in this modern and progressive world where it will help in generating wealth, profit, jobs, safety, and security. However, the significant activities of manufacturing industry have overburdened the environment. According to Indian brand equity foundation report, the estimated worth of manufacturing sector was US$ 395.89 billion during the financial year 2018 19, but estimated carbon emission footprints has increased by 1.73% since 2013 which is at its highest level [4] (Fig. 11.1). The sustainable manufacturing deals with minimizing the impact of manufacturing over the ecology by characterizing its actions. The manufacturing sector is upgraded and modified in terms of systems and processes without neglecting its performance and environmental sustainability. A system is not characterized as sustainable if it is wasting the natural resources, creating wastage, and destroying the environment. Actually sustainable system is a close system where whatever you take from system; you will get by the system. So sustainability and manufacturing can mutually exist giving priority to environmental balance and economic growth. Environmental concern is raised time to time for restricting the manufacturing activities by implementing the regulations and policies for holistic sustainable approach.

Figure 11.1 Three pillars of sustainability.

Sustainability and survivability in manufacturing sector

207

11.2 Elementary concepts of sustainability in manufacturing The term manufacturing has business quotient as well as socioeconomic values. A well-established firm can work with subsystems like (production, planning, scheduling, machining, controlling, quality, transportation, etc.) for the profits and also helping the environment to attain sustainability. Manufacturing is a process in which available resources are input (machines, manpower, material, money) of the system to create products which are market ready [5]. But climate change, global warming, and excessive carbon emission has created an adverse effect on the both environment and the society. The most popular and widely accepted definition on sustainability was given by “Brundtland commission,” chaired by Gro Harlem Brundtland. The conclusion of this summit was compiled and presented in report “our common future.” This definition was proposed by renowned business leaders and technologist with a common goal to attain progressive society with social equality, protection of environment, and scaling of economy [6]. The most relevant definition in terms of engineering is proposed by Miheleic et al. who states that “systems are designed in terms of industry and natural habitat for better quality of life without harnessing the natural resources, loss of environment, and human health.” One of the definition was proposed by United States, Department of Commerce, which states that “sustainable manufacturing and development is the creation of manufacturing product without creating any adverse impact on environment, preservation of natural resources, and environment” [7] (Fig. 11.2).

11.2.1 Metrics The term metrics is used for measuring the sustainability performance in both qualitative and quantitative way for both manufacturing system and processes. The main purpose of metrics is to optimize the decision making ability of the manufacturing industry. For implementing the metrics in sustainability the integration of three parameters are needed to be characterized and qualified. Ideally metrics include comprehensive detailing of parameters which can influence and control the economy and society of any developing country. A review is proposed on sustainability methodologies by Singh et al. which is accepted globally [3]. He presented the assessment on the basis of indices and rating. The framework is created by United Nations Division of Sustainable Development (UNDSD) where metrics are initially

208

Ankita Awasthi et al.

Figure 11.2 Interaction between environments, socio-economic with other components.

mapped with sustainable parameters (ecological balance, social equality, and economic development), then with subsystem (education and technology) [8,9]. Over the past few years, environment is degrading at alarming rate in terms of polluted air quality, toxicity in vegetation, severe energy crisis, etc., which captures the attention. The United Nations Environment Program (UNEP) has compiled the sustainability indices worldwide. This data is important for measuring the sustainability index and system performance. Parris et al. has proposed 12 major initiative for social sustainable metrics which helps in evaluation of sustainability index. 1. United Nations Commission on Sustainable Development 2. Consultative Group on Sustainable Development Indicators 3. Wellbeing Index 4. Environmental Sustainability Index 5. Global Scenario Group 6. Ecological Footprint 7. Genuine Progress Indicator 8. US Interagency working Group on Sustainable Development Indicators

Sustainability and survivability in manufacturing sector

209

Costa Rica System of Indicators for Sustainable Development Boston Indicators Project State Failure Task Force Global Reporting Initiative (Figs. 11.3 11.5) In order to develop sustainable system in manufacturing system, it is essential to consider manufacturing cost, waste management, and energy utilization along with three fundamental pillars Environment, Social, and Economic relevance [10]. According to report published by leading automobile company general motors, for value addition in business, it is necessary to take measures for sustainability in order to facilitate innovation and growth simultaneously to obtaining common growth of the system [11] (Fig. 11.6). 9. 10. 11. 12.

11.2.2 Evaluation of manufacturing system performance A performance of a manufacturing system can be evaluated when it is mapped with three important parameters. The most common approach to reduce and minimize the environmental deterioration is applying environmental management system (EMS). The EMS is an organizing body which continuously monitors, controls, and takes corrective actions against the insignificant activities done by manufacturing system. Any manufacturing firm is required to operate with ISO 14001-14004 standards which standardized, implemented, and controlled the risk and ensures the compliance with relevant environmental activity. These standards can record and report any activity which is harmful to the environment happening in firm and it only focus on continuous improvement of environmental performance [4] (Fig. 11.7).

Figure 11.3 Sustainable development goal.

210

Ankita Awasthi et al.

Creativity, education and technology index

Development index

Market-and economy-based index

Eco-system-based index

Composite sustainability performance index for industries

Investment, ratings, and asset management index

Summary of creativity index Investment in the education-based economy Performance in the education-based economy creativity index National creative capacity IT and Telecommunication technologies based sector Technology growth parameter index General indicator of science and technology Human development index Index of sustainable and ecollomic welfare Relative intensity of regional problems in the community (by the EC)

Internal market parameter assessment method Business climate assessment Labour performance calculator Composite leading index Genuine savings index! indicator (GSs) Economic sentiment Index Net national product (EDP) and SEEA

Sustainability performance assessment method Ecological index Planet index Ecological footprint index

Composite sustainability development and performance index ITT sustainable assessment method G score assessment method

Sustainable asset measurement management switzerland Dow Jones sustainability group index (DJSGI), United States Corporate sustainability index United States petroleum refineries Environmental risk index, United Kingdom Investor responsibility research centre (IRRC), Washington, DC, United States Council on economic priority (CEP), New York, United States

Figure 11.4 Sustainability assessment methodologies [Part A].

The life cycle assessment is the most popular technique for environmental evaluation in manufacturing industry. The ISO14040 has introduced the term life cycle assessment which escalates the aspects and effects of the process to the environment, starting from raw material to final product and

211

Sustainability and survivability in manufacturing sector

Investment, ratings, and asset calculator index

Jupiter income trust funds, United Kingdom. Goods index assessment Fund and bank assessment, Switzerland Environmental value fund, Oslo, Norway. Innovest strategic value advisors Environment rating assessment method

Life cycle index European ford product sustainability index

Product-based sustainability index

Sustainability index for metropolitan cities

Environmental effect assessment (policies, nations, regions)

Urban sustainable assessment method Sustainable development index method for Taipei City growth index Compost index of sustainable development Urbano performance calculator Sustainable developing index, Seattle

Environment sustainability and quality index Environmental problems impact assessment method Environment policy performance method Environment vulnerability assessment method Two methods of calculating the synthetic environmental index

Ecological point method Ecological compass method 99 methods for ecological-index calculator Environment technology assessment

Environment assessment method for industries

Energy-based index

Index calculation for quality of life and social relevance

Sustainable assessment method for calculating energy of the system Assessment of energy for sustainability in developed and developing countries

Gender empowerment measurement technique Quality of life index Human health and well-being measurement techniques National health and care systems Overall health monitoring and index method Sustainable society assessment

Figure 11.5 Sustainability assessment methodologies [Part B].

212

Ankita Awasthi et al.

Environment factor assessment Green house gas emissions (kg CO2 eq./unit) Amount of renewable energy used (%) Water consumption rate annually (kg/unit) Energy consuming rate

Labour cost unit wise ($/unit) Energy meter cost ($/unit) Maintenance of energy based instruments cost ($/unit) Waste assessment measurement method Chemical contamination of working environment (mg/m") Mist/dust level (mg/m^ Physical load index (dimensionless)

Economical assessment Energy usage yearly (kWh/unit) Calculation of total energy usage for workability (kWh/unit) Total energy consumption for industry (kWh/unit) Safety measurement

Wide exposure to toxic chemical Rate of physical accident

Health monitoring system assessment Total mass deposition (kg/unit) Recycle ratio (%)

Figure 11.6 Potential sustainable manufacturing process metrics.

then recycling and further disposal in landfills. According to ISO system, a life cycle assessment involves four important parameters: 1. Objective 2. Defining scope 3. Inventory requirement and its analysis 4. Interpretation and output In this process relevant data is collected and resources are allocated on the basis of its objective and scope [12,13] (Fig. 11.8).

11.3 Manufacturing process In this, highly competitive and progressive world where industrial development is continuously growing, from industrial revolution to machine age and then to automation, this has changed the industrial

Sustainability and survivability in manufacturing sector

213

Figure 11.7 Assessment cycle in manufacturing industry.

Figure 11.8 Parameters which effect manufacturing sector.

scenario. Now new techniques and processes are adapted by industries in order to mechanized and automate the manufacturing firms. Manufacturing is the process where goods, products, and services are made to meet the human needs and expectations. Raw material or scrap

214

Ankita Awasthi et al.

is converted into finished product by adding value in it such as shape, size, surface finish, quality, etc. [2]. A large number of manufacturing processes can be applied to raw materials in different ways to satisfy the needs of customer. Manufacturing process can be classified as following: 1. Primary processes 2. Secondary processes 3. Advance processes Primary metal shaping process: In this, material is shaped in proper shape and size by applying simple tool and technique. They are most easy process which does not require highly skilled labor with average dimensional tolerance. Example: Casting, metal forming (rolling, extrusion, forging, etc.), joining (welding, soldering, brazing, etc.). Secondary metal shaping process: Secondary manufacturing process can be applied after primary manufacturing process just to enhance the mechanical properties through recrystallization, dimensional tolerance, release thermal stresses, etc. Sometimes product shape can be resized and reshaped with the help of machine. Example: Machining and heat treatment process. Advance manufacturing process: Here variety of new methods and techniques are applied in order to remove material from the product or raw material in a very little amount. A close dimensional tolerance is achieved with excellent surface quantity. But advance processes are expensive and require high precision [14]. Example: Powder metallurgy, additive manufacturing, and 3D printing.

11.3.1 Measures taken in manufacturing process •

•

Primary metal shaping process such as casting creates hazardous gas and when hot molten metal is poured in, molds oxide fumes are released that create pollutants. There are some measures which are required in casting where permanent casting molds are required. Improvement in the quality of sand, sand binders, relief from thermal stresses, and heat affected zone (HAZ) are also required. The reutilization of fused casting will reduce the emission of greenhouse gases and eliminate the requirement of surface finish and machining therefore it will directly reduce the cost [15,16]. In metal forming process, different types of tools and lubricants are used to facilitate the forming process. The excessive use of lubricant

Sustainability and survivability in manufacturing sector

•

•

•

215

on machine will increase the CO2 emission but increase the efficiency of machines. This can be avoided by using forming tools (single point), laser processing will increase the installation cost but have after benefits on environment. The use of integrated die coating can also improve the life of dies and reduce the amount of coolant applied on it. Machining process is material removal process. It requires energy to tear out metal chips from the metal surface. Machining is very useful in part designing and process planning. Many chemicals and lubricants are used for managing heat balance in tool; compensate tool wear, cooling, etc. But these synthetic lubricants create an adverse impact on environment by dissipating heat, increase nitrogen level around the machine working envelope. This can be minimized by using the scarps, fused metals which reduce the energy consumption and release of dangerous gases [17]. Additive manufacturing, powder metallurgy, and rapid prototyping are some of the most promising technologies but they also degrade the air quality by use of low sintered powder which is low grade in quality. Additive manufacturing machines use electricity which increases the energy requirement and high precision machine manufacturing requires advanced technology for fabrication [18]. For surface finishing and close tolerance, part is risen in chemical bath, lubricant, coolant, coating of paints, etc. But they can promote toxic environment and affect the sustainability by releasing the cadmium and highly injurious chemicals in river without proper waste treatment (Fig. 11.9).

11.4 Survivability of a communication network With the coming of cheap and free internet and industry 4.0, one cannot discard the role of communication network in today’s manufacturing process. The ease of remote location operation is only possible through the communication network. The so called remote operations are now covered under the category of IOT and industry 4.0. It is now an established fact that survivability of the communication network is needed in order to eliminate the data loss that occurs during the fiber cut. As we all know that the backbone of any communication network is optical fiber. Hence our data is carried out by the optical fiber network.

216

Ankita Awasthi et al.

Figure 11.9 Root cause of imbalance and analysis to achieve sustainability.

In a fully automated environment the command to operate the assembly line, the output data, the input data, and the storage and access of the data related to the manufacturing process can be given remotely through the network. If the system is sustainable there will be no wastage of resources. This automation completely depends upon the communication lines for its commands. Sometimes due to fiber cut this valuable data is lost which results in the reduced efficiency of the sustainable system. Survivability of network is an important parameter. A network is said to be a survivable network when it continues to work even when a fiber cut occurs. Two important methods namely protection and restoration are used to make the optical network survivable. Network protection means a predefined backup path and wavelength is assigned to the already existing path. So in case of a failure, the entire data path is changed and the data traffic is

Sustainability and survivability in manufacturing sector

217

diverted to the already assigned backup path. In case of network restoration, the backup path is not predefined but a new route is discovered then and there by utilizing different algorithms for the data traffic (in case of a fiber cut). The recovery of a link in case of a protection method is very fast because the redundant path is already predefined but in case of network restoration method the recovery is slow. However the later method (restoration method) is very cost effective as the resources are optimally utilized, whereas in case of protection method the resources are wasted as most of the time the predefined link sits ideal.

11.5 Challenges in sustainable development In spite of much advancement in technical field, research, and innovation many challenges still remain. The extensive research is required in restricting the CO2 emission [19]. So it is essential to develop such machine mechanism which reduces the ecological footprints by understanding the process and parameters of equipments. The main purpose of any new machine design is to reduce the energy and resource consumption. Some conclusive strategies are required to be formulated in order to improve working environment, right size of the machine design, up gradation of new mechanism, less usage of lubrication, coolants, etc. Manufacturing system should reconstruct them in terms of minimal waste production and dumping zones; recycling and recreational facilities should be installed in manufacturing firms [20,21]. This facility should be designed is such a way that it requires lesser energy consumption, proper management of machines lead time, etc. In order to increase the life cycle of the product, product recovery and material utilization system should be developed properly. Sometimes both forward and backward line assembly system can also reduce the total time and enhance the production. Sustainable environment can improve the quality of life without compromising the quantity and quality of production [22]. A conclusive knowledge should be imparted to future engineers and students who can explore and contribute in the field of sustainable development. The broader understanding of social, economic, and environmental impact is necessary in order to know the critical aspects of sustainability. It is a closed system where all the basic needs such as product, material, and services are managed in a most sustainable manner [23].

218

Ankita Awasthi et al.

References [1] Brundtland GH. Our common future. New York, NY: Oxford University Press; 1987. [2] Singh RK, Murty HR, Gupta SK, Dikshit AK. An overview of sustainability assessment methodologies. Ecol Indic 2012;15(1):281 99. [3] Feng SC, Joung C, Li G. Development overview of sustainablemanufacturing metrics. In: Proceedings of the 17th CIRP international conference on life cycle engineering, Hefei, PRC; 2010. [4] Parris TM, Kates RW. Characterizing and measuring sustainable development. Annu Rev Environ Resour 2003;28(1):559 86. [5] Brent A, Labuschagne C. Social indicators for sustainable project and technology life cycle management in the process industry (13 pp 1 4). Int J Life Cycle Assess 2006;11(1):3 15. [6] Mihelcic JR, Crittenden JC, Small MJ, Shonnard DR, Hokanson DR, Zhang Q, et al. Sustainability science and engineering: the emergence of a new metadiscipline. Environ Sci Technol 2003;37(23):5314 24. [7] Klugman J. Human development report 2010 20th anniversary edition. The Real Wealth of Nations: Pathways to Human Development; 2010. [8] Jawahir IS, Dillon OW. Sustainable manufacturing processes: new challenges for developing predictive models and optimization techniques. In: Proceedings of the first international conference on sustainable manufacturing, Montreal, Canada; 2007. p. 1 19. [9] Parrish BD. Sustainability-driven entrepreneurship: principles of organization design. J Bus Venturing 2010;25(5):510 23. [10] Jawahir IS, Dillon OW, Rouch KE, Joshi KJ, Venkatachalam A, Jaafar IH. Total life-cycle considerations in product design for sustainability: a framework for comprehensive evaluation. In: Proceedings of the 10th international research/expert conference, Barcelona, Spain; 2006. p. 1 10. [11] Dreher J, Lawler M, Stewart J, Strasorier G, Thome M. General motors: metrics for sustainable manufacturing, laboratory for sustainable business, Massachusetts Institute of Technology, Cambridge, MA. ,http://actionleaming.mit.edu/files/slab_files/ Projects/2009/GM,%20report.pdf.; 2009 [accessed 19.06.12]. [12] Hischier R, Weidema B, Althaus H-J, Bauer C, Doka G, Dones R, et al. Implementation of life cycle impact assessment methods, final report ecoinvent v2.2 No. 3. In: SwissCentre for Life Cycle Inventories, Dubendorf, Switzeriand; 2010. [13] ISO. ISO 14040:2006, Environmental management—life cycle assessment-principles and framework. Geneva: Intemational Organization for Standardization; 2006. [14] Herrmann C, Schmidt C, Kurle D, Blume S, Thiede S. Sustainability in manufacturing and factories of the future. Int J Precis Eng Manuf-Green Technol 2014;1(4):283 92. [15] Kusi-Sarpong S, Gupta H, Sarkis J. A supply chain sustainability innovation framework and evaluation methodology. Int J Prod Res 2019;57(7):1990 2008. [16] Madanchi N, Thiede S, Sohdi M, Herrmann C. Development of a sustainability assessment tool for manufacturing companies. Eco-factories of the future. Cham: Springer; 2019. p. 41 68. [17] Yacob P, Wong LS, Khor SC. An empirical investigation of green initiatives and environmental sustainability for manufacturing SMEs. J Manuf Technol Manag 2019;30(1):2 25. [18] Giret A, Trentesaux D, Prabhu V. Sustainability in manufacturing operations scheduling: a state of the art review. J Manuf Syst 2015;37:126 40. [19] Harik R, El Hachem W, Medini K, Bernard A. Towards a holistic sustainability index for measuring sustainability of manufacturing companies. Int J Prod Res 2015;53(13):4117 39.

Sustainability and survivability in manufacturing sector

219

[20] Ford S, Despeisse M. Additive manufacturing and sustainability: an exploratory study of the advantages and challenges. J Clean Prod 2016;137:1573 87. [21] Govindan K, Jha PC, Garg K. Product recovery optimization in closed-loop supply chain to improve sustainability in manufacturing. Int J Prod Res 2016;54 (5):1463 86. [22] Chen L, Olhager J, Tang O. Manufacturing facility location and sustainability: a literature review and research agenda. Int J Prod Econ 2014;149:154 63. [23] Mani M, Madan J, Lee JH, Lyons K, Gupta SK. Characterizing sustainability for manufacturing performance assessment. In: ASME 2012 International design engineering technical conferences and computers and information in engineering conference. American Society of Mechanical Engineers; 2012. p. 1153 1162.

Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A AACF. See Areal autocorrelation function (AACF) ABAQUS software, 147 ABC-correlation model, 23 ABS. See Acrylonitrile butadiene styrene (ABS) AC. See Alternating current (AC) Acoustic emission signals (AE signals), 31 32 Acrylonitrile butadiene styrene (ABS), 132 Activated carbon, 69 70 CSA application as, 72 74 Additives, 69 71, 74 75 Advanced high strength steels (AHSS), 145 147 Advanced manufacturing techniques for composite structures, 212 compression molding, 9, 9f HLU method, 7 8, 7f molding techniques, 6 7 PMC, 3 5 processing methods, 5 6 RTM method, 8, 8f vacuum bagging, 10, 10f VERTMTy, 10 11, 11f AE signals. See Acoustic emission signals (AE signals) AFM. See Atomic force microscope (AFM) Agricultural solid waste, 77 AHSS. See Advanced high strength steels (AHSS) AISI H13 steel tool, 81 82 Alpha grain’s volume fraction, 101 102 Alternating current (AC), 45 46 Alternative solid-state welding process, 43 44 Aluminum (Al), 43 44 Aluminum alloy, 76 AA7075 aluminum alloy, 32 33 Al7075-T651 aluminum alloy, 31

Aluminum matrix composite (AMC), 76 Analysis of variance (ANOVA), 76, 139 140, 158, 164 Area measurements, 17 19 Area-based methods, 24 Areal autocorrelation function (AACF), 27 28 Arrhenius-type formula, 98 99 Artificial fractal structures, 17 19, 18f ASS. See Austenitic stainless steel (ASS) Atomic force microscope (AFM), 24 25 Austenitic stainless steel (ASS), 97 chemical composition, 100t computerized UTM, 101f constitutive models, 106 107 constrained optimization, 119 120 assessment of experimental versus predicted data, 122f, 123f experimental and predicted correlation coefficient values, 124f, 125f, 126f EDS report for fractured surfaces, 110f, 111f, 112f, 113t, 114t JC model, 116 117 material and experimental details, 100 101 material constants, 115t microstructure examination and fractography, 101 106 optical micrographs, 103f representative fractured test workpiece, 102f result, 120 126 statistical parameters, 124t, 125t Zerilli Armstrong model, 119 Automated washing machines, 191 Automotive manufacturing, 43 5-Axix machines, 169 flow of commands for, 169 170, 170t

B Ball-milling method, 76 77

221

222

Beta phase’s volume fraction, 101 102 Blanket method, 24 Box-counting method, 17 20, 19f, 29 Bragg’s equation, 89 92 Brass ANOVA and regression equation, 164 chemical composition of investigated brass, 160t materials and methods, 159 162 ASTM-E8M tensile test, 159f experimental plan, 159 161 experimental setup, 161 162 tensile specimen orientation standard specimen, 159f work piece preparation, 159 process parameters and levels, 160t results, 162 163 design matrix, 160t experimental setup, 161f variation of %EL with velocity for variables, 164f variation of YS with velocity for different variables, 163f Brass alloy, 157 158 Brownian motion methods, 17 19 Brundtland commission, 205

C Carbon dioxide, 181 182 Carbonic materials, 74 75 Carbonized coconut shell ash (CCSA), 79 Ceramic matrix composites, CS application in, 76 79 CSA and Elemental composition of CSA, 82f variability in chemical content of coconut shell particles, 79t in elemental composition of coconut shell particles, 79t Ceramics, 3 Charcoal, CSA application as, 72 74 Chlorine (Cl), 71 72 Chopped strand mats, 5 Clamp pressure system, 135 Clamping force, 47 49

Index

pressure, 132 CNC. See also Multiaxis CNC programming and machining machine cells, 168 169 programmer, 173 Coconut shell (CS), 69 70 application as concrete reinforcement, aggregate, and as filler, 70 72 global percentage of coconut, 70f XRD measurement data, 90t application in metal, polymer, and ceramic matrix composites, 76 79 coconut shell particle application as water purification and heavy metals removal, 74 75 friction stir processed Al7075/CCSA characterization, 82 84 materials and methods, 79 82 friction stir processing methodology, 80 81 materials collection and preparation, 80 81 NC-controlled FSW machine, 83f XRD experimental specification, 83t SEM fractography of Al7075, FSPed Al7075, and FSPed Al7075/CCSA, 88f structural evaluation analysis, 89 92 surface integrity evaluation for processed samples, 87 89 surface roughness analysis measurement, 89t tensile behavior, 84 87 Coconut shell ash (CSA), 69 70 application as activated carbon or as charcoal, 72 74 Coconut shell charcoal (CSC), 73 74 Coherent diode laser system, 134 Complex tool path, 174 Composite laminate prototypes, 9 manufacturing process, 6 7 materials, 3 Compression molding, 9, 9f Concrete reinforcement, coconut shell as, 70 72 Confirmation test, 158

223

Index

Constitutive equation, 99 100, 106 107, 117 118 Constitutive models, 106 107 KHL, 111 116 m-FB, 107 110 Copper (Cu), 43 44 Copper zinc alloy (Cu Zn alloy), 157 158 Correlation function, 25 Cost-benefit analysis, 193 195 CS. See Coconut shell (CS) CSA. See Coconut shell ash (CSA) CSC. See Coconut shell charcoal (CSC) Curing process, 4, 6 Cutting depth in milling operation, 31

D 1D1F. See One district-one factory (1D1F) 2,4-DCP. See 2,4-Dichlorophenol (2,4DCP) Demand-side legislation, 186 DFA. See Tagushi desirability functional analysis (DFA) 2,4-Dichlorophenol (2,4-DCP), 75 Differential box counting method, 19 20 Dimension, 14 15 of conventional geometries, 15f Dislocation (DSs), 101 102 Doping of metals, 74 75 Drop-off technique, 190 DSA. See Dynamic strain aging (DSA) DSs. See Dislocation (DSs) Dynamic strain aging (DSA), 97

E EBSD analysis. See Electron backscatter diffraction analysis (EBSD analysis) EDS. See Energy-dispersive X-ray spectroscopy (EDS) %EL. See Percentage elongation (%EL) Electric vehicles (EVs), 43 Electron backscatter diffraction analysis (EBSD analysis), 60 64, 63f EMS. See Environmental management system (EMS) Energy generation, 69 70

Energy-dispersive X-ray spectroscopy (EDS), 56 59, 72, 76 Al Cu binary phase diagram, 59f images of weld interfaces, 60f Environmental management system (EMS), 207 Epoxies, 5 Estrogen malfunction, 181 182 EVs. See Electric vehicles (EVs) Excellent corrosion resistance, 97 Exothermy, 6

F FB model. See Fields and Bachofen model (FB model) fBm. See Fractal Brownian motion (fBm) Feedstock recycling, 192 Fields and Bachofen model (FB model), 98 FIS. See Fuzzy interface system (FIS) Fisher’s ratio, 139 140 Flat punch test. See Marciniak test FLC. See Forming limit curve (FLC) FLD. See Forming limit diagram (FLD) Flow curve stress, 118 Flow stress model equation, 107 110 Flow stresses, 162 Fluid film lubrication, 148 Forming limit curve (FLC), 152 153 foil thickness effect on, 152 153 rolling direction effect on, 151 152 Forming limit diagram (FLD), 145 147, 149 150 measuring strains for different thicknesses and rolling directions, 150t Fourier-transform infrared spectroscopy (FTIR), 76 77 Fractal analysis, 13 14 in friction stir, 32 34 in laser manufacturing, 29 31 in machining, 31 32 in manufacturing, 24 34 in thin films, 24 29 Fractal Brownian motion (fBm), 20 21 Fractal dimension, 15, 23 methods of computing, 17 24 Fractal geometry, 13

224

Fractal theory in modern manufacturing, 13 14 definition and properties, 14 17 methods of computing fractal dimension, 17 24 Fracture surface morphology, 52 53, 52f Freundlich isotherm, 75 Friction stir, fractal analysis in, 32 34 Friction stir processed Al7075/CCSA characterization, 82 84 structural integrity of Al7075/CCSA, 83 surface integrity evaluation, 84 tensile analysis, 83 84 Friction stir processing (FSP), 79 81 surface roughness tester, 85f tensile sample sectioning from processed zone, 84f Friction stir welding (FSW), 32 33 FSP. See Friction stir processing (FSP) FTIR. See Fourier-transform infrared spectroscopy (FTIR) Full width at half maximum (FWHM), 89 92 Fuzzy interface system (FIS), 76

G G0926 5H satin weave carbon fabric, 10 11 Galamsay, 180 GDP. See Gross domestic product (GDP) GFRG. See Grey-fuzzy reasoning grade (GFRG) Ghana Institution of Engineers (GhIE), 196 Ghana sachet-water waste, 190 Ghana Standards Authority (GSA), 196 Ghana Water Company Limited (GWCL), 180 GhIE. See Ghana Institution of Engineers (GhIE) Global warming, 181 182 Grey relational analysis, 140 Grey relational coefficient, 134 Grey relational grade (GRG), 76 Grey relational theory, 133 Grey-based Taguchi method, 133 134, 141t

Index

response table for grey relational grade, 142t Grey-fuzzy reasoning grade (GFRG), 76 GRG. See Grey relational grade (GRG) Gross domestic product (GDP), 194 GSA. See Ghana Standards Authority (GSA) GWCL. See Ghana Water Company Limited (GWCL)

H Hand lay-up (HLU) method, 6 8, 7f Heat affected zone (HAZ), 212 Heat exchangers, 30 31 Heavy metals removal, coconut shell particle application as, 74 75 Hemispherical punch test. See Nakajima test Hexcel RTM6 Epoxy resin, 10 11 Higuchi algorithms, 33 Hot pressed composite laminate, 9 Hurst exponent/index, 21, 21f Hyperbolic law, 118

I IMCs. See Intermetallic compounds (IMCs) Indium-doped zinc oxide (IZO), 25 IZO/glass, 25 Indium-doped zinc oxide/indium tin oxide (IZO/ITO), 25 Indium-doped zinc oxide/silicon (IZO/Si), 25 Intermetallic compounds (IMCs), 43 44 Inverse power law, 23 Iron, 190 191 Iron (III) oxide (Fe2O3), 71 72 Isarithm method, 24 IZO. See Indium-doped zinc oxide (IZO) IZO/ITO. See Indium-doped zinc oxide/ indium tin oxide (IZO/ITO) IZO/Si. See Indium-doped zinc oxide/ silicon (IZO/Si)

J JC model. See Johnson Cook model (JC model)

225

Index

Johnson Cook model (JC model), 98, 116 117, 117t Joints mechanical analysis of, 49 53 microstructural analysis of, 53 64

K Khan and Huang (KH) model, 99 Khan Huang Liang (KHL) model, 99, 111 116, 116t Koch curve, 15, 16f Korcak’s empirical relationship, 24

L LABs. See Low angle boundaries (LABs) Land filling, 182 Lap-shear pull test, 136 137 Laser additive manufacturing, 30 31 CO2, 29 30 deposition, 13 14 fractal analysis in laser manufacturing, 29 31 Laser scanning confocal microscope (LSCM), 29 30 Laser transmission welding process, 131 132 confirmation test results, 142t experimental work, 135 137 laser welding setup used for experimental works, 135f selected process parameters and levels, units, and notations, 136t grey-based Taguchi method, 133 134 multiobjective optimization, 140 142 parametric analysis, 137 140 PMMA-ABS sample, 136f Lateral drive spot welding system, 45 46 LCM. See Liquid composite molding (LCM) Lead zirconatetitanate (PbZnTi), 45 46 Life cycle assessment, 208 210 Limiting dome height (LDH) test, 145 148 Linear logarithmic relationship, 19 20 Liquefied natural gas (LNG), 157 158 Liquid composite molding (LCM), 7 8

Lithium-ion (Li-ion) batteries, 43 mechanical analysis of joints, 49 53 fracture surface morphology, 52 53, 52f microhardness, 50 52, 52f tensile and T-peel strength results, 49 50, 51f microstructural analysis of joints, 53 64 EBSD analysis, 60 64 EDS analysis, 56 59 optical microscopy of weld crosssection, 53 64, 54f SEM of fracture surface, 56 TEM analysis, 64 XRD analysis, 59 60 process parameters, 47 49 USW process, 44 45 system, 45 47 LNG. See Liquefied natural gas (LNG) Long fiber thermoplastic composites manufacturing methods, 4 Low angle boundaries (LABs), 101 102 LSCM. See Laser scanning confocal microscope (LSCM)

M m-Arr equation. See m-Arrhenius type equation (m-Arr equation) m-Arrhenius type equation (m-Arr equation), 117 118, 119t m-FB. See Modified Fields Backofen (mFB) m-ZA model. See Zerilli Armstrong model (m-ZA model) Machining, fractal analysis in, 31 32 Magnesium oxide (MgO), 71 72 Manufacturing, 205, 210 212 process, 210 213 measurement, 212 213 root cause, 214f sector, 204 parameters which effect, 211f system evaluation, 207 210 assessment methodologies, 208f, 209f potential sustainable, 210f Marciniak test, 145 147

226

Material models, 99 Matrix, 3 MDG. See Millennium development goals (MDG) Mechanical disc-milling, 80 81 Metal forming process, 212 213 Metals, 3 CS application in, 76 79 doping, 74 75 matrix composites, 69 70 MgO. See Magnesium oxide (MgO) Microforming, 145 147 experimental investigations, 147 153 comparison of forming limit curves, 153f experimental setup, 148 FLD, 149 150 foil thickness effect on forming limit curve, 152 153 limiting dome height test, 147 148, 149f rolling direction effect on forming limit curve, 151 152 specimen for uniaxial, plane, and biaxial strain path, 148f surface strain measurement, 148 Microhardness, 50 52, 52f Millennium development goals (MDG), 177 Modified Fields Backofen (m-FB), 107 110, 113t Modified PDM methods, 23 24 Mold filling phase, 6 Molding techniques, 6 7 Molecular diffusion, 131 132 Molybdenum (VI) oxide (MoO3), 71 72 Mountains Map Software, 31 32 Multiaxis CNC programming and machining continuous improvement without editing, 174 175 complex tool path, 174 cutting tool path, 175 integrating CNC and automation, 168 169 5-axis machining, 169

Index

numerical control of machine tools, 167 168 validation, 170 174 diagrams point position, 171f Multiobjective optimization, 140 142

N Nakajima test, 145 147 Natural fractal structures, 17 19, 18f NC. See Numerical control (NC) Network, 213 215 Nitrogen adsorption process, 75 Nitrogen oxides, 181 182 Numerical control (NC), 167, 172f

O One district-one factory (1D1F), 194 Optical microscopy of weld cross-section, 53 64 of AA 6061/Cu weld samples, 54f fractured surfaces of USW Al and Cu samples, 57f high magnification optical microscopy images of Al tabs, 55f Orthogonal array, 133

P Parametric analysis, 137 140 ANOVA for weld strength, 139t for weld width, 140t experimental array with measured results of weld strength and weld width, 137t main effects plots of welding parameters on weld width, 138f Parametric analysis, 137 140 ANOVA for weld strength, 139t for weld width, 140t effects plots of welding parameters on weld width, 138f experimental array with measured results of weld strength and weld width, 137t PCBBs. See Polychlorinated biphenyls (PCBBs)

227

Index

PDM. See Power differentiation method (PDM) PE. See Polyethylene (PE) Percentage elongation (%EL), 162 PET. See Polyethylene terephthalate (PET) Phenolics, 5 PHILIPS X’Pert machine, 83 Pixel-covering method, 32 33 Plastic deformation, 50 52 PLC. See Portevin-Le Chatelier (PLC) PMC. See Polymer matrix composites (PMC) Polychlorinated biphenyls (PCBBs), 183 Polyesters, 5 Polyethylene (PE), 178, 193f Polyethylene terephthalate (PET), 187 188 Polyimides, 5 Polymer, 3 CS application in, 76 79 reinforcement, 76 77 Polymer matrix composites (PMC), 3 5, 73 74 Polypropylene (PP), 73 74, 187 188 Polystyrene (PS), 187 188 Polyurethane (PUR), 5, 187 188 Polyvinyl chloride (PVC), 187 188 Portevin-Le Chatelier (PLC), 97 Potassium hydroxide (KOH), 75 Potassium oxide (K2O), 71 72 Power differentiation method (PDM), 23 24 Power spectral density functions (PSDFs), 23 24, 28 29 Power spectrum method, 23 24, 31 Power time curve, 47 49 PP. See Polypropylene (PP) Primary metal shaping process, 212 PS. See Polystyrene (PS) PSDFs. See Power spectral density functions (PSDFs) Pultrusion methods, 6 PUR. See Polyurethane (PUR) PVC. See Polyvinyl chloride (PVC)

Q Quality loss, 133

R Recyclable materials, 184 Recyclates, 187 189 Recycling of polyethylene, 178, 184 195 cost-benefit analysis of, 193 195 legislation, 184 187 plastics waste, 188f processes, 189 191 recyclates, 187 189 water PE-packaging, 180 183 Refuse paper fuel (RPF), 192 Refuse plastic fuel (RPF), 192 Regression analysis, 23 Regression equation, 164 Reinforcement, 3, 92 fiber, 5 mat architecture, 6 Remanufacturing processes, 191 Resin cure kinetics, 6 Resin gelation time, 6 Resin transfer molding method (RTM method), 6 8, 8f Resin viscosity, 6 RMS. See Root mean square (RMS) Rolling direction effect on forming limit curve, 151 152 Root mean square (RMS), 25 26 Rovings, 5 RPF. See Refuse paper fuel (RPF); Refuse plastic fuel (RPF) RTM method. See Resin transfer molding method (RTM method)

S S/N ratio. See Signal-to-noise ratio (S/N ratio) Sachet water, 177 178 in Ghana, 179 180 waste recycling method, 192 Scanning electron microscope (SEM), 24 25, 44, 71 72 of Al side, 61f of fracture surface, 56 for fracture surface, 104f, 105f, 106f, 107f, 108f, 109f images of weld interfaces, 60f SEM-EDX, 76

228

Scanning electron microscope (SEM) (Continued) of weld interfaces at different weld time, 58f Scherrer techniques, 83 SDG. See Sustainable Development Goal (SDG) Secondary metal shaping process, 212 Self-similar characteristics, 13 14 SEM. See Scanning electron microscope (SEM) Separation vector, 21, 22f Sheet metal forming process, 145 147 Sierpinski carpet, 16, 17f Sierpinski gasket, 15 16, 17f Sierpinski sponge, 17, 18f Signal-to-noise ratio (S/N ratio), 133 Silicon dioxide (SiO2), 71 72 Sodium oxide (Na2O), 71 72 Solid recovered fuel (SRF), 192 SPARTAN-II Lite RTM Machine model of GlasGraft, 8 SRF. See Solid recovered fuel (SRF) Steel, 190 191 Stir-casting experiment, 76 Structural evaluation analysis, 89 92 XRD structural pattern for tested samples, 91f Styrene, 5 Sulfur oxides, 181 182 Surface roughness analysis measurement, 89t tester, 84 Surface strain measurement, 145 148 Survivability of communication network, 213 215 Sustainability in manufacturing sector challenges in, 215 elementary concepts, 205 210 interaction between environments, socio-economic, 206f metrics, 205 207 sustainable development goal, 207f manufacturing process, 210 213 pillars of sustainability, 204f Sustainable development, 203 Sustainable Development Goal (SDG), 178

Index

T Taguchi L16 orthogonal array, 136 Taguchi method, 132, 136, 140 of robust design, 133 Tagushi desirability functional analysis (DFA), 76 Talysurf PGI 1240 profiler, 31 32 TEM analysis. See Transmission electron microscopy analysis (TEM analysis) Tensile and T-peel strength results of joints, 49 50, 51f Term manufacturing, 205 Term metrics, 205 207 Thermal expansion algorithms, 168 169 Thermal recycling applications, 192 Thermoplastic PMC, 4 Thermoset PMC, 4 Thermoset resins, 4 Thin films, fractal analyses in, 24 29 Three dimensional simulations (3D simulations), 145 147 Three-dimensional printing (3D printing), 13 14 Topography, 24 25, 29 30 Transmission electron microscopy analysis (TEM analysis), 64, 65f, 72. See also Scanning electron microscope (SEM) Triangular prism method, 24 2D fast Fourier transform (2D-FFT), 23

U Ultimate tensile strength (UTS), 158 Ultrasonic energy, 45 47 Ultrasonic spot welding (USW), 43 44 joint, 47 49 process, 44 45, 45f system, 45 47 lateral drive spot welding system, 45 46, 46f wedge-reed spot welding system, 46 47, 47f Ultrasonic welding process, 47 49 UNDSD. See United Nations Division of Sustainable Development (UNDSD)

229

Index

UNEP. See United Nations Environment Program (UNEP) Uniaxial tensile tests, 158 Unimproved water source, 177 178 United Nations Division of Sustainable Development (UNDSD), 205 207 United Nations Environment Program (UNEP), 205 207 Universal testing machine (UTM), 161 162 Unsaturated polyester resins (UP resins), 5 UP resins. See Unsaturated polyester resins (UP resins) USW. See Ultrasonic spot welding (USW) UTM. See Universal testing machine (UTM) UTS. See Ultimate tensile strength (UTS)

V Vacuum bagging, 10, 10f Vacuum enhanced resin transfer molding technology (VERTMTy), 10 11, 11f Variance method, 132 Variation method, 31 Variogram method, 21 23

W Water purification, 69 70 coconut shell particle application as, 74 75

Wavelet algorithms, 31 32 Welding parameters, 132, 141 142 Well-established firm, 205 Williamson hall formula, 89 92 Wire cut electric discharge machine (WEDM), 159 Wire-cutting electro-discharge machining process, 100 Woven rovings, 5

X X-ray diffraction (XRD), 59 60, 76 77, 89 92 analysis on weld cross-section, 62f experimental specification, 83t measurement data, 90t structural evaluation analysis, 89 92 X-ray fluorescence (XRF), 71 72, 76 Xforce P-type Zwick/Roell Z250 Tensile tester, 83 84

Y Yarns, 5 Yield strength (YS), 158

Z Zener Hollomon parameter, 118 Zerilli Armstrong model (m-ZA model), 119, 120t Zinc chloride (ZnCl2), 75 Zinc sulfide (ZnS), 26 27