Industry 4.0 Value Roadmap: Integrating Technology and Market Dynamics for Strategy, Innovation and Operations [1st ed. 2019] 978-3-030-30065-4, 978-3-030-30066-1

Table of contents :
Front Matter ....Pages i-xvii
Introduction (Tuğrul U. Daim, Zahra Faili)....Pages 1-3
Literature Review (Tuğrul U. Daim, Zahra Faili)....Pages 5-13
Enablers: Industry 4.0 (Tuğrul U. Daim, Zahra Faili)....Pages 15-24
Problem Statement (Tuğrul U. Daim, Zahra Faili)....Pages 25-25
Methodology (Tuğrul U. Daim, Zahra Faili)....Pages 27-28
Value Roadmap Development for Automotive Industry (Tuğrul U. Daim, Zahra Faili)....Pages 29-53
Value Roadmap Development for Healthcare Industry (Tuğrul U. Daim, Zahra Faili)....Pages 55-73
Value Roadmap Development for Telecommunication Industry (Tuğrul U. Daim, Zahra Faili)....Pages 75-100
Conclusion (Tuğrul U. Daim, Zahra Faili)....Pages 101-104
Limitations and Future Research (Tuğrul U. Daim, Zahra Faili)....Pages 105-105
Back Matter ....Pages 107-118

Citation preview

SPRINGER BRIEFS IN ENTREPRENEURSHIP AND INNOVATION

Tuğrul U. Daim Zahra Faili

Industry 4.0 Value Roadmap Integrating Technology and Market Dynamics for Strategy, Innovation and Operations 123

SpringerBriefs in Entrepreneurship and Innovation

Series Editors David B. Audretsch School of Public & Environmental Affair, Indiana University Bloomington, IN, USA Albert N. Link Department of Economics, University of North Carolina at Greensboro Greensboro, NC, USA

More information about this series at http://www.springer.com/series/11653

Tuğrul U. Daim • Zahra Faili

Industry 4.0 Value Roadmap Integrating Technology and Market Dynamics for Strategy, Innovation and Operations

Tuğrul U. Daim Department of Engineering and Technology Management Portland State University, Portland, OR, USA

Zahra Faili Technical University of Hamburg Hamburg, Germany

National Research University Higher School of Economics, Moskva, Russia Chaoyang University of Technology, Taichung, Taiwan

ISSN 2195-5816     ISSN 2195-5824 (electronic) SpringerBriefs in Entrepreneurship and Innovation ISBN 978-3-030-30065-4    ISBN 978-3-030-30066-1 (eBook) https://doi.org/10.1007/978-3-030-30066-1 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Abstract

Industry 4.0 has been one of the latest concepts which has altered as well as disrupted the business model of organizations around the world. The adoption, however, has been slow in various industries as a clear roadmap for the integration of the same lacks in project planning. Hence, the main purpose of this thesis is to develop a value roadmap for three different industries: Automotive, Healthcare, and Telecommunication so to satisfy the market demand. The value roadmap for these three sectors is developed by taking into consideration five various factors which are market drivers, product features, technology features, enablers, and resources. Finally, these five factors are combined to form the final value roadmap. The roadmap is also segregated into two timelines which are short term and long term. For the evaluation of the value roadmap, views of experts from different organizations have been put into use. Keywords  IoT, Value roadmap, Quality function deployment

v

Acknowledgments

This work is partially funded by the Basic Research Program of the National Research University Higher School of Economics (HSE) and by the Russian Academic Excellence Project “5-100.”

vii

Contents

  1 Introduction����������������������������������������������������������������������������������������������    1   2 Literature Review������������������������������������������������������������������������������������    5   3 Enablers: Industry 4.0 ����������������������������������������������������������������������������   15   4 Problem Statement����������������������������������������������������������������������������������   25   5 Methodology ��������������������������������������������������������������������������������������������   27   6 Value Roadmap Development for Automotive Industry����������������������   29   7 Value Roadmap Development for Healthcare Industry ����������������������   55   8 Value Roadmap Development for Telecommunication Industry��������   75   9 Conclusion������������������������������������������������������������������������������������������������  101 10 Limitations and Future Research����������������������������������������������������������  105 Appendix: Survey��������������������������������������������������������������������������������������������  107 References ��������������������������������������������������������������������������������������������������������  109

ix

List of Figures

Fig. 1.1 Industrial revolution timeline������������������������������������������������������������������ 2 Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 2.5

Schematic of technology roadmap—traditionally���������������������������������� 6 Key identified challenges of TRM���������������������������������������������������������� 7 Generic S&T roadmap���������������������������������������������������������������������������� 8 Value roadmap concept ������������������������������������������������������������������������ 11 VRM process mapping ������������������������������������������������������������������������ 13

Fig. 3.1 Telecom big data analytics framework ������������������������������������������������ 17 Fig. 5.1 Flowchart of value and technology roadmap���������������������������������������� 28 Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 6.4

Roadmapping of market drivers—automotive�������������������������������������� 34 Roadmapping of product features—automotive ���������������������������������� 40 Roadmapping of technology features—automotive ���������������������������� 49 Roadmapping of enablers—automotive������������������������������������������������ 52

Fig. 7.1 Fig. 7.2 Fig. 7.3 Fig. 7.4

Roadmapping of market drivers—healthcare �������������������������������������� 58 Roadmapping of product features—healthcare������������������������������������ 64 Roadmapping of technology features—healthcare������������������������������ 70 Roadmapping of enablers—healthcare ������������������������������������������������ 72

Fig. 8.1 Fig. 8.2 Fig. 8.3 Fig. 8.4

Roadmapping of market drivers—telecommunication ������������������������ 79 Roadmapping of product features—telecommunication���������������������� 88 Roadmapping of technology features—telecommunication���������������� 97 Roadmapping of enablers—telecommunication���������������������������������� 99

Fig. 9.1 Value and technology roadmap—automotive ������������������������������������ 102 Fig. 9.2 Value and technology roadmap—healthcare�������������������������������������� 103 Fig. 9.3 Value and technology roadmap—telecommunication������������������������ 104

xi

List of Tables

Table 2.1 Roadmap classification based on objectives ������������������������������������������ 9 Table 6.1 Market drivers evaluation—automotive������������������������������������������������ 33 Table 6.2 Product features—automotive�������������������������������������������������������������� 35 Table 6.3 QFD matrix for market drivers versus product features—automotive���������������������������������������������������������������������������� 41 Table 6.4 Technology feature—automotive���������������������������������������������������������� 42 Table 6.5 QFD matrix for technology features versus product features—automotive���������������������������������������������������������������������������� 51 Table 6.6 QFD matrix for enablers versus technology features—automotive���������������������������������������������������������������������������� 53 Table 7.1 Market drivers evaluation—healthcare ������������������������������������������������ 57 Table 7.2 Product feature—healthcare������������������������������������������������������������������ 58 Table 7.3 QFD matrix for market drivers versus product features—healthcare ���������������������������������������������������������������������������� 64 Table 7.4 Technology feature—healthcare ���������������������������������������������������������� 65 Table 7.5 QFD matrix for technology features versus product features—healthcare ���������������������������������������������������������������������������� 71 Table 7.6 QFD matrix for enablers versus technology features—healthcare ���������������������������������������������������������������������������� 73 Table 8.1 Market drivers evaluation—telecommunication ���������������������������������� 79 Table 8.2 Product feature—telecommunication �������������������������������������������������� 80 Table 8.3 QFD matrix for market drivers versus product features—telecommunication �������������������������������������������������������������� 89 Table 8.4 Technology feature—telecommunication �������������������������������������������� 90 Table 8.5 QFD matrix for technology features versus product features—telecommunication �������������������������������������������������������������� 98 Table 8.6 QFD matrix for enablers versus technology features—telecommunication ������������������������������������������������������������ 100 Table 9.1 Comparison between three evaluated sectors—value and technology roadmap �������������������������������������������������������������������� 104

xiii

Nomenclature

AAR Audio augmented reality ABS Anti-lock braking system AFSA Artificial fish swarm algorithm AH Authentication header protocol AM Additive manufacturing ATV All-terrain vehicle BCM Body control module BP Blood pressure C-ART Connected autonomous road transport CDPD Cellular digital packet data COPD Chronic obstructive pulmonary disease CRRM Cognitive radio resource management CT Computed tomography DARPA Defense advanced research projects agency DCF Discounted cash flow EAP Extensible authentication protocol ECG Electrocardiogram EDA Electrodermal activity EGR Exhaust gas recirculation EMG Electromyogram ENEC Emerson network energy center EPS Evolved Packet System ESC Electronic stability control ESP Encapsulated security payload EWOD Electrowetting on dielectric FCD Floating car data FHRP First hop redundancy protocol FRN Fixed relay node GDP Gross domestic product GMR Giant magnetoresistance xv

xvi

Nomenclature

HCP Health care professional HetNet Heteregeneous network HMD Head mounted display HR Heart rate IC Integrated circuits IC engine Internal combustion ICT Information and communications technologies IEA International Energy Agency IoT Internet of Things IPComp IP payload compression protocol ITS Intelligent Transport Systems LED Light-emitting diode Li-Fi Light fidelity LiPF6 Lithium hexafluorophosphate LOS Line of sight LTE Long-term evaluation MCM Mass customization manufacturing MIMO Multiple-in, Multiple-out MODV Modular vehicle MRI Magnetic resonance imaging MRN Moving relay node NAC Network access control NLPRS Network layer packet redundancy scheme NPV Net present value NTP Non-thermal plasma OECD Organization for Economic Co-operation and Development OEM Original equipment manufacturer PAN Polyacrylonitrile PHEV Plug-in hybrid electric vehicle PM Predictive maintenance PMR Professional mobile radio PRP Parallel redundancy protocol PSS Public safety and security QFD Quality function deployment QoE Quality of Experiences R&D Research and Development RAN Radio access network RC Redundancy controller RHMAS Remote health monitoring and alert system RMBI Remote machine–brain interface RRM Radio resource management RTC Road traffic crashes S&T Science and Technology SCR Selected catalytic reduction SPA Scalable product architecture

Nomenclature

TRM Technology roadmapping VAD Virtual auditory display VANET Vehicular ad hoc network VBTO Virtual-build-to-order VoIP Voice over Internet Protocol VRM Value roadmapping WAP Wireless access points WAVE Wireless access in vehicular environment WBAN Wireless body area network WBSN Wireless body sensor network WDM Wavelength division multiplexing WEP Wireless equivalent privacy WSN Wireless sensor network

xvii

Chapter 1

Introduction

The first drastic change in terms of manufacturing process occurred in the beginning of nineteenth century which is then referred to industry 1.0. In that concept, the mechanical mass production was introduced. One of the key characteristics of that era was the increase in the production capability and business growth (Rojko 2017; Petri 2017). One of the main drivers for the first industrial revolution was the improvement in terms of living quality. While industry 2.0 was concerned with the resource allocation and utilization as well as mass production, it was in the beginning of twentieth century that electricity was become the main source of power. During that time, other improvements were made as well such as division of labor, which resulted in increased productivity. Also, mass production came into place. Although this era was involved with possibility of mass production, the mass products’ customization was not present. The famous quote from Henry Ford with respect to the Ford T-Model vouched for that when he mentioned that the customers can have any car color as long as it is black (Rojko 2017). It was all till the last few decades of twentieth century that electronic devices were invented and the key technology enablers were: digital power or in another words, the introduction of transistors, integrated circuits (IC) which made the automation possible and was known as industry 3.0 (Raut 2016). Microelectronics and automation made the manufacturing and production line more flexible (Rojko 2017). Outcome of industry 3.0 was perceived to increase the living standards and global industrial development.

1.1  Fourth Industrial Revolution The fourth industrial revolution was initiated by the vast development of Information and Communications Technologies (ICT). Advanced connectivity and smart automation of the cyber-physical systems are the main technological features. At present, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_1

1

2

1 Introduction

Industry 1.0 "Mechanization"

Mechanical equipment operating with water/steam power

Industry 2.0 "Electrifciation"

Mass production carried out by labor division and electrical energy

Industry 3.0 "Automation"

Automation of production with IT and emergence of electronics

Industry 4.0 "Automization"

Cyber physical production based on the IoT and services

Fig. 1.1  Industrial revolution timeline (Petri 2017)

the fourth industrial revolution can be referred differently in different regions. For instance, in the USA, it is known as Smart/Advanced Manufacturing. Mass customization is one of the key enablers and drivers for the fourth industrial revolution which is making a shift from the traditional “pull from the market” to “pull from the customer.” The benefit of this business strategy results in the higher customer’s need satisfaction by the provided individualized solutions/services (Petri 2017). The industrial transition is represented in Fig. 1.1 which describes the development involved in industrial manufacturing from its traditional manual work all the way to a smart automation known as industry 4.0. In traditional manufacturing, the companies were very much reluctant in integrating the technological advancement and were very slow in terms of reacting to the same. The fourth generation in industrial evolution is believed to represent a vision for an interconnected and online factory where the decisions can be made intelligently (Raut 2017). It is worth highlighting that today’s manufacturing is transforming from its traditional mass production to mass customization as characterized by the industry. With all rapid change of connected devices and the abundant amount of data, the technology landscape shall remain adapted. Technology is perceived to be one of the elementary drivers for the innovation existing in today’s world and the advancement in technology has resulted in evolution in industry ever since the eighteenth century. Gradually, many advancements were seen in different fields such as biotechnology and information and communication technology which has caused a drastic change and improvement in innovation which till today is increasing. This rapid change brings along some challenges not only for individuals but also for organizations and society as a whole (Phaal et al. 2013; Kostoff and Schaller 2001). Thus, many managers and in general the responsible individuals are mostly bound to make tough decisions so as to limit the allocation of resources considering the cost, complexities, and the associated risks of affluent investment which is required to keep up with the global competition. Hence, technology management has been introduced as a field to address the aforementioned challenges. Technology management is closely related to the technological core business processes which embody the innovation, product development, strategy planning, and operations management. There should be a balance between the market pull and

1.1  Fourth Industrial Revolution

3

the technology push which results from an implementation of a healthy technology management. There are possible frameworks that are being introduced in order to ensure the proper understanding on how to integrate both technological aspect and market knowledge to support strategy development, innovation as well as operational ­processes in the organization. One of the tools which is introduced to answer the ­challenges with respect to technologies and technology management is “Technology Roadmapping.”

Chapter 2

Literature Review

2.1  Technology Roadmapping Technology roadmapping (TRM) concept was first introduced by Motorola back in 1970s. Main objective of the Motorola’s TRM was to align the gaps that could arise both in technology and product development (Phaal 2015). The core concept of roadmapping has been the same of giving a strategic vision to the company and how to utilize it but the ways of implementation have changed. For example, a major aerospace organization has implemented technology roadmapping in order to achieve success in its single-aisle program which is its biggest revenue driver (Sourav et al. 2018). The concept of Hierarchical Decision Modelling (HDM) has been implemented by the power industry for the strategic roadmapping of robotics technologies (Daim et al. 2018). Not only the technology sector but the process of sustainability has involved in the roadmapping process such as cattle farming in Germany (Rivero and Daim 2017). Hence roadmapping has covered every breadth of industries because of the comprehensive methodology it encapsulates. Since then, the approach has been adopted in different businesses and organizations to ensure the innovation and business strategy and provide a suitable platform for industry’s competitive advantage. Koen and ERIMA introduced the first technology roadmapping structure long before in 1970s (Fenwick et al. 2009). Later, the approach was modified and become pragmatic by Phaal et al. through the proposed T-Plan. As stated by Phaal et al., issue of running business is increasing with respect to cost and complexity and volatility of technologies. Hence, for businesses to ensure their survival and having proper alignment with customer needs, the management of technology is vital to be considered. Technology roadmapping is considered as a flexible and adaptable technique that can be identified as a strategic tool to ensure that effective processes and systems are taken into consideration. If implemented properly, the technology roadmapping can

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_2

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6

2  Literature Review

bring value and competitive advantage for a business and can improve the decision-­ making process (Phaal et al. 2001b). It is believed by many researchers that the main objective of a TRM can be concluded as a framework which visually integrates different facets of market, product features and technology, and the further analysis based on the time series (Kostoff and Schaller 2001; Phaal et al. 2001b). Moreover, another advantage of using TRM is the capability of the framework to bring communication across the organization and different functional levels and it provides a benchmarking for further and future dialogue once TRM is being implemented. One of the reasons for providing the transparency involves engaging key stakeholders in the process of roadmap development which not only improves wider perspectives but also it brings the consensus among the stakeholders (Phaal 2015; Kostoff and Schaller 2001). Although there are many benefits being identified for using TRM framework, many companies still struggle to find the proper application due to the existence of various forms with limited practical support which would sometimes undermine the benefit of TRM. Traditional TRM was basically comprised of three different layers: Business/Market, Product/Service, and Technology over the time horizon. Figure 2.1 depicts the traditional main three layers of TRM and key challenges identified for successful implementation of TRM, respectively (Phaal 2015) (Fig. 2.2).

Time

Business/Market

Product/Service

Technology

Fig. 2.1  Schematic of technology roadmap—traditionally (Phaal et al. 2001b)

2.2  Roadmapping Process

7

60%

Responses

50% 40% 30% 20% 10% 0% Starting up the TRM process

Developing a robust TRM process

Rool-out of the TRM process

Keeping the TRM process “alive” on an ongoing basis

Other

Fig. 2.2  Key identified challenges of TRM (Phaal et al. 2001b)

Research and development (R&D) is one of the main support elements of technology and R&D as the fourth layer is being added to the TRM framework. Due to this, the TRM technique became more adaptive and flexible. Hence, the generic science and technology (S&T) roadmap as shown in Fig.  2.3 has basically two dimensions (spatial and temporal), where the nodes as well as links are illustrated. Spatial dimension describes the relationship projected in the S&T projects at a certain point in time. Also, temporal dimension explains the evolution of S&T capabilities (Kostoff and Schaller 2001).

2.2  Roadmapping Process Utilization of roadmapping can improve the process of decision-making with the aim to address the rapid change in the field of technology to support the technology roadmapping and planning which is needed for any firm and business (Phaal et al. 2001b). When it comes to the process of roadmapping, literatures suggest the possibility of utilizing two essential approaches: expert-based approaches and computer-­based approaches. Yet, due to some limitations that either of the aforementioned approaches have, there is a possibility of combining the two as it is known as hybrid approach (Kostoff and Schaller 2001). By doing so, there is a holistic overview on the TRM which, at the end, results in a more robust and structured decision-making. Although technology roadmapping is recognized as a powerful and substantial tool which can help organizations to make better strategic planning, the abundance of technology roadmapping forms had resulted in existing challenges. Some literatures have tried to provide insights and share the experience in this regard; however,

8

2  Literature Review

M1

Market

Product

M2

P1

P2

P3 P4

Technology

T3

T1

T4

T2 R&D Project (Science)

R&D1

R&D2

R&D4

R&D3

R&D6 R&D5

Time 1a

(year)

0

1

2

3

4

5

6

1a

Fig. 2.3  Generic S&T roadmap (Kostoff and Schaller 2001)

there has been a little amount of practical support for companies on how to reinvent their whole process. For instance, Bray and Garcia (1997) and Groenveld had shared their summary on technology roadmapping. The result of their research indicated that for an effective TRM, well-established vision and dedication towards iterative process is required (Bray and Garcia 1997; Groenveld 1997). Yet, the authors did not present a very detailed guidance on the exact application of the process. Phaal et al. introduced an approach which is known as T-Plan fast start to overcome the existing gap (Phaal et al. 2001b; Phaal et al. 2004a). Under the technology roadmapping process, there are two different planning involved known as: Strategic Planning (S-Plan) and Technology Planning (T-Plan) (Natalense and Zouain 2013). T-Plan was developed as a resultant of three-year research performed by Phaal et al. (2004a) in various industries. T-Plan focuses on the product and technology level strategic planning (Phaal et al. 2004a). Under this plan, four important stages are identified as follows: Market: Both market driver (external) and business driver (internal) factors are identified with respect to the product-technology strategic planning. After that, they are prioritized for the key market segments. Product: At this stage, product features and attributes are identified, categorized, and prioritized.

2.3  Purpose of Technology Roadmapping

9

Technology: In this phase, the associated technologies which can result in the development of the product features are identified and prioritized. Charting: At this stage, the initial roadmap based on the aforementioned three stages is developed. In other words, the linkage between market and business drivers, product as well as technology features are being agreed upon. It is worthy to mention that after each stage knowledge gaps shall be identified. As it was described in above paragraph, it is vivid that the initial objective of T-Plan is to draw the attention on how to initiate the roadmapping process while considering both economical and agility for the “first-cut” roadmap (Phaal et  al. 2004a, 2004b; Ilevbare et al. 2011). Strategic Planning (S-Plan) is tailored to meet business specific needs and help the organizations on finding a proper roadmap to utilize the strategy and innovation within a firm (Consortium 2018). The main advantage of using S-Plan is providing proper communication and can be used as a reference point in further analysis.

2.3  Purpose of Technology Roadmapping As it was mentioned earlier, the technology roadmapping is a very flexible approach. There are eight different clusters found with respect to technology roadmapping based on the examined structure and content as illustrated in Table  2.1 (Phaal et al. 2001a). Eight different categories were identified with respect to the purpose involved in roadmapping. As it was described by Phaal et al., customization of T-Plan approach is required for the abovementioned categories except product planning as it is a Table 2.1  Roadmap classification based on objectives (Phaal et al. 2001b) Category 1. Product planning

Description Linkage of technology with manufactured product (most common type of technology roadmapping) 2. Service/capability Linkage of technology and how it can be suited to service-based planning business operations 3. Strategic planning Integrates the strategic aspect at business level to analyze the opportunities and threats 4. Long range planning Includes the time dimension and generally is referred as foresight at higher level (national/sector) 5. Knowledge asset Alignment of both knowledge asset and knowledge management goals planning with the business objectives 6. Program planning More targeting the strategy implementation and is directly related to project planning 7. Process planning Focuses on specific area of process with the aim of supporting the management of knowledge 8. Integration planning Integration on how different technologies come together to form a new technology (integration and evolution of technology)

10

2  Literature Review

standard process (Phaal et al. 2004b). Another factor that roadmaps can be associated with is its graphic types. There are also eight graphics being identified as: multiple layers, bars, tables, graphs, pictorial representation, flow charts, single layer, and text format.

2.4  Value Roadmapping As it is described by Dissel et al. during the initial phase of technology development, there has been a dissatisfaction with the technique mainly due to the lack of accuracy in the assumptions made. Complementary feature is added to the previously known technology roadmapping approach which is called value roadmapping to fill the gap (Dissel et al. 2006). Value Roadmapping (VRM) is derived from substantial amount of exploration bound by years of experience with the goal of improving the technology valuation. There were certain drawbacks with the previous methodologies of technology valuation (Dissel et al. 2006). For instance, the majority of techniques used to evaluate the early stage of technology valuation utilized the financial valuation—i.e., discounted cash flow—and decision theory techniques. This indicates that the available quantitative approach was driven. Although this could provide justified and well-­ structured result, yet they lacked contextual sophistication. To add on, Cooper’s research illustrated that firms which had utilized only financial (quantitative) methods suffered from underperformance in comparison with firms that utilized both quantitative and qualitative methods (Dissel et al. 2006). One of the main reasons for the quantitative methodology not leading to fruitful decision-making at the early stage of technology is due to the uncertainty involved with financial valuation. When decision-making for investment on technology is concerned, it shall be understood by the decision makers that the final result of technology is often realized at the final phase. Hence, it is common that technology project demands sequential and continuous investments. In addition, technology itself is inherently uncertain (Dissel et al. 2006). Also, it was believed that managers are aware of flaws in the quantitative approach (specifically in discounted cash flow) when there is a high uncertainty and flexibility involved in the project (Faulkner 1996). Discounted Cash Flow (DCF) does not grant flexibility and often leads to poor accuracy. Also, consideration of only financially oriented analysis would suffer from dubious quality or unavailability of data because of the fuzziness during the early stage (Kahraman et al. 2002). In value roadmapping (VRM), different facets are considered with respect to valuation of projects such as decision trees, technology roadmapping (TRM), and net present value (NPV) which is evaluation in terms of finance. VRM provides a more holistic framework which in turn investigates the valuation of a project (be it at early stage).

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2.4  Value Roadmapping

Time Market & Business trends & drivers

Market & industry trends & drivers (social, economic, environmental, political and technological), customer needs, competitor activity, business milestones

Products Service Value streams

Businesses / facilities Technology / IP

Future revenue streams arising from technology capability. together with strategic impact

Cost / risk reduction Strategic position

Barriers & Enablers Technology capabilities

Non-technical Technical R&T programe

Scenario Vision Strategic Framework

Challenges, barriers & risks associated with exploiting the potential value of the technology. together with complementary assets and actions

R&T investment, leading to evolution of technical capability

Fig. 2.4  Value roadmap concept (Bannister and Remenyi 2000)

One of the first technique that considers qualitative factor is portfolio management. Under portfolio management, the decision process that is involved for the new products and R&D projects is getting updated and revised constantly. During this process, new products get evaluated as well as get prioritized. When new products come into picture, there is a possibility that the existing products get exhausted or de-prioritize (Dissel et al. 2006). Collecting expert knowledge is another technique used in order to overcome the challenges that involve single usage of quantitative approach. Hence, “gut feeling” has become prevalent in qualitative and valuation approaches. Studies performed by Bannister & Remenyi illustrated the fact that investment in information technology is based on instinct and value is referred as “acts of faith” (Bannister and Remenyi 2000). They have stated in their research that there is a lack in understanding when it boils down to valuation and the limit to it that can be achieved. VRM provides a framework that can be utilized to interconnect both technological and marketing aspects of a technology during its lifecycle. Figure 2.4 illustrates the VRM architecture.

2.4.1  Market and Business Drivers This section is also the same as the technology roadmapping and the market and business trend and drivers are assessed based on internal and external environments, respectively.

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2  Literature Review

2.4.2  Value Stream Future sources of revenues and savings are driven by value streams. Under value streams there are various categories such as products, services, technology/IP, cost/ risk reduction, strategic positioning, and so forth. All the aforementioned value streams contribute to the generation of revenue except the “strategic positioning” which comprises of non-financial aspects needed for generating future revenues.

2.4.3  Enablers and Barriers It comprises both technical and non-technical challenges and risks that are needed to be captured the valuation in technology.

2.4.4  Technology Capabilities It contains the underlying technologies which are the result of the investment on technology as its end outcome. One of the most crucial features of the VRM is the time horizon, which has been segregated into short-, medium-, and long-term objectives. Also, VRM has the following eight steps as shown in Fig. 2.5. It is believed that the first step of VRM which is defining the strategic framework, vision, and scenario is the most vital step and it should be clearly addressed in order to ensure the successful implementation of the whole VRM.

2.4  Value Roadmapping

Define

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1. Strategic framework, vision, scenario

2. Technology development & investment milestones

Map

3. Value streams

4. Market & business trends & drivers

Define

5. Technical and non-technical enablers and barriers

Review

6. Project plan & VRM, including key linkages

Present

7. Visualization of VRM for wider communication

Maintain

8. VRM as process

Fig. 2.5  VRM process mapping (Bannister and Remenyi 2000)

Chapter 3

Enablers: Industry 4.0

3.1  Big Data Intelligent car concept is the main factor in the big data strategy of the automotive sector. Its use case should be properly realized in order to ensure its successful implementation on a larger scale. In this concept, not only there is a huge amount of real-time data being gathered but also a platform for a direct publication of the data to the driver via the big data analysis (Voigt et al. 2014). This has resulted in new business and service opportunities across industries while having added value to the service provider, the OEMs as well as the end customer (driver). One of the examples that BMW took was its ConnectedDrive initiative that offers a unique app for monitoring the real-time traffic, concierge service, intelligent emergency call, infotainment, and so forth. This shows the possibility of mass customization which can be achieved via big data. Big data in healthcare also plays an important role. Basically, there are three areas of big data analytics that are currently discussed in the healthcare. The following concerns with those three areas (Belle et al. 2015): Image processing  Medical images are a crucial part of diagnosis, assessment, and planning. Some examples of medical images that are constantly used for the same purposes are: Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-ray, ultrasound, and so forth. The medical image data is having a wide range from a few megabytes to hundreds of megabytes depending on the nature of study, hence, these data require a great deal of storage capacity for the longer term. The challenge that is so far identified with the data in medical imaging consists of both cohesive storage and development of an efficient method for addressing the wide range of available data (Belle et al. 2015).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_3

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3  Enablers: Industry 4.0

Signal processing  Similarly, medical signals also are bounded by significant amount of volume and velocity especially when the patient is connected to different monitoring devices and high resolution and continuous data is required to extract meaningful information. Also, physiological signals are complex in their essence and they become more accurate when physiological signals are integrated with situational context and real-time monitoring along with predictive algorithms to ensure its robustness (Belle et al. 2015). Genomics  By the advancement in developing a high-throughput sequencing technology, the cost to sequence human genome has experienced a drastic drop which continues to fall. One of the biggest challenges that computational biology is facing in analyzing the genome-scale data is providing a proper recommendation in a timely manner. Both cost and time for delivering the recommendations are the main elements in a clinical setting (Belle et al. 2015). With regulatory restrictions getting eased off, the possibility for telecommunication operators becomes immense to gather data from various sources which allows to understand their networks better and the behavior of the customers. These information can be obtained from the website the user visits and the amount of time a user talks over the phone, over the top applications (OTT-Apps) such as WhatsApp and Skype. Network operators can obtain more insights on their users by the gathered relevant data and information about them and pairing them into the network KPIs. Quality of Experience (QoE) then can be integrated with the CRM data, for instance, the user complaints and the posts shared on social media to understand the user’s experience in different geographical locations with respect to the services they receive (Chen 2016). When it comes to volume and velocity of telecom industry, one can observe the dramatic evolution in the recent years with respect to data. Telecom data has experienced a rapid growth ever since 3G broadband was introduced, whereas, today, terabyte scale for datasets is ubiquitous. This trend will continue to grow as the next generation of network comes into picture (optical, 4G, 5G) which provides an opportunity for the users to share large amount of data and content on the internet. In earlier times, the return on the investment on the data analytics was not encouraged; however, in the wake of recent years, investment on big data analytics have gained huge amount of appreciation as the outcome has become measurable and valuable to understand the customer behavior and satisfaction thoroughly (Chen 2016). Figure 3.1 shows the big data analytics framework in telecommunication.

3.2  Predictive Maintenance In automotive industries, “periodic maintenance” is used widely. In this concept, car owners are asked to get their vehicles regularly monitored and serviced based on certain covered mileage or time period. For instance, the general advice is to get the

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3.2  Predictive Maintenance Infrastructure & Products Product Recommendation

Data Monetization

Network Planning

Capacity Management

Operations

Churn Analysis & Prediction

Proactive Customer Care

Fraud Management

Ordering Process Optimization

Fraud Management & Root Cause Analysis

Fig. 3.1  Telecom big data analytics framework (Chen 2016)

car checked up either within the first 3 months from the last service date or after having up to 10,000 kilometers of travel (Dhall and Solanki 2017). Apart from the regular guidelines, there are other times that the car needs an emergency service/ maintenance after a malfunction or breakdown. Embracing the technology however can bring more benefits in the conventional maintenance in automobile and fleet management system. Internet of things (IoT) has becoming an important element of today’s life. This concept is not very new; however, the advancement in the technology has impacted the activities of individuals globally. An alternative to the periodic maintenance can be done through utilizing the technology and usage of sensors and IoT. This approach collects relevant data about the vehicle such as fitness measure and operating condition of the different parts of the vehicle and communicates the data to the centralized system. Later on the data can be further investigated to identify which part requires a maintenance or service; also the system can give an emergency alert that informs the car owner about the potential breakdown of some parts (Dhall and Solanki 2017). In medical engineering, predictive maintenance is the core functionality. The main goal of PM is to ensure safety of the medical devices as well as serve as a preservation of investment in the purchased equipment via enhanced longevity and product life cycle. PM is an approach which is based on risk assessment. However, the implementation and design of such an effective device is not simple and requires an extensive administrative support. One important task in management systems is maintenance prioritization (Saleh et al. 2015). In telecommunication, predictive maintenance plays a very crucial role as well to decrease breakdown of equipment. The need for predictive maintenance has risen because of increased complexity of traffic patterns, increased usage of network, and several equipment vendors. Companies deploy predictive maintenance to decrease the potential breakdown of equipment in telecommunication site with an aim to reduce the operations cost and improve customer satisfaction. One example is the Markov process model which was developed to address the customer trouble ticket

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3  Enablers: Industry 4.0

as well as enhance the quality of service. A predictive maintenance can be performed as soon as the next CCT is identified which at the end results in satisfying the vision of the company (Kadry et al. 2018).

3.3  Cloud Computing There is a stress sensed on transport systems due to the increased number of vehicles. The rapid growth has made roads to be susceptible and more dangerous. Therefore, there is a necessity for adaptation of existing transport system to improve its infrastructure and safety. To overcome the aforementioned issues, the Intelligent Transport Systems (ITS) has decided to provide traffic applications and cooperative traffic monitoring and control flow. Through emergence of Vehicular Ad hoc Network (VANET), such applications will be present everywhere soon and would be considered as an environment of ITS (Ghafoor et al. 2014). Also, in the coming years more cars will be integrated with devices that empower the communication between the cars, for instance Wireless Access in Vehicular Environment (WAVE) which communicates with nearby vehicles and access points in the coverage area. This advancement is also seen in car manufacturing process for better storage and computation as well as communication through devices. The main goal of these devices is to improve traffic safety and efficiency. To add on to that, these vehicles can have access to internet services which would eventually benefit the drivers and passengers. However, the on-board resources have seldom been applied. In order to overcome the underrepresentation of that application, the vehicular cloud concept is proposed. Cloud computing embedded unique features (on-demand self-service, broad network access, and so forth) which are claimed to improve the conventional health IT in health organization. It was believed that cloud computing could provide great amount of benefits for healthcare, such as enhanced flexibility in the IT resources and higher availability with respect to IT infrastructure to address the health IT demands as well as reduced cost of health IT usage. Cloud computing integration in the healthcare is a very novel idea. When it comes to cloud computing in healthcare organizations, it is the second type which tries to improve the product, service, and care (Gao et al. 2018). Similarly, in ICT industry, cloud computing is one of the main trends in technology and business. In telecom industry, the cloud computing has provided a platform for new business opportunities as well as resulting in operational efficiencies. With the help of cloud computing concept, the conventional product based has been transformed into service based. Having a software as a service provider has certain advantages such as significant improvement in delivery times, reduced cost, and higher flexibility. In addition, new business models can be realized when companies focus on the cloud computing and deploy technologies which results in new context in: network expertise, security infrastructure as well as quality of service (Vajda et al. 2012).

3.4  Digital Twin

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3.4  Digital Twin The definition of digital twin was first conceptualized in 2003 by Grieves. Up until now there are a couple of new concepts that has been recognized but the most common one is the concept by Glaessegen and Stargel in 2012. Based on this definition, digital twin is referred to as combined multi-physics, multi-scaled as well as probabilistic analysis and simulations performed on products which utilizes the physical models and update in sensors to reflect the life of the surrounding twin. Digital twin can be discussed in three main parts: physical product, virtual product as well as connected data that integrates both physical and virtual parts of product (Tao, et al., 2017). Realization of digital twin is broadly distributed from cloud ecosystems to very distinct exchange formats. Also, there is a possibility to embed specific component during manufacturing which provides transparency among suppliers and integrators. System integrators can utilize the information provided through this realization to implement it on a wider system range, for example car manufacturing, factory, or even the whole train (Boschert et al. 2018). Digital twin concept in healthcare provides a framework to analyze the data-­ driven healthcare practices alongside its ethical implications in either preventing care or human development and therapy. Digital twin concept is identified to have the potential of enhancing the resolution and comprehensiveness in terms of defining the disease and normality in healthcare. For instance, deviation from normal can be drawn from having a “virtual self” which can have a detailed map model (Bruynseels et al. 2018). The “normal” state which refers to healthy condition can be identified with high resolution and with multiple data dimension which is tested via molecular and behavioral level assessment against person’s life time. In other words, this physiological makeup and comparison provides a great amount of data in detail. In current approaches, the comparison range is mainly done through age and gender. In addition, large amount of variations in human genomes which in previous years were not appreciated and was considered as futile, have gained importance by knowing how vital information can be taken from them. A great advantage that can be realized with digital twin in healthcare is the level of transparency that is provided for caregivers with respect to the status of individuals (Bruynseels et al. 2018). The parts of telecom networks such as towers and sites are perfect for the digital twin concept. There are different ways through which providers would be transformed. One of the ways is tower management. Telecom sites use different pieces of equipment such as antennae, power generators, and aircraft warning lights. These require continuous monitoring. There are different sorts of data coming from the telecom sites such as proximity, image, motion, and position, which can be obtained through sensor networks and evaluated using AI/ML algorithms. The data that is fed into the digital twin of a tower or site allows operations and field service management to address these issues (Malim 2018).

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3  Enablers: Industry 4.0

3.5  Autonomous Robots Autonomous robots are used in assembly line and for handling as well as transport system. In order to have a precise and successful assembly, the next generation of industrial robots should be equipped with sensors that have the intelligence of the human beings. One example is that Fujita has developed a human-like assembly robot that tries to generate task and get the job done by observing a sample object. This is performed by the detailed knowledge of executable task and the available sensors. In addition, another development by Scholz-Reiter and Freitag was introduced as a robotic system with capability of handling vendor parts and delivering them in cases and the position of cases is defined via laser scanners. Controller also uses the same data to select the case to attach to first (Scholz-Reiter and Freitag 2007). One of the most interesting robots’ application might have been seen in healthcare. Healthcare robots exhibit a great level of chances for providing help to a large amount of people. These robots can be deployed to help people with their sensory, cognitive as well as impairment related to motor skills. This can result in a great support to not only the patients but also the caregivers and many other stakeholders. Robots are basically a physical system that are able to make physical change around. Decisionmaking for robots is done through sensors that had already gathered information and data. In addition, the autonomy of robots utilizes algorithms and processing data as well. Therefore, robots in healthcare have a great potential to close the care gap in healthcare caregivers. Robots have a wide range of applications from surgery to physical, clinical rehabilitation, drug delivery, and patient management (Riek 2017). The occurrence of natural disasters is very unpredictable. Incorrect prediction of happenings of natural disaster can result in greater sufferings and losses. However, with an appropriate disaster management, less detrimental losses can be achieved. IT is one of the tools for achieving disaster management. For example, early warning system can be integrated for the purpose of planning as well as mitigating the disaster. Yet, during the period of disaster many communication networks and the infrastructure get damaged. Therefore, it is required that a very fast and reliable response is developed to restore the communication network. There are certain studies that suggested and evaluated the usage of robots for disaster management. For example, Stormont gave a proposal to use swarms of autonomous robots with the most probability of capturing the survivors. The other types of robot were developed by Hsieh et al. which is an autonomous rescue and surveillance robot and is found in urban areas (Budianto et al. 2011).

3.6  Augmented Reality Augmented reality integrates virtual objects into the reality. After the proceedings of the image, the output of the process can either be of head mounted display (HMD) or a usual type of screen. Having HMD has certain advantages such as full visibility

3.6  Augmented Reality

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for the user to see through the screen and even the possibility of having construction tasks while the user is interacting with the virtual object. One irreplaceable feature of any virtual environment application is 3D user interface design. Three categories are identified under user interaction which are (1) Navigation, (2) Selection/manipulation and (3) System control. The mostly used user action is navigation in 3D environment which is subdivided into travel and way finding. Second, the task is described on virtual objects through selection and manipulation. These tasks can be summarized as selection of objects, positioning of object as well as rotation of object. Thirdly, system control describes the task command and its application for change in the state of the system or the interaction (Himperich 2007). In healthcare, many imaging methods such as CT, MRI, and X-ray are used in surgical procedure or diagnosis. These images are 2-dimensional and are gathered immediately prior to the surgical operations. One of the setbacks of preoperative images is that they are only used as a reference right before the operation. In addition, these images are not capable of providing spatial data with regard to organs of patients. On the other side, some imaging methods such as ultrasonography are intraoperative. One main advantage of intraoperative imaging is its ability to provide real-time interaction during the surgical operations. By this, spatial information on the patient can be obtained, so that the body organ can be evaluated (Tang et al. 1998). In the current telecom systems, only monaural audio is being deployed. Traditional audio telecom devices and features such as cellphones and voice-over­IP (VoIP) software do not assist the interaural cues which hence diminish the communication performance with the original in-person conversations. However, the natural telecommunication happens in binaural (Tang et al. 1998). In face-to-face types of conversation, multiple speakers can be segmented based on their positioning by a listener which is called a “cocktail party effect.” With the help of Audio Augmented Reality (AAR), the binaural communication would be possible which is done through augmenting the natural human auditory perceptions (through embedded spatialized virtual audio content). One of the AAR’s use cases could be the teleconference scenario where the whole conference is recorded through a headset via an embedded microphone and is worn by one attendee. The content of AAR is presented via Virtual Auditory Display (VAD) which is an overlay of acoustic environment. The cocktail party is also true in telecommunication of multiple-party. VAD feature can segregate the speech signal of the speaker spatially which overall enhances the comfort in listening and intelligibility. One distinct difference of auditory perception is the fact that it is not constrained to the “field of view” and the orientation and distribution of users are not playing a role in teleconference call. By having a virtual speaker registered, users can bend to a representative in the same manner if in-person conversation would have taken a place. The root of AAR is the augmentation of reality rather than replacement. Acoustical transparency is achieved in virtual setup through capturing the real sound heard at ears of users and getting played back via earphones. The core principle of “mic-through augmented reality” is mixing both real world and virtual sound which in other words means to have real world perceived via the microphones (Gamper and Lokki 2010).

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3.7  Sensors Today, consumers are looking forward to having different aspects when focusing on automotive industry such as higher quality, reliable, safer, more ecofriendly, and user friendly products. In order to satisfy these requirements, new design methodologies shall be used for on-boarding automotive sensor to software solutions with higher efficiency of engine and the control system (Ranky 2002). At the end of the day, customers are looking for what part was replaced and for what exact reason with its associated cost and time. To accommodate those, smart sensors and advanced software are required to allow the traceability of the whole lifecycle in automotive industry. In modern automotive industry, a real-time networking and distributed sensor is required (Ranky 2002). In healthcare, miniaturization and sensors play a very important rule. In terms of e-healthcare, the necessary data is collected, whether it is outside or inside the human body. Smart sensors gather the data, store it and transmit the data. These sensors have different use cases such as real-time monitoring where today’s wearable sensors (devices) are worn for the continuous monitoring. For this purpose, a detailed knowledge on MIMO (Multiple-In, Multiple-Out) wireless networks is required to enable the wireless body area network (Thayananthan and Basuhail 2017). Therefore, healthcare facilities can be managed faster when efficient framework is widely available at any places. Nanotechnology and DNA have been a backbone of miniaturized devices in the field of medical which has enhanced the implantable facilities. Future innovation in the e-healthcare is dependent on the miniaturization which allows the integration of wearable sensors. The next generation of e-healthcare should be revolutionary in terms of size, performance, and capabilities. Secure and real-time monitoring of healthcare devices would ensure that patients get the required facilities as soon as needed in a timely and secure manner. For instance, remote brain-machine interface (RMBI) is a full framework—that is a wearable headband with nanosensors and is communicated via Bluetooth—that assists the elderly patients. Moreover, one application of sensors in e-healthcare is the analysis of temperature. In healthcare technology, very small machines are used as a sensor that has the major role in identifying all facets of medical and healthcare systems (Thayananthan and Basuhail 2017). Wireless Sensor Networks (WSNs) first originated from a program at Defense Advanced Research Projects Agency (DARPA) back in 1980s. The WSN platform is based on the spatially distributed sensor nodes. These sensor nodes are able to perform certain tasks independently. Afterwards, sensor nodes communicate with one another to transfer the information to the processing unit. One of the common sensor nodes is Mica2 Mote which was developed by Crossbow Technology (Wang and Balasingham 2010). The common hardware parts of a sensor node include radio transceiver, embedded, memory, power supply, and sensors. WSN architecture is based on various number of sensor nodes, wireless communication platforms, and processing abilities. The nodes are distributed in an unconsidered environment. Sink nodes are used to collect data as they have access to infrastructure network platforms such as Internet.

3.8  3D Printing

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3.8  3D Printing 3D printing design is an additive manufacturing process which is used to make design in layers through material deposition. That is, in additive manufacturing a design is developed layer by layer and the material for that is present in the form of fine powder. Automotive industry is constantly working with AM as a potential that can result in breaking the existing barriers in the conventional automotive manufacturing. In automotive sector, efficiency and time to market can significantly increase by using rapid production that is offered by AM technique. It can also reduce the cost of production. One example is the Ecoboost cylinder head of Ford Motor that uses 3D prototyping. Conventionally, production of parts would take up to 4–5 months; however, Ford Motor was able to design and print the metal cylinder in just 3 months. This can highly suggest the advantage of 3D prototyping in the automotive sector. Apart from that, 3D prototyping and AM would result in diagnosis and resolve mechanical issues. One example was the brake noise issue in the Ford Explorer that was addressed by Ford Motor in 2010 through additive manufacturing (Manghnani 2015). 3D prototyping is under a lot of research in the field of healthcare application. Bioengineered blood vessels, bioengineered human tissue, and biomedical devices for dental or orthopedic are the examples of such intensive efforts. In surgical planning, bioplastics and 3D prototyping are used for the purpose of creating anatomical models, prosthetics devices, and drugs. Yet, the commercialized available orthopedic prosthetics devices are generally costly, lack certain anatomical capabilities and lack customization. Although some less expensive prosthetics are available, they are indeed inconvenient for amputee and fall easily. More sophisticated prosthetics are available, but they are quite expensive and are not affordable for many. However, 3D printing as one solution that can reduce the cost of production and the capability of customization via patient-specific is highly appreciated. For example, some use cases of 3D printing and prosthetic devices contain dental, spinal, hip replacements. Similarly, medical implants, customized drug treatment, and bio-printing are the other examples (Mills 2015). When it comes to the application of 3D printing in telecommunication industry, there are some indirectly associated uses involved. For example, taking MIMO antennas which are the technology for wireless communication with the aim of minimizing errors and data speed optimization. The printing process is very precise, and the antennas can be finished within half an hour (Goulding 2018). The material used is made of very photosensitive resin to ensure high conductivity of the antenna. Second use of 3D printing is found in one of the world’s leading telecommunication operators. Orange—French company—is working on providing a clean renewable energy to one million of the customers as well as expansion of off-grid users via the 3D printed components with the goal of optimization of power sources such as wind turbines. The company—Orange—has adopted 3D printing to print the blades for wind turbines; this has resulted in significant cost reduction and improving the performance. The third example is Optomec which utilizes 3D manufacturing and is

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3  Enablers: Industry 4.0

specialized in solar cell printing, electronics, touchscreen, and other components in New Mexico. The company now is investigating on 3D printing for the phone antenna in order to provide more design flexibility and re-configurability of production line. With the help of 3D printing, the hazardous manufacturing of electronic devices and usage of toxic solvents and materials will no longer be used while resulting in a lower cost solution (Goulding 2018).

Chapter 4

Problem Statement

Many production and supply chain inefficiencies can be addressed by the utilization of industry 4.0. This concept can transform traditional businesses into a more sustainable and long term-oriented engagement with customers. Industries implement different methodologies to cope with technological advancements. One of the most common frameworks is “Technology Roadmapping.” Introduction of technology roadmapping helped in structuring the processes required for the successful product. Under this approach, different aspects for a successful technology or product are addressed. However, as it has been seen from past experiences, this technique lacks the real valuation of the product. In today’s world of business, the customization and value-based products/services can survive the highly competitive and fast-pace market. For that purpose, the hybrid framework is suggested to bind both technology roadmapping and value roadmapping. This thesis targets three different industries of automotive, healthcare, and telecommunication and tries to integrate the concept of industry 4.0 by the utilization of hybrid roadmapping (VRM and TRM). Future development of industry 4.0 and its impact on automotive industry would require synergic demands from all different ecosystem partners such as OEMs, policy makers, suppliers, end users, and so forth. In addition, having a flexible production line will result in a customizable design.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_4

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Chapter 5

Methodology

At initial step, the methodology implemented was to investigate the available technology roadmapping for three different sectors: automotive, healthcare, and telecommunication. In addition to technology roadmapping, value roadmapping for the same three sectors were analyzed separately. First step in technology roadmapping was to capture the market and business drivers. Market driver is the driving force for the customers to make them buy the product and their willingness to pay. On the other side, business drivers are related to the business itself such as resources and processes for companies/business success. As the next step, the product features that are associated with the three investigated sectors are identified. The current product features are laid out and gaps with the existing product features are identified. The further step involves laying out the short-term and future long-term goals for the product features. After this, a quality function deployment (QFD) is performed between the market drivers as well as the product features. In this process, the market drivers are displayed on the x-axis (horizontal) and product features are showcased on the y-axis (vertical). The market drivers are weighted on a scale of 1–10. Further, a scale of 0–3 is utilized for the correlation, where 3 denotes the highest possible correlation and 0 denotes no correlation. Thereafter, technology features are evaluated in the same process as product features and a QFD is deployed between technology features and product features. Technology features are analyzed because they are necessary to make the product features achievement possible. Another step involved is identification of industry 4.0 which acts as enablers in the roadmap. Since industry 4.0 is being rolled in the integral research and development programs in organizations, hence it makes it necessary to study the effect of these features which act as enablers for the technology features. The final stage involved in the value roadmapping is identification of the resources needed for fulfilling the enablers. After evaluation of market drivers, product features, technology features, Industry 4.0 enablers and services, the final roadmap can be established for three industries viz. automotive, healthcare, and telecommunication. The steps can be illustrated by Fig. 5.1 below:

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_5

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• Identifying market and bsuiness drivers • Product feature definition and identifying gaps • Evaluation of product feature and market/business drivers through QFD • Technology feature definition and identifying gaps • Evaluation of product feature and technology feature through QFD • Industry 4.0 Enablers • Listing of required resources for technology realization • Putting up the roadmap

Fig. 5.1  Flowchart of value and technology roadmap

Chapter 6

Value Roadmap Development for Automotive Industry

6.1  Market and Business Driver 6.1.1  Sustainability Sustainable measures demand for proper investments in research and development in both technical and managerial skills. It is normally driven by an innovative agent that requires considerable time to be integrated as a new part of the production (Rodrigues Vaz et al. 2017). Car manufacturing is an important contributor to environmental, social development and economy of a country. In other words, sustainability is the most relevant concept in design and manufacturing in automotive sector. In the context of sustainability, new concepts such as “eco-innovation” are being used which refers to “eco-efficiency” as well. This procedure results from an intersection among two dimensions of sustainability concept which is bundling both economic aspect and social aspect. “Eco-efficiency” is concerned with the other two pillars of sustainability which are economic and environmental (Rodrigues Vaz et al. 2017). Eco-efficient innovations tend to result in decreased amount of materials used in a product as well as energy per unit produced. This is even more relevant in automotive sector.

6.1.2  Customer Experience Customer’s attitude is changing rapidly with respect to purchasing of new car. This has brought challenges that car manufacturing companies are encountering with today. New buyers can be categorized in different segments with emphasis that

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_6

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b­ uyers put on economy, comfort, convenience, performance, and so forth (Nath 2009). Due to globalization and attraction towards international market, car manufacturing companies need to adjust their business especially their marketing variables based on different cultures. A study performed by Nath (2009) described the correlation analysis of responses that customers place on different car attributes. Also, the underlying benefits that each buyer asks for new car generation and clarifying them into relative importance they place on the features. Hence, the resultant of customer considerations in decision-­making can be defined as two main factors: economic benefit factors and social benefit factors.

6.1.3  Digitalization As reported by Jain and Garg (2007), the automotive industry is facing challenges due to globalization, individualization, and digitalization. The report argues that size of organization does not guarantee success anymore in this highly competitive industry. Also, the report displays that only companies can survive in the future that constantly tries to create new ways of developing values for its customers. New business models have emerged in recent years especially in the automotive sector where the digital innovations are accelerating (Riasanow et al. 2017). New trends such as self-driving cars, connectivity, and car sharing are disrupting the whole traditional business model and all are the resultant of emerging technologies and transition towards digitalization. Hence, new inventions in technologies intensify the digital innovation as well. Value creation in the current era is exclusively through physical materiality but digital transformation has enabled a change in the methodology of value creation. Strategies deployed in digital transformation are also crucial, as it “reflects the pervasiveness of changes induced by digital technologies throughout an organization” defined by Chanias and Hess (2016). Although the increasing change on these emerging trends is visible to organizations and business, the real future of digitalization and which trend would surpass the rest and becomes prevail is still a big question mark (Simonji-Ellias et al. 2014). Apart from that, Hanelt et al. integrated both digital and physical world in their research and also explored the possible impacts that digital trends will place on automotive industry business model. They have categorized it into four different business models: extension, revision, termination, and creation (Hanelt et al. 2015). In addition, digitalization has a significant impact on the production and products in the automotive sector as well. Core competencies in both ICT industry and automotive have come together to address the effects of digitalization (Peters et al. 2016).

6.1  Market and Business Driver

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6.1.4  New Markets Emerging economies have been displaying substantial growth. It is important to highlight that not only the demand is shifting to other emerging economies but also the whole manufacturing is altering towards the countries with new opportunities in terms of new buyers. Global growth of passenger cars has been enjoying the 72% upward trend from years 2000 to 2014. Emerging countries are: Korea, Brazil, China, India, and some other developing countries (Traub-Merz 2017). There has been a transformation in terms of technology drives in the global perspective due to the future scarcity of fossil fuels, environmental challenges, and climate issues. Back in 1990s, the power train electrification was developed with the emergence of hybrid drive systems in Japan. Literatures suggest that the ultimate future success of automotive industry relies on three main elements: innovation and new development in car batteries, utilization of renewable energy since the usage of fossil fuels have an adverse impact on emission balance, and political enforcement (Traub-Merz 2017). Shifting to new technologies such as electric cars would result in changes in OEMs and suppliers’ relationship and also the possibility of bringing in new players specifically in power generation and storage technologies and innovations. However, there exist some uncertainties within the OEMs with respect to the implemented strategies to tackle technological changes. For instance, some companies have decided to fully integrate the hybrid motors and others are only considering the reduction of emission through incremental innovations (Traub-Merz 2017). In summary, it is quite clear that automotive industry is going to be positioned for future growth as well as business expansion.

6.1.5  Cost Most of the times, the manufacturing has been the limiting factor when it comes to cost reduction and modelling. This also holds true for the automotive industry. Costing strategy is one of the key strategies that can make the company to stand still over the years and survive the highly competitive market through identified competitiveness (Monteiro 2001).

6.1.6  Fuel Efficiency The international energy agency was formed in 1974 in the view of Organization for Economic Co-operation and Development (OECD) with the vision to establish a universal energy program. One of the goals of the IEA was to enhance the energy

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supply of the world and demand by searching for the appropriate energy sources and improve the used energy efficiency (International Energy Agency 2005). Energy consumption has always been a concern in motor vehicles. It is not only due to scarcity or price of the petroleum but also environmental factors associated with them. Fuel economy is one of the terminologies used to measure the efficiency of a vehicle. It refers to the relationship between the distance of travel and fuel which is consumed by the vehicle. Generally speaking, one of the fuel economy improvements can be recognized by increase in the average engine efficiency over the drive cycle (International Energy Agency 2005). It has been reported by International Energy Agency (2005) that integrating electric motor maximizes the engine efficiency on both test cycle and on-road operating conditions. Also, hybridization at higher level can improve system efficiency to obtain fuel savings up to 50% during city travel, taking into consideration that the efficiency increase is much lower during highway speed.

6.1.7  Manufacturing Process By introduction of computers and electrification, production methodologies were altered together with more granted visibility on operations by means of collecting and sharing the data on an integrated value chain. Nowadays more software-based manufacturing and production with higher flexibility is being used to overcome the classical full human interface in operation towards human-machine operations (Khajavi and Holmstroem 2016). Next transition in manufacturing is defined through digital manufacturing. Additive manufacturing (in other words, 3D printing) is one of the main pillars of digital manufacturing in twenty-first century. When factory manufacturing is discussed, the main focus is shifted on integration of additive manufacturing in mass production while improving the flexibility and customization as well. This variation of adaptation is fully reliant on incorporation of additive manufacturing into already existing manufacturing and production (Ryan and Eyers n.d.). In terms of future concern, there can be two distinct elements that shall not be overlooked and neglected. First, the certification with respect to safety procedures all the way from parts, material to process. Second, “smart” spare parts which are now possible with the plethora of advancement in sensor technology as well as predictive maintenance, unlike this would not be the case in modern and future manufacturing process that the replacement of a part was suffering from a long and relatively expensive procedure (Ryan and Eyers n.d.).

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6.1.8  Disruptive Models Researchers suggest that the automotive sector is facing an era of innovation with electronics finding its place, the necessity of sustainable solution, and new prevalent usage of sharing platforms, which have caused this industry to undergo a paradigm shift (Ferràs-Hernández et al. 2017). Some examples of paradigm shift can be seen in the invention of self-driving cars, 3D printing, new batteries, and so forth (Ferràs-­ Hernández et al. 2017). Companies such as Apple and Google are considering entering the automotive market which shows their leverage in terms of battery management technologies, operating system development, virtual reality, and other software/hardware advantages that can intensify their marketplace quite rapidly. Majority of traditional car manufacturers are dependent on their third party which eventually results in competitive disadvantage for them (Butler and Martin 2016). Table 6.1 illustrates the identified market drivers along with the rated weightage based on expert opinions from scale 1 to 10 with 1 having the least and 10 with the Table 6.1  Market drivers evaluation—automotive Drivers Sustainability

Customer experience Digitalization

New market

Cost

Fuel efficiency

Manufacturing process Disruptive models

Definition Sustainability is the most relevant concept in design and manufacturing in automotive sector since car manufacturing is important contributors to environmental, social development and economy of a country Customer’s attitude is changing rapidly with respect to purchasing of new car generations. This has brought challenges that car manufacturing companies are encountering with today Automotive industry is facing challenges due to globalization, individualization, and digitalization which requires new business model where the digital innovations are accelerating Emerging economies have been displaying substantial growth, not only the demand is shifting to other emerging economies countries but also the whole manufacturing is altering towards the countries with new opportunities in terms of new buyers Costing strategy is one of the key strategies that can make the company to stand still over the years and survive the highly competitive market through identified competitiveness One of the aims of IEA was to improve the world’s energy supply/ demand by finding right energy sources and increasing the used energy efficiency Nowadays more software-based manufacturing and production with higher flexibility is used to overcome the classical fully human interface in operation towards human-machine operations Automotive sector is facing an era of innovation with electronics finding its place, the necessity of sustainable solution, and new prevalent usage of sharing platforms, which have caused this industry to undergo a paradigm shift and hence disruptive models

Average weight 7

8

8

8

7

8

6

5

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highest weightage for the automotive industry. The average weight is taken for the final illustration.

6.1.9  Roadmapping of Market Drivers After evaluation of the market drivers, the drivers are distributed according to the timeline considering their relative importance. The drivers are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the drivers are ranked, they are placed on the roadmap according to short term and long term, for example, “cost” as a market driver in automobile is a long-term feature since “cost” would be one of the major factors when it comes down to product acceptance. Figure 6.1 shows the roadmap of market drivers for automotive industry.

6.2  Product Feature in Automotive The product features in the section deal with the features required in the automobile which would be necessary to satisfy the market drivers. The product features enlisted in the table below are further segregated into short-term (~3  years) features and long-term (~7 years) features. The gaps mentioned later on depict the shortcomings in the current product features, which could be addressed by short-term and long-­ term goals. Table 6.2 shows a summary of product features in automotive sector.

6.2.1  Emission 6.2.1.1  Current Feature Euro 6 standards is introduced to address the emission issues: “considerable reduction in NOX (oxides of nitrogen) emissions from diesel vehicles is necessary to improve air quality and comply with limit values for air pollution.” European emission standard regulates and monitors gasoline and diesel vehicles separately. In

Fig. 6.1  Roadmapping of market drivers—automotive

6.2  Product Feature in Automotive

35

Table 6.2  Product features—automotive Product features Emission Safety Customizable Efficient engines Storage systems Connected cars Smart and recyclable material

Current level Euro 6 standard

Short term ~ 3 years Emission reduction by 30% Seat belts Airbags Third living space – Battery powered Range extender engine Ni-Cd batteries Ni-Mh batteries Telematics control Fully autonomous unit vehicle Steel Aluminum

Long term ~ 7 years – Skid avoidance – Fuel cell Na-S batteries Connected autonomous road transport Plastic

Euro 6/VI, the limit on the amount of nitrogen oxide has been declined by 56% compared to previous emission standard of Euro 5/V (Williams and Minjares 2016). 6.2.1.2  Short Term European leaders are constantly looking for initiatives to overcome the climate change and the recent adopted framework is called “2030 climate and energy framework” that was accepted in October 2014 with the vision of cutting emissions in the European Union by 40% by the year 2030. One of the initiatives is called Effort Sharing Regulation which targets the cutting of greenhouse gas emissions by 30% by 2030 comparing with the year 2005. Different sectors are included in this measurement such as transport, agriculture, waste management, and buildings (European Parliament 2018).

6.2.2  Safety 6.2.2.1  Current Feature According to WHO, road traffic fatalities and injuries are the main public health issues happening in the world. Statistics show that around 1.2 million people get killed in road traffic accidents annually (World Health Organization n.d.). One identified risk factor that causes road fatalities and injuries in vehicle occupants is the failure of using seat belts. Those passengers failed to wear seat belts are considered to suffer from severe injuries and casualties during the time of accident (World Health Organization n.d.).

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6.2.2.2  Short Term One of the products used as a safety restraint system in automobiles is airbags. Airbag consists of a flexible fabric cushion that is inflated when a vehicle is about to collide. Airbags are designed with the goal of getting of a hold of vehicle passengers during car crash while providing protection of the occupants against being hit against windows and steering wheel. Intensity of injuries reduced as less forces exerted on the passengers’ bodies (Shaikh et al. 2013). 6.2.2.3  Long Term In order to prevent road traffic crashes (RTC), certain measurements have been done through various products such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC) system with the goal of preventing road traffic injuries, for instance: safety seat belts and airbags which tend to limit the intensity of injuries during car crash (Khorasani-Zavareh et al. 2013). Skidding of the wheels is also another severe phenomenon that could lead to drastic injuries and fatalities. Skidding happens when during a heavy braking, the force of the brake surpasses the force on the wheels causing the rotation. Moreover, not only the wheels face skidding and loss of control but also it produces a long stopping line on pathways (Khorasani-Zavareh et al. 2013).

6.2.3  Customizable 6.2.3.1  Current Feature Automotive interior design and its usage from occupants’ point of view have been significantly impacted by the advancement of technology and new proposed infrastructure. There are a couple of opportunities and identified use cases that is the resultant of the advancement known as third living space, a space which is personalized to the customer’s taste and behavior; there is no boundary between office, home, and automotive interiors (Dattatreya 2016). One example is called “no frontiers,” which is referred to no visible boundaries between different spaces such as office, car, or between real world vs. the virtual world all due to the new offerings in cars’ connectivity. Second example is known as “extension of oneself,” this concept refers to a more personalized future of automobiles. Current deployed intelligent HMI solutions have resulted in more personalized feature. Thirdly, “holistic HMI” which describes a numerous sophisticated functionality in cockpit architecture by the introduction of interactive technologies. Holistic view in this concept addresses both understanding of drivers’ state and technology functionalities as well as the current positioning of the car and its surroundings (Dattatreya 2016).

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37

6.2.4  Efficient Engines 6.2.4.1  Current Feature One of the advancements in mobility sector to reduce future conventional emission and energy consumption is achieved by electric vehicles. Electricity can be supplied to the car through either battery or fuel cell (FC) (Helmers and Marx 2012). The modern vehicle engines comprise either the hybrid engine types, battery powered engine, or the conventional internal combustion (IC) engines. As the hybrid and battery powered engines still cover a smaller percentage of market due to costs hence the IC engines comprise the most commonly used engine. The SI engines come under the category of reciprocating engines. The SI engines work through the internal combustion where the internal combustion is ignited by a stroke of spark to produce the required energy. 6.2.4.2  Short Term Battery electric vehicles suffer from one main weakness which is its low range. In order to overcome this issue, a range extender is added which is responsible to generate power either through a small internal combustion engine or a fuel cell. When the battery is sufficient enough to provide the energy, the supplementary range extender is not used (Andwari et al. 2017). 6.2.4.3  Long Term Electric vehicles are identified to have different advantages compared to its fuel-­ based vehicles such as absence of air pollution which is the result of internal combustion, decreased refueling cost as well as less maintenance cost. However, there exists several main disadvantages with respect to electric cars such as lesser autonomy of the driver, longer charging of the car battery as well as the cost (Aschilean et al. 2018). The way to mitigate the short timing between two refueling points could be by the implementation of a secondary storage system which can allow the battery to charge during movement and can thus increase the time gap between two refueling points. Hybrid vehicles with a tandem between hydrogen and proton exchange membrane fuel cell is an effective way to store and convert chemical energy directly into electricity (Aschilean et al. 2018).

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6.2.5  Storage Systems 6.2.5.1  Current Feature Current electric vehicles use nickel cadmium batteries for their energy storage. Nickel Cadmium (Ni-Cd) batteries have certain advantages such as lower dependencies on the discharge rate and its high-power density. Due to these reasons, these batteries provide longer life cycle and consistent range which is provided by these batteries. Ni-Cd batteries have the specific energy of 35 Wh/kg and it has been in use since 1998 electric vehicle (Biradar et al. 1998). 6.2.5.2  Short Term Advancement in battery technologies have evolved and a newly introduced battery is Nickel-Metal Hydride. Ni-Mh batteries are scaled and they require no maintenance and their specific energy has been improved to 50 Wh/kg. These batteries are known to be environmentally friendly. One major advantage of Ni-Mh batteries is the fact that no cadmium is used in the whole entire cell (Biradar et al. 1998). 6.2.5.3  Long Term New proposed technologies in the batteries are through sodium-Sulfur (Na-S). Projected energy density of Na-S batteries is known to be 80 Wh/kg. In addition, these battery types can operate in a wider temperature range from 350 to 380 °C due to both the temperature operation and reactivity of sodium (Biradar et al. 1998).

6.2.6  Connected Cars The concept of connected cars deals with the ability of the car to offer convenience services like emergency dispatch, connected maps, concierge, and internet radio. There are numerous amount of technologies which are present in a car but the telematics control unit is the core component of the vehicle which grants the car the ability to connect. The three primary connected systems are embedded, tethered, and smartphone (Kollaikal et al. 2015). 6.2.6.1  Gaps The connected car functionality allows for functions that can remotely allow access to vehicles, e.g., keyless entry, preconditioning, or window entry. The body control module (BCM) is a gateway between the vehicular networks of the car and these

6.2  Product Feature in Automotive

39

functionalities allow a wireless entry point towards BCM and therefore is prone to physical and remote attacks (Modwel et al. 2015). 6.2.6.2  Short Term Connected cars come up with the functionality of self-parking or auto-collision avoidance features. However, till the vehicles cannot drive itself independently it cannot be called a true autonomous vehicle. The short-term transition from connected cars is a fully autonomous vehicle (Raposo et al. 2017). 6.2.6.3  Long Term Connected autonomous road transport (C-ART) is an extension of the automated vehicle concept which adds communication capabilities and connects vehicles in between. There is also an addition of a central coordination player which helps achieve full potential of automated driving in terms of social, economic, and environmental benefits (Raposo et al. 2017).

6.2.7  Smart and Recycle Material 6.2.7.1  Steel The composition of vehicles since 1920 has been low-carbon steel. Currently, high-­ strength steel is the major contributor towards one-third of the steel on vehicle. The composition of high-strength steel continues to grow. The challenges still lie with high-strength steel although it is strong and difficult to weld, repair and heat-treat (Taub 2006). 6.2.7.2  Aluminum Nowadays, lightweight materials for instance aluminum, magnesium, and high-­ strength plastics are become more prevalent in use and are being replaced by the conventional steel in vehicles. General Motor is one of the leading companies that have become the user of aluminum and magnesium in automotive sector. Main ­reason of adapting these materials is due to improved performance and improved fuel economy cost (Singh 2016).

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6.2.7.3  Plastic The development and research of new materials is a permanent process. The innovation in lighted polypropylene, blended thermoplastic materials, and biodegradable plastics are examples of continuous growth in research in plastics (Szeteiová 2010).

6.2.8  Roadmapping of Product Features After evaluation of the product features, the features are distributed according to the timeline considering their relative importance. The product features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the product features are ranked, they are placed on the roadmap according to short term and long term, e.g., “Ni-Mh batteries” could be considered as a short-term product feature of battery type in automobile, whereas “Na-S batteries” could be determined as a long-term product feature. Figure  6.2 shows the product feature with respect to short and long term.

6.2.9  Mapping of Product Features and Market Drivers The mapping of product features and market drivers which in other words is the link between product features and market drivers is performed using a quality function deployment. The market drivers are listed on the x-axis (horizontally) and product features are listed on the y-axis (vertically). Next, the market drivers which are weighted by the experts are given a correlation with the product features on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation, and 3 denotes complete correlation. Henceforth, the summation of the product of market drivers and product features is performed and illustrated in the “total” column and finally a “rank” is given based on the total score. Table 6.3 depicts the QFD matrix for market drivers vs. product features and which are rated per experts’ opinions.

Fig. 6.2  Roadmapping of product features—automotive

Emission Safety Customizable Efficient engine Storage system Connected cars Smart and recyclable material

Product features

Market driver Weight Levels

Sustainability 7 D1 2 0 0 2 3 0 2

Customer experience 8 D2 1 3 3 3 2 3 2 Digitalization 8 D3 2 1 2 2 1 3 0

Table 6.3  QFD matrix for market drivers versus product features—automotive New market 8 D4 1 1 0 1 1 2 2 Cost 7 D5 1 0 2 2 3 1 3

Fuel efficiency 8 D6 1 1 0 3 2 0 2

Manufacturing process 6 D7 0 0 3 0 0 0 1

Disruptive models 6 D8 1 0 3 2 3 2 2

67 48 90 112 108 83 101

Total

4 1 2 5 3

Rank

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42

Table 6.4  Technology feature—automotive Technology features Emission reduction technology Anti-skidding Modular platform

Current level Non-thermal plasma (NTP) – –

Short term ~ 3 years Model catalytic convertor ABS3 Platform 2.0

Fuel efficient

–

PHEV

Battery systems Interconnected devices Carbon fiber

Li-ion battery – –

LiPF6 Cloud computing Lignin

Long term ~ 7 years Turbo charging ABS Spoofer Scalable product architecture Parallel and hybrid PHEV Silicon-based anodes Floating car data Lignocellulosic sugars

6.3  Technology Feature in Automotive The technology features in the section deal with the features required in the automobile which would be necessary to satisfy the market drivers. The technology features enlisted in the table below are further segregated into short-term (~3 years) features and long-term (~7 years) features. The gaps mentioned later on depict the shortcomings in the current technology features and which could be addressed by short-term and long-term goals. Table 6.4 depicts the technology features summary based on short and long term and present status.

6.3.1  Emission Reduction Technology Air pollution could be defined as the emission of toxic gases such as CO2, CO, HC, SO2, and NOx from industrial plants, automobiles, aircrafts, and other potent sources of air degradation. Air pollution which is emitted from vehicles and mobile sources contributes to the air quality, which eventually leads to health problems for the society (Balan et al. 2017). It is expected that the vehicle population grow to almost 1300 million by 2030 while being around 700 million in the world (Piumetti et  al. 2016). Hence, it becomes relevant to tackle the issue of emission from one of the sources, which is, automobiles. Due to stringent regulations, several catalytic DeNox have been researched for lean-burn conditions. The three used catalysts are: direct decomposition of NOx, selective catalytic reduction (SCR) by using different reducing agents (e.g., ammonia/urea, hydrocarbons), and NOx storage reduction. However, these three-way catalysts cannot reduce NOx when the excess oxygen is present. The reason being is that high amount of oxygen reduces the reactions (Piumetti et al. 2016).

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Another investigated technology to reduce the NOx and PM emission is the implementation of non-thermal plasma (NTP) discharge in the exhaust gas. NTP is produced by electrical excitation which is to induce unstable NOx species and it should decompose to N2 and O2 (Piumetti et al. 2016). NTP as a potential technology is proposed for reduction of NOx and PM emissions in diesel exhaust mechanisms. Engine features such as high pressure drop, complicated control systems, and the limitation due to weight and space consumption are linked to the piling up of expensive catalytic convertors which in turn is due to the strict regulations in the automotive industry for both NOx and PM emissions (Piumetti et al. 2016). 6.3.1.1  Gap Exhaust gas recirculation (EGR) is considered as one of the most effective ways to control NOx emissions without significant modification in the diesel engine; however, the application of EGR cannot be done alone. Emission reduction suggests that the demand to reduce the NOx emissions is still a challenge and the levels of the same remain critical. Research emphasizes and focuses on effective techniques to meet the Euro VI standards in general (Hebbar 2014). 6.3.1.2  Short Term Based on a study performed by Messerer et  al. (2004), an experiment was conducted to model a catalytic converter system based on the development of filterless soot deposition systems for constant removal of diesel particulate matter. The objective was to identify the catalyst structures for the filterless diesel particulate deposition as well as oxidation in heavy vehicle exhaust system (Messerer et al. 2004). In order to avoid the clogging effects in ceramic filters, particular traps are designed to enable low exhaust gas back pressure. A deposition efficiency of 70% has been achieved under realistic flow conditions for sub-micrometer particles. In order to study the kinetics of soot oxidation, a model catalytic convertor is used under different reaction conditions. For the soot in real diesel engine, different model soot substances are used (Messerer et al. 2004). 6.3.1.3  Long Term One of the technologies that can be used in the emission reduction is the usage of turbo charging. This technique can at the same time improve the fuel economy and reduce the PM emissions. More air can be forced into the combustion chamber by having the turbocharger which compresses the air entering the cylinder of a vehicle. Having an excess air in the combustion chamber provides two distinct advantages. Firstly, excess air provides a complete combustion, which results in reduction in the

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PM emission. Secondly, more fuel is added to the chamber, which results in more generated power compared to an engine without turbocharging mechanism. Also, the engine weight and the overall fuel economy are improved by having generated more power (Maiwada et al. 2016).

6.3.2  Anti-Skidding 6.3.2.1  Gap The control in an anti-lock braking system (ABS) is an issue because of uncertain and nonlinear characteristics. Also, the stable vehicle orientation cannot be generalized for every road type and ABS can result in longer stopping distances (Oniz et al. 2009). 6.3.2.2  Short Term The third generation of ABS now provides greater speed and precision due to enhanced brake pressure control. The brake performance is optimum due to the more adaptive controller design. The abilities of ABS3 would enable the cars to respond to the changes and the drivers can retain control of their vehicles (Ruehling 2018). 6.3.2.3  Long Term In order to protect the ABS from spoofing attacks, a hardware could be setup like ABS spoofer module utilizing the industrial ABS sensors and wheel speed decoders. The proposed methodology is for ABS sensors where an electronic module is designed to evaluate the feasibility (Shoukry et al. 2013).

6.3.3  Product Platform 6.3.3.1  Current Feature Automotive industry is embedded in manufacturing industry. Mass Customization Manufacturing (MCM) has become a prevalent concept in twenty-first century. MCM has gained recognition by providing flexibility to respond to the rapid change of market and the competition. Current market share and success of manufacturing relies on the order fulfillment and new acquiring methods in customer acquisition while having the ability to adapt to the abrupt and unforeseeable changes (Qiao et al. 2006).

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Thus, the main identified goal of MCM is to manufacture customized products in an agile manner while having the costs comparably low as mass production by utilizing the economies of scale. Joseph Pine was one of the pioneers to give a strategy back in 1993 to recognize the necessary exploitation of product variety and individualization (Qiao et al. 2006). 6.3.3.2  Short Term Virtual-Build-to-Order (VBTO) is an approach that was proposed by Agarwal et al. VBTO approach is an enabler in mass customization that can be used in the process of designing and process management. This approach ascertains that no matter at what stage the product is located either in planning status, under manufacturing, or even finished products are all “open to view” and can at the same time be allocated to the customers (Brabazon et al. 2010). 6.3.3.3  Long Term The main goal of Modular Vehicle (MODV) is to create one single vehicle design that can accommodate for all terrain types known as All-Terrain Vehicle (ATV). This concept provides 24-h configurability of car to respond to different climate and terrain combination. By only swapping the traction components, the vehicle can be easily configured to meet different terrain requirements. In addition, this concept provides an efficient energy transfer which is its advantage. Higher energy transfer is achieved through implementation of power transfer from the vehicle batteries to the hub motors which is based on electrical means compared to the conventional mechanical power transfer (Rue 2015).

6.3.4  Modular Platform 6.3.4.1  Current Feature A standardized platform is one of the main targets to gain efficiency in design and development process and to achieve economies of scale. The initial goal by the car manufacturers was to have optimization in the assembly process. Modularization has emerged as a way to improve scale and scope economics and operational flexibility (Lampón et al. 2017). 6.3.4.2  Short Term Platform 2.0 strategy presents itself as a new feature for modularization. From the perspective of design, modular principles are key points which allow for an increasing number of models to be built from a single platform. The aim here is to combine

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vertical and horizontal variety. This method of modularization not only makes it possible to assemble several models but also enables different models from different segments (Fleiss et al. 2016). 6.3.4.3  Long Term The Scalable Product Architecture (SPA) is a modular chassis technology which has been introduced by Volvo. The Volvo XC90 is the first car application on the SPA architecture. The new architecture allows for a new domain based electrical architecture. This has also enabled a drive-E power train which is based on compact and modular gasoline and diesel engine architecture (Fleiss et al. 2016).

6.3.5  Efficient Engines 6.3.5.1  Gap The reliance on chemical energy portrays a problem. The problem with chemical energy is that it is available in form of potential energy and therefore must be converted to other forms before being used (National Energy Strategy n.d.). 6.3.5.2  Short Term One solution to provide cost-efficient and optimized energy for vehicles is usage of Plug-in Hybrid Electric Vehicles (PHEV). PHEV is an effective and novel approach in order to address the increasing problems arising from traffic congestion and environmental issues. In this topology, a combination of dual battery that is powered as PHEV is used. This approach optimizes the utilization of energy sources which also depends on the driving conditions. There are certain advantages in using PHEV such as: the engine never goes in idle that results in reduction in vehicle emission, engine is assured to be used in its specified efficient region, engine has the ability to drive the generator to operate at its optimum point and due to swapping capability of engines, the battery life is increased up to 12 years (Vishnu and Ajaykrishna 2011). 6.3.5.3  Long Term PHEV system comes with two power train mechanisms: parallel hybrid and series hybrid. Parallel Hybrid: The standard model of hybrid drivetrain uses its Internal Combustion Engine (ICE) to power up the wheels directly while using the excess ICE power to act as a storage through electric generator and battery pack for the later use (Vishnu et al. 2012).

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Series Hybrid: Unlike the parallel hybrid, in series hybrid all the power drive reaches to the wheels through electric motors. It is claimed that the series hybrid is more efficient than the parallel hybrid due to fact that the electric motors should act independently powerful to provide sufficient power to the vehicle without requiring assistance from ICE power unit. As shown in the figure, the output of gasoline engine is connected to a generator, and the electricity being produced by the motor could be used for purpose of charging the starter battery or providing enough power to traction motor if the battery is discharged during critical situations (Vishnu et al. 2012).

6.3.6  Battery Systems 6.3.6.1  Current Feature Electric vehicles nowadays utilize Li-ion battery as their main battery technology due to higher energy density and more power per mass battery unit. Studies show that Li-ion battery is the best available solution with respect to “charge to weight.” Apart from that, another main advantage of Li-Ion is independence to memory capacity which results in increased life cycle. Another disadvantage which can be stated is the memory effect loss (to gradually diminish the energy capacity in case of repeated recharge and without being completely discharged), which leads to an increased life cycle (Iclodean et al. 2017). 6.3.6.2  Short Term One way to improve the lithium batteries is to investigate the fast chargeability of them. Experiments prove that the batteries can charge properly at 0 and 20 °C. The chemistry behind the lithium polymer is the lithium cobalt dioxide which is the positive electrode and a crystalized carbon at the negative electrode. The reactions are mediated by electrolyte. The electrolyte present as liquid in the lithium polymer battery contains LiPF6 (Lithium Hexafluorophosphate) as well as organic solvents. Despite having different battery in the market, majority of the batteries cannot overcome the barriers for fast charging batteries according to the standard given by Advanced Lead Acid Battery Consortium known as ALABC (Kim et al. 2008). 6.3.6.3  Long Term New proposed technology in the Li-ion battery is to use silicon-based anodes. Main reason for silicon to be the adapted material is its high specific capacity. Nanostructured silicon anodes are validated to have superior specific capacity as well as life cycle comparing with conventional carbon-based anodes. Silicon has the theoretical lithium storage capacity of 4200 mAhg−1 which is more than the current

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prevalent carbon-based anodes. Due to abundance and environment compatibility of silicon, it has made itself as a potential substitute for carbon-based anodes (Feng et al. 2018).

6.3.7  Interconnected Devices 6.3.7.1  Gap Collection of floating car data from fleets of vehicles is an excellent way to support the application of intelligent transport systems. The major shortcoming that is caused is the insufficient penetration rate. There is also a question on the reliability of travel time information on paths. Also, the concept of new mobility services needs data which are difficult to obtain through established data collection methods (Brockfeld et al. 2007). 6.3.7.2  Short Term Cloud computing imparts high scalable and virtual storage or network resources which helps to enable services on demand. Cloud computing envelops distributed data storage, data parallel programming models and implementations. For geospatial computing, cloud computing offers the opportunity to perform large-scale and efficient geospatial data processing tasks (Li et al. 2011). 6.3.7.3  Long Term Estimation of time travel in vehicles is a major roadblock in the domain of prognosis of dynamic traffic. Another way is the increment in the count of sensor objects which are considered in the road network. For this, floating car data (FCD) which includes vehicle formation pertaining to travel time is passed via the long-term evolution (LTE) to the server (Ide et al. 2012).

6.3.8  Carbon Fibers 6.3.8.1  Short Term Current carbon fibers are produced from polyacrylonitrile (PAN) precursors. Yet, those petroleum-based precursors and its carbon fibers processing costs remain as a limiting factor which has been used for special usage in different industries such as aerospace, sporting goods, high end automotive, and other types of applications.

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49

Lignin is being the most prevalent carbon fiber material for the purpose of manufacturing. The process involves the preparation of a suitable lignin which under the effect of an inert atmosphere is melt-spun into fiber. The lignin fiber at the end is thermo-stabilized and also carbonized (Baker and Rials 2013). 6.3.8.2  Long Term Lignocellulosic sugars are a biomass material. The new R&D findings refer to extraction of carbon fibers from lignocellulosic sugars which possesses technical and economic feasibility. Lignocellulosic sugars have the equivalent functionality to (polyacrylonitrile) PAN-based carbon fibers. This process is still in the R&D phase and commercializing it requires new manufacturing development and bigger commercialization process. On the other side, the accessibility of lignocellulosic sugars suffers from feedstock competitions from other sectors, for instance power generation and transportation (Baker and Rials 2013).

6.3.9  Roadmapping of Technology Features After evaluation of the technology features, the features are distributed according to the timeline considering their relative importance. The technology features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the technology features are ranked, they are placed on the roadmap according to short term and long term, e.g., PHEV is a short-term feature, whereas PHEV with power train mechanism is a long-term feature. Figure  6.3 shows the technology features in automotive sector.

6.3.10  Mapping of Technology Features and Product Features The mapping of product features and technology features which in other words is the link between product features and technology features is performed using a quality function deployment. The product features are listed on the x-axis and technology features are listed on the y-axis. Next, the product features which are

Fig. 6.3  Roadmapping of technology features—automotive

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6  Value Roadmap Development for Automotive Industry

weighted by the experts are given a correlation with the technology features on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation, and 3 denotes complete correlation. Henceforth, the summation of the product of product features and technology features is performed and illustrated in the “total” column and finally a “rank” is given based on the total score. Table 6.5 depicts QFD matrix for technology features vs. product features.

6.3.11  Roadmapping of Enablers After evaluation of the enablers as mentioned in Sect. 6.3, the enablers are distributed according to the timeline considering their relative importance. The enablers’ features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the enablers are ranked, they are placed on the roadmap accordingly, e.g., “augmented reality” could be a long-term prospect for achieving the required technology features. Figure  6.4 shows the timeline of industry 4.0 enablers’ roadmap.

6.3.12  Mapping of Technology Features and Enablers The mapping of technology features and enablers, which in other words is the link between technology features and enablers is performed using a quality function deployment. The technology features are listed on the x-axis and enablers are listed on the y-axis. Next, the technology features which are weighted by the experts are given a correlation with the enablers on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation, and 3 denotes complete correlation. Henceforth, the summation of the product of technology features and enablers is performed and illustrated in the “total” column and finally a “rank” is given based on the total score. Table 6.6 shows QFD matrix for enablers vs. technology features.

Technology features Emission reduction technology Anti-skidding Cyber protection systems Product platform Fuel efficient Battery systems Interconnected devices Carbon fibers

Product features Weight Levels 0 3 3 0 1 0 0 3

0 0

0 2 0 0 0

Safety 9 P2

3

Emission 7 P1

2 0 2 0 1

0 0

0

Customizable 6 P3

0 2 2 0 0

0 0

2

Efficient engines 7 P4

Table 6.5  QFD matrix for technology features versus product features—automotive

0 1 3 0 0

0 0

0

Storage systems 8 P5

1 0 0 3 0

0 1

0

Connected cars 7 P6

1 2 2 0 2

0 0

2

Smart and recyclable materials 7 P7

26 59 64 21 47

27 34

Total 49

4

2 1

5

Rank 3

6.3  Technology Feature in Automotive 51

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6  Value Roadmap Development for Automotive Industry

Fig. 6.4  Roadmapping of enablers—automotive

Big data Predictive maintenance Cloud computing Digital twin Autonomous robots Augmented reality Sensors 3D printing

Enablers

Technology features Weight Levels Anti-­skidding 8 T2 1 3 2 1 0 0 2 0

Emission reduction technology 7 T1 3 2

3

1 0

2

3 1

0 0

1

0 0

2

Cyber protection systems 7 T3 2 0

Table 6.6  QFD matrix for enablers versus technology features—automotive

0 3

1

1 2

0

Product platform 6 T4 0 0

3 2

2

2 0

2

Fuel efficient 8 T5 3 0

2 0

0

0 0

0

Battery systems 8 T6 1 0

3 0

2

3 0

2

Interconnected devices 7 T7 2 0

98 41

57

58 12

81

Total 89 38

1

5

4

3

Rank 2

6.3  Technology Feature in Automotive 53

Chapter 7

Value Roadmap Development for Healthcare Industry

Due to many factors it is important to have a transformation in the health services. The focus should be on the General Practitioner (GP)-led primary care. To be able to have a strong GP-led care, there should be appropriate and sufficient amount of investment in prevention (ILC-UK 2012). It should also be understood that government, healthcare institute providers need to accept the fact that prevention might decrease the investment in other forms of health and at the end can enhance the overall health related issues.

7.1  Market and Business Driver 7.1.1  Demographic Changes One of the drivers in healthcare system is changes in aging population as well as an increased observation in chronic disease. As it has been reported by Tontus (2017) based on data analyzed by the United Nations, increase in population of people above 65 years in developing countries is going to rise up from 17% today up to 24% by 2035. In addition, average global life expectancy has gone up 72  years while in 2005 the average global life expectancy was reported to be 69 years which shows over 4.3% rise in a 12-year period. Looking at the USA as an example, in 2010 baby boomers has reached to the retirement phase and hence has resulted in more demand for healthcare. This has caused many hospitals and healthcare providers facing problems in terms of increased number of patients and one strategy that US hospitals have implemented is utilization of offshore hospitals to address some portion of the demand (Tontus 2017).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_7

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7.1.2  Cost Taking the USA as an example, it is important to highlight that the USA is the only country in the range of developed countries that does not have a national healthcare system. Private healthcare insurances are provided by the employers; however, they are considered poor in terms of health performance. It is also reported that American citizens pay twice the price for their healthcare treatment for the comparable quality in other countries. Hence, this leads to immense pressure on the health providers and individuals for financing it (Tontus 2017).

7.1.3  Quality (Improved Clinical Outcomes) When the focus comes into quality, it is clear that emerging countries (together with the USA and Europe) are utilizing more modern facilities which can offer medical procedures for half the price in other western countries. Standard international accreditation certificates are also growing in terms of popularity and many service providers are keen on obtaining them. One of the reasons is that the main focus of patient care is achieved by the fundamental requirement of establishing common protocols for the continuous care, proper measures for discharge process, referral, check-up, and transfer of patients (Tontus 2017).

7.1.4  Access to Care (Increase in Consumer Experience) One of the recent trends that has been identified with respect to quality and the price is “medical tourism.” Hence, access to care is often constrained by high charged price or long waiting time. In addition, majority of national healthcare programs do not cover the cosmetic surgeries, dental procedure, and other similar services, hence many patients from the USA, Canada, and the UK travel to seek medical procedures for economic reasons (Horowitz et al. 2007; Tontus 2017). Some concerns have been raised by Horowitz et al. (2007) that medical tourists might find it hard when it comes to identifying a well-trained and educated physicians and hospitals that are equipped with high quality care. Hence, some standards can be checked which would help patients in identifying appropriate healthcare providers, for instance, accreditation by the Joint Commission International. This accreditation is granted for more than 125 facilities in 24 countries around the globe. In addition, International Organization of Standardization could give insightful information and reference points for the patients when it comes to offshore medical facilities selection (Horowitz et al. 2007).

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57

7.1.5  Waiting Time/List As it was discussed, one of the elements of prevalent emergence of medical tourism was a long waiting time in the home countries which mostly is associated with high cost (European Commission 2014). In medical tourism destination, the waiting time is minimal and elective surgeries such as hip replacement, cholecystectomy, and prostatectomy are performed. This short waiting time includes shorter time for an appointment, surgical operations, and follow-ups/check-ups. One example could be in terms of hip replacement time in the UK which takes almost 2 years while in many other medical tourism destinations there is no waiting time (Horowitz et al. 2007; Tontus 2017). Table 7.1 illustrates the identified market drivers along with the rated weightage based on expert opinions from scale 1 to 10 with 1 having the least and 10 with the highest weightage for the healthcare industry. The average weight is taken for the final illustration.

7.1.6  Roadmapping of Market Drivers After evaluation of the market drivers, the drivers are distributed according to the timeline considering their relative importance. The drivers are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the drivers are ranked, they are placed on the roadmap according to short term and long term, e.g., “cost” is a long-term market driver as healthcare costs are very significant when it comes to customer satisfaction. Figure 7.1 shows the roadmap of market drivers for healthcare industry. Table 7.1  Market drivers evaluation—healthcare Drivers Demographic changes

Definition One of the drivers in healthcare system is changes in aging population as well as increase observed in chronic disease Cost The cost of healthcare systems has been increased drastically and is not distributed globally Quality (improved Emerging countries are utilizing more modern facilities clinical outcomes) and the gained popularity in obtaining international standard accreditation has resulted in increased quality of care Access to care (increase Access to care is often constrained by high charged price or long waiting time. Hence new concept of “medical in consumer tourism” has emerged experience) Waiting time/list One of the elements of prevalent emergence of medical tourism was a long waiting time in the home countries which mostly is associated with high cost

Average weight 8 8 9

7

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58

Fig. 7.1  Roadmapping of market drivers—healthcare Table 7.2  Product feature—healthcare Product features Data transmission through sensors Reduce health accidents Pharmaceutical therapy User experience Load reduction on hospitals

Current level Short term ~ 3 years Wireless sensor network Faster data mechanism Monitoring health status Aladdin platform using sensors Nanosensors High sensitivity biosensors Gamification Patient to doctor interaction using apps Wearable sensors Remote health monitoring and alert system

Long term ~ 7 years – Portable health monitoring devices Colorimetric nanosensors Health wearables as a necessity Wireless network sensors

7.2  Product Features in Healthcare The product features in the section deal with the features required in the healthcare which would be necessary to satisfy the market drivers. The product features enlisted in the table below are further segregated into short-term (~3  years) features and long-term (~7 years) features. The gaps mentioned later depict the shortcomings in the current product features and which could be addressed by short-term and long-­ term goals. Table 7.2 depicts the technology features summary based on short and long term and current status.

7.2.1  Data Transmission Through Sensors 7.2.1.1  Current Feature In the coming years, the usage and applications of wireless sensor network (WSN) is going to gain more attractions. Therefore, real-time monitoring requires real-time wireless sensor network which would result in higher reliability and timeliness of data transmission and will be well justified for industrial application for the purpose of monitoring and closed loop control (Pöttner 2014).

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7.2.1.2  Short Term Data is one of the main key elements which organizations are deeply relied upon. The data has many different sources and is collected via a distributed network that results in different data types and formats. There should be another process of cleaning data source which is subjected to algorithms which is time consuming (Gatimu et al. 2015). Technological innovation exists within the domain of data warehouses, where the process involves data manipulation which is carried out before the data gets transferred to target systems (Gatimu et al. 2015).

7.2.2  Reduce Health Accidents 7.2.2.1  Current Feature Individuals’ physiological conditions and health can be monitored through wearable devices. Different flexible healthcare monitoring sensors are deployed which can be further integrated into textile fiber, elastic bands or directly placed on the human body. Various physiological signs can be measured such as electrocardiogram (ECG), electromyogram (EMG), heart rate (HR), body temperature, electro dermal activity (EDA), blood pressure (BP), and so forth (Majumder et al. 2017). 7.2.2.2  Gap It is quite clear that in order for the data to be useful, it requires to be meaningful and easy to comprehend by the users. Many studies show that in order to keep the user encouraged to support the process for a long period of time, less raw data and ambiguous numbers shall be used. For example, one study illustrates that the usage of pedometer by the users lose its attraction after a certain point in time which is due to large amount of data provided (Haensel et al. 2015). 7.2.2.3  Short Term Technology can be exploited in order to decrease the impact of health accidents. One example is the Aladdin platform which has been developed to assist elderly and care whom they suffer from dementia. This project provides an integrated online and social support platform for both the patients suffering from dementia and their caregivers with the aim of providing planning, health management, and monitoring of patient’s health status (Dolićanin et al. 2015). This technology is able to prevent the emergency accidents and situations due to changed symptoms, cognitive functions as well as monitoring behavioral aspects,

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reducing the stress level for home care system and in general the quality of life has been increased (Dolićanin et al. 2015). 7.2.2.4  Long Term Statistics suggest that there is a high correlation between driver’s sudden medical conditions and car crashes. Sudden medical illness refers to loss of consciousness such as heart attack. Development of portable health monitoring devices and system which can constantly be used to monitor health conditions can be a solution to reduce the car crashes due to sudden medical illnesses. This device can prevent the car accident by informing the driver prior to the heart attack condition and asking him/her to stop as well as providing appropriate information for caregivers. Hence, driver’s life can be saved through applications which health monitoring system can provide (Chowdhury et al. 2018).

7.2.3  Pharmaceutical Therapy 7.2.3.1  Current Feature In order to have portable health monitoring devices, nanosensors are required to be used. Nanosensors are referred to special type of sensors that are used to transfer relevant biological data from the nanoparticles to the higher level macroscopic. In other words, the nanosensors are deployed to detect the chemicals existing in nanoparticles or the temperature changes. In addition, it is worth noting that the process of making nanosensors requires different approach levels such as top-down lithography process, bottom-up assembly as well as molecular self-assembly (Raparthi n.d.). 7.2.3.2  Gap Advances in nanotechnology field have resulted in fabricating different variety of structures with specific electrical and mechanical properties of material which has derived from classical physics, for instance Maxwell’s equations. There are issues involved with miniaturization of sensors. One of the issues involved is the fabrication of a nanosensor compared to a larger sensor. One of the concerns associated with miniaturization is the decrement in precision measurement, which results in poor limits in detection (Dahlin 2012).

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7.2.3.3  Short Term Conventional diagnostic mechanism for chronic diseases especially like cancer involves different methods of diagnosis such as endoscopy, X-rays, positron emission tomography, MRI, and so forth. Yet, these methods are not accessible to all the population and they are not repeated for early stage diseases (Swierczewska et al. 2012). One way to increase the practicality of diagnosis is to deploy optical sensing which is done through nanosensors. These optical detections illustrate a high sensitivity due to unique interactions made between the nanomaterial and the light wave (Swierczewska et al. 2012). 7.2.3.4  Long Term For the purpose of clinical and personalized point-of-care diagnostic, colorimetric detection for the target analytes for identifying the chemical constituents is required. These colorimetric nanosensors are highly sensitive and come with high specificity and because of their special optical properties, plasmonic nanomaterials are integrated into colorimetric sensing mechanism (Li and Tang 2017).

7.2.4  User Experience 7.2.4.1  Current Feature After recent advancement in the era of information technology, new concepts of design features were borrowed from video games industry and the terminology coined was “gamification.” Gamification is aimed to enhance the user’s motivation and provide an interactive platform for the activities via usage of the technology (Morschheuser et al. 2017). A study performed in the Motivation and User Engagement in Fitness Tracking reveals three key areas of user experience which have a direct implication on both motivation and efficacy of the user. Tracking in real time and large info-graphic content of mission is what is primarily supportive of gamification (Asimakopoulos et al. 2017). 7.2.4.2  Gap It might be a wonder to know that even in today’s twenty-first century, still there are people even in the developed society suffering from health illiteracy. Studies show that half of American adults have very limited health literacy when it comes down to finding relevant information related to health which is associated with certain negative result obtained from overall poorer health (Mackert et al. 2016).

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Health information technology also known as HIT can provide a platform for making health related information available to the patient through wearable devices and electronic tools. In addition, there might be a misunderstanding due to complicated HIT privacy and information for the patient due to direct flow of information (Mackert et al. 2016). 7.2.4.3  Short Term Different aspects of clinical practices are influenced by the usage of mobile devices through Health Care Professionals (HCPs). Due to increase in growth of mobile devices in healthcare service, other medical software applications (Apps) are becoming mainstream. Nowadays, it can be seen that many number of apps are available in the market to help the purpose of HCPs. These apps are identified to provide vital information such as health record maintenance, accessibility and time management, communication and consulting, clinical decision-making, and health training and education (Ventola 2014). 7.2.4.4  Long Term The major causes of death globally are resulted from chronic diseases. These diseases are mainly due to unhealthy lifestyle such as limited physical activities and bad diet. The chronic diseases not only contribute to severe amount of care and constant medication but also are the main driver for the whole healthcare system expenses in the world (Spil et al. 2017). Knowing that accessibility to mobiles and smartphone is quite common in todays’ life, this can promote healthy lifestyle applications that has risen from the utilization of smartphones (Spil et al. 2017).

7.2.5  Load Reduction on Hospitals 7.2.5.1  Current Feature Wearable sensors are a type of sensors that can be worn on body. These sensors are very important in monitoring the physiological parameters for the sake of diagnosis of health issues and diseases (Islam and Mukhopadhayay 2017). Sensors measure physical parameters such as motion, stress, vibration, and other parameters which can result in diagnosis of different type of diseases. Accelerometers are used to monitor activities of human body such as predicting and detecting of falling, movement and motion analysis as well as postural orientation. Also, another type of sensor is an inertial sensor which monitors the physical parameters. These sensors are also helped in detecting the fall and postural orientation (Islam and Mukhopadhayay 2017).

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63

7.2.5.2  Gap Some recent incidents such as earthquakes and wars have displayed the need for physiology sensors which are portable, scalable, and low cost. Advancements in the field of battery technology and materials science are enabling new forms of wearable sensors and health systems which are low cost but still a lot of progress needs to be made so as to reach the mass (Fletcher et al. 2010). 7.2.5.3  Short Term It is a burden when it comes to monitoring of elderly people as normally they are alone in the time of incident and emergencies. There are a few available monitoring devices which are targeted for the elderly people, and those that are targeting the elderly demographic are barely wireless and wearable. The existing devices are wired up and only suitable for admitted patients. One way to tackle this issue is to use Remote Health Monitoring and Alert System (RHMAS). RHMAS is an improved tool over the existing systems which is wearable and does not hinder the movements of patients. The main objective of this development is to establish a mechanism for healthcare systems and relatives to ensure an appropriate response in the times of danger for their potential sufferers. One main advantage of RHMAS is its cost-effectiveness as it does not require very sophisticated sensor technology (Valliappan et al. 2017). 7.2.5.4  Long Term Over the past couple of years, wireless sensor network (WSN) technologies are being developed. Sensor nodes are used for the purpose of monitoring. Battery powered WSNs comprises different sensors, processors, and RF (Radio Frequency) modules. Sensor nodes communicate via a communication link wirelessly and they transmit data to the base station by communication through a gateway (Jawad et al. 2017).

7.2.6  Roadmapping of Product Features After evaluation of the product features, the features are distributed according to the timeline considering their relative importance. The product features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the product features are ranked, they are placed on the roadmap according to short term and long term, e.g., “export of data” regarding human health that has to be passed from the human body to the wearables is a long-term product feature since the data evaluation is essential for providing necessary services to the customers. Figure 7.2 shows the product feature with respect to short and long term.

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64

Fig. 7.2  Roadmapping of product features—healthcare

Table 7.3  QFD matrix for market drivers versus product features—healthcare

Product features Export of data Reduce health accidents Pharmaceutical therapy User experience Load reduction on hospitals

Quality (improved clinical Market Demographic driver changes Cost outcomes) Weight 8 8 9

Access to care (increase in consumer experience) 7

Waiting time/ list 7

Levels D1 0 0

D2 2 1

D3 2 1

D4 1 3

D5 0 3

Total Rank 41 5 59 4

0

2

2

1

2

55

3

2

2

3

2

2

87

1

1

2

3

3

1

79

2

7.2.7  Mapping of Product Features and Market Drivers The mapping of product features and market drivers which in other words is the link between product features and market drivers is performed using a quality function deployment (QFD). The market drivers are listed on the x-axis and product features are listed on the y-axis. Next, the market drivers which are weighted by the experts are given a correlation with the product features on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation, and 3 denotes complete correlation. Henceforth, the summation of the product of market drivers and product features is performed and illustrated in the “total” column and finally a “rank” is given based on the total score. Table 7.3 depicts the QFD matrix for market drivers vs. product features and which are rated per experts’ opinions.

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Table 7.4  Technology feature—healthcare Technology features Data transmission Health detection systems Pharmaceutical therapy imitation Personalization

Sensor technology

Current level Wi-Fi Physical activity monitoring devices

Short term ~ 3 years IEEE 802.11 RFID enabled wireless mobile multimedia information system On-body biosensor Electrowetting on dielectric devices Continuous ambulant monitoring PVDF piezoelectric polymer film

Intelligent biomedical clothing Wearable antenna on metal watch strap

Long term ~ 7 years Li-Fi IS-active system

Giant magnetoresistance biosensors WatchThru

Liquid antennas

7.3  Technology Features in Healthcare The technology features in the section deal with the features required in the healthcare which would be necessary to satisfy the market drivers. The technology features enlisted in the table below are further segregated into short-term (~3 years) features and long-term (~7 years) features. The gaps mentioned later on depict the shortcomings in the current technology features and which could be addressed by short-term and long-term goals. Table 7.4 depicts the technology features summary based on short and long term and current status.

7.3.1  Data Transmission 7.3.1.1  Current Features Wireless communication is currently one of the standards in the world. Wi-Fi is basically an open standard technology that enables connectivity between equipment and local area networks. Wireless internet connection does have an impact on the businesses conducted around the world. Wi-Fi which is also known as 802.11b, 802.11g, and 802.11a has emerged as one of the dominant standards for wireless LANs around the world (National Telecom Regulatory Authority 2003). 7.3.1.2  Gap Research still goes into improving the speed provided by the current Wi-Fi technology. It has been stated that increasing the distance from the wireless router leads to a decrease in the signal strength. Numerous other measurements can be performed

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to signify the effect of different objects and factors on strength of Wi-Fi signal (Soldo and Malarić 2013). 7.3.1.3  Short Term The IEEE 802.11 wireless local area networks for wireless internet are cost-­effective solutions which can satisfy majority of the communication requirements in different scenarios be it domestic, public, or business. As stated by Bellalta (2015), the IEEE 802.11ax-2019 will replace the IEEE 802.11n-2009 and IEEE 802.11ac-2013 in the next wireless local area network amendment. 7.3.1.4  Long Term Due to the rapid advancement in science and technology has in turn led to advancements in communication systems such as Wi-Fi, modems, and broadband connection. Li-Fi is an advancement to the Wi-Fi technology, where light as a medium is used for the transmission of data. Li-Fi stands for light fidelity. The concept of Li-Fi is about removing the fiber from the fiber optics and sending information through LED which differs in intensity (Sharma et al. 2016).

7.3.2  Health Detection Systems 7.3.2.1  Current Features Some of the important public health issues are sedentary behavior and physical inactivity. Wearable devices have the ability to overcome some shortcomings in in-­ person traditional programs for physical activity and weight. Wearable devices that have the ability to monitor physical activity are cheaper than gym subscriptions. Advancements in low-cost wearable device that provide assistance for physical activity have become rapid. 7.3.2.2  Gap One of the best solutions for a health wearable could be integrating as many functions as possible into one form factored device, and the best location for the wearable sensor to be placed is the wrist. Technical challenges still do exist because the wrist might not be the best place for the establishment of sensors because of motion artifacts and size limitations (Kim et al. 2014).

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67

7.3.2.3  Short Term Biswas and Misra (2015) discuss a cheap prototype of a health monitoring device that can evaluate health parameters and transmit data to healthcare caregivers using internet for the purpose of remote health monitoring. An RFID enabled wireless mobile multimedia information system depicts the methodology for the development of wireless mobile multimedia systems for the improvement of quality and efficiency of healthcare. 7.3.2.4  Long Term The IS-Active system is a person centric health solution especially designed for elderly patients with chronic conditions and is based on wireless inertial sensing systems. Using the patients suffering from chronic obstructive pulmonary disease (COPD), the results need to be validated for the same (Inertia Technology 2018).

7.3.3  Pharmaceutical Therapy Imitation 7.3.3.1  Current Feature The current trend in personal health management and treatment of medical problems is health monitoring using wearable sensors. Wearable sensors can be best described as on-body biosensor devices that measure physiological signals such as heart rate, blood pressure, and body temperature (Soh et al. 2015). 7.3.3.2  Gap The challenge in the design of Wireless Body Sensor Network (WBSN) lies with the management of residual energy of sensors and efficient transfer of data. Generally, the battery of biosensor nodes is difficult to recharge or replace in healthcare applications. Therefore, residual energy of sensors is a critical issue and has to be considered in WBSN (ElAzhari et al. 2017). 7.3.3.3  Short Term For various chemical and biological applications, various microfluidics devices have been developed. The electrowetting on dielectric (EWOD) is a technique dependent on the interfacial properties of the liquid using an electric field. In addition to the advantage of lower power consumption, it has the advantage of scalability. These characteristics make them very suitable for adding additional sensing

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modules. These systems can therefore be used for different biosensing applications as they allow multiple processing of several samples on the same chip (Luka et al. 2015). 7.3.3.4  Long Term Giant magnetoresistance (GMR) biosensors have been developed for the influenza A virus detection. Research has been ongoing to use the monoclonal antibodies to viral nucleoprotein in combination with magnetic nanoparticles (MNPs). The binding of MNPs to the GMR sensor is due to the availability of influenza virus and this binding is directly proportional to the concentration of the virus. When the MNPs get bound to the GMR sensor, a change in the sensor resistance is seen which is measured via the electrical readout (Krishna et al. 2016).

7.3.4  Personalization 7.3.4.1  Current Feature Functions such as transmission and instantaneous single parameter measurement are currently offered by the market. There is a limited number of wearable systems which are able to provide continuous ambulant monitoring. Currently the market is devoid of smart wearable systems that integrate multiple sensors to support medical decision and for easy interaction with health providers (Lymberis 2003). Research on health monitoring for wearable health smart systems has fastened through the help of public and private financial support. 7.3.4.2  Gap Active interaction with the customers seems to be an issue. Technology could be used to have a better customer interaction such as tracking all customer desires, improving security features without diminishing the customer experience and by using internal staff to address customer expectations (Brown 2018). 7.3.4.3  Short Term Intelligent biomedical clothing could be one of the ways to provide support for the self-management of diseases around and also health at any point of time. Multidisciplinary research is required to develop intelligent biomedical clothing through research in textile fibers, sensors which could be used in biomedical applications, and telecommunication through mobile (Lymberis and Olsson 2003).

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7.3.4.4  Long Term There is limited space for interaction of small screen smart watches with the users due to compact form factors. This feature can be expanded for smart watches through the use of WatchThru. An additional screen could be an add-on to the main touchscreen with a graphical display that helps the main touchscreen, and which could be floated mid-air. Different information could be displayed on two screens depending on the user’s viewing direction (Wenig et al. 2017).

7.3.5  Sensor Technology 7.3.5.1  Current Feature An ultrasonic sensor has been developed which has the ability to monitor skeletal contraction. A PVDF piezoelectric polymer film is used to construct the ultrasonic sensor and does not have a multilayer or backing material. This ultrasonic sensor would have the properties such as non-invasive and can perform functions such as monitoring of muscle without constricting the muscle movement. This is not possible using a normal ultrasonic probe which is handheld (AlMohimeed et al. 2013). 7.3.5.2  Gap Sensor technology is gaining popularity and becoming omnipresent because of which there is a wealth of sensor data. In most of the applications, the data measured through the sensors is prone to errors. The presence of noise in data coming from sensors has inspired a lot of research in the domain of sensor networks and machine learning (Wen et al. 2015). 7.3.5.3  Short Term A metal watch strap which is a wearable antenna is a potential adaptation in a short run. A 2.4 GHz circular antenna has already been examined on a smart metal watch. Within the surrounding of an unbroken metal rim, a 7-band WWAN/LTE utilizing direct fed dual loop antenna has been developed. This methodology has displayed good performance while going through different shapes and paths (Li et al. 2017). 7.3.5.4  Long Term Metal antenna performance is one of the limiting factors for performance of biosensors and wireless body area network (WBAN). Wireless sensors in microwave and RF are limited to 1–2 cm due to high dielectric property and conductivity. The liquid

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7  Value Roadmap Development for Healthcare Industry

Fig. 7.3  Roadmapping of technology features—healthcare

antenna concept which is based out of the concept of aqueous solution conductivity gives an improvement by a factor of 5–10 and this methodology could be extended for the creation of RF electronics in liquid form for real-time monitoring of wearables (Traille et al. 2008).

7.3.6  Roadmapping of Technology Features After evaluation of the technology features, the features are distributed according to the timeline considering their relative importance. The technology features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the technology features are ranked, they are placed on the roadmap according to short term and long term, for example, under the category of personalization, “intelligent biomedical clothing” is a short-term feature, whereas “Watchthru” is a long-term feature. Figure  7.3 shows the technology features in healthcare sector.

7.3.7  Mapping of Technology Features and Product Features The mapping of product features and technology features which in other words is the link between product features and technology features is performed using a quality function deployment. The product features are listed on the x-axis (horizontally) and technology features are listed on the y-axis (vertically). Next, the product features which are weighted by the experts are given a correlation with the technology features on the y-axis. The correlation is ranked from 0 to 3, where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation, and 3 denotes complete correlation. Henceforth, the summation of the product of product features and technology features is performed and illustrated in the “total” column and finally a “rank” is given based on the total score. Table 7.5 depicts QFD matrix for technology features vs. product features.

Technology features Data transmission Health detection systems Pharmaceutical therapy imitation Personalization Sensor technology

Product features Weight Levels 2 3 0 2 3

0 2

Reduce health accidents 8 P2

3 3 2

Export of data 6 P1

1 0

1 1 3

Pharmaceutical therapy 8 P3

Table 7.5  QFD matrix for technology features versus product features—healthcare

2 2

2 3 1

User experience 9 P4

1 2

2 1 2

Load reduction on hospitals 6 P5

48 66

Total 72 83 57

5 3

Rank 2 1 4

7.3  Technology Features in Healthcare 71

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7  Value Roadmap Development for Healthcare Industry

Fig. 7.4  Roadmapping of enablers—healthcare

7.3.8  Roadmapping of Enablers After evaluation of the enablers as mentioned in Sect. 7.3, the enablers are distributed according to the timeline considering their relative importance. The enablers’ features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the enablers are ranked, they are placed on the roadmap accordingly, e.g., “Big data” could be seen as a long-term prospect for achieving the required technology features because of the abundance of human body factors. Figure 7.4 shows the timeline of industry 4.0 enablers’ roadmap.

7.3.9  Mapping of Technology Features and Enablers The mapping of technology features and enablers which is the link between technology features and enablers is performed using a quality function deployment. The technology features are listed on the x-axis and enablers are listed on the y-axis. Next, the technology features which are weighted by the experts are given a correlation with the enablers on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation, and 3 denotes complete correlation. Henceforth, the summation of the product of technology features and enablers is performed and illustrated in the “total” column and finally a “rank” is given based on the total score. Table 7.6 shows QFD matrix for enablers vs. technology features.

Big data Predictive maintenance Cloud computing Digital twin Autonomous robots Augmented reality Smart sensors 3D printing

Enablers

Technology features Weight Levels

Health detection systems 9 T2 2 3 2 2 0 2 3 0

Data transmission 8 T1 3 3

3 0 0 2 3 0

Table 7.6  QFD matrix for enablers versus technology features—healthcare

2 2 0 0 1 1

Pharmaceutical therapy imitation 6 T3 0 1 2 3 0 3 3 3

Personalization 8 T4 2 2 1 1 0 2 3 2

Sensor technology 9 T5 1 3

79 63 0 76 108 48

Total 67 100

4 1

3

Rank 5 2

7.3  Technology Features in Healthcare 73

Chapter 8

Value Roadmap Development for Telecommunication Industry

8.1  Market and Business Driver 8.1.1  Socio-economic Development There are certain facets that influence the time and to what extent the diffusion of new technology penetrate into the market. Couple of those factors include: income, price charged for the service structure, technological changes, customer experience and their preferences (Telecom Domain 2012). Economy is one of the main drivers which affect many industries. Telecommunication is also one of those industries that is highly affected by the economic cycle. Also, telecommunication industry is very sensitive to those economic cycles which is the resultant of increase in cross border presence and large-­ scale operations (Telecom Domain 2012).

8.1.2  Mobile Network Size Mobile network size is identified as having great impacts on network mobile subscription. A study which was performed by, illustrated that mobile network size together with price and GDP are the main drivers in this industry (Telecom Domain 2012).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_8

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8.1.3  GDP The acceptance of any product or service offered by an industry also depends on the gross domestic product (GDP) of the country. Likewise, the services such as high-­ speed data connectivity and other services are also directly impacted by the GDP of the country. A better economic health allows a higher spending capacity by customers and in terms of telecommunication services it could be more number of services offered (Telecom Domain 2012).

8.1.4  Quality of Main Lines Quality of network is one of the key elements for the end customers (Zhen 2015). The quality of main line does not only mean the seamless transfer of data from one place to another but it also encompasses speed, capacity, coverage and which could be categorized under the broad term ‘Quality of Experiences (QoE)’.

8.1.5  Size of Fixed Network The size of fixed network can be best explained using the concept of packet data. Data packets are units of data which are bundled into a single package and then are made to travel along a network path. The cellular digital packet data (CDPD) is assigned to a spectrum of telephone cellular network on which the packet data transfer takes place. This concept of packet switching overlay to an existing cellular voice network was introduced by IBM (Salkintzis 1999). The CDPD currently has been replaced by GPRS which a faster standard is.

8.1.6  C  hange of Role Telecommunication Infrastructure: From Voice to Data The telecommunications market has seen a continued decline in traditional fixed line telephone. Mobile communication has displayed a growth which is also due to the increased popularity of cellular phones (Hess 2006). Increase of broadband access has enabled the data consumers to reach out to voice over internet protocol (VoIP) and has led to radical changes in the telecommunication market. Overall, the traditional feature of using voice services on mobile devices has changed to data driven services.

8.1  Market and Business Driver

77

8.1.7  Customer Relationship With the competitive intensity in telecommunication market, organizations get challenged due to changing customer patterns and advancements in information technology. With the onset of relationship marketing, the success of companies is not only reliant on the traditional acquisition of customers but retention and loyalty are significant as well (Katona and Baier 2005). E-CRM or the electronic customer relationship management has been an area of application in the information and communication technology to boost the scope of customer service (Blery and Michalakopoulos 2006).

8.1.8  Content Innovation and Commercialization Selection of commercialization strategy is necessary for the diffusion of an innovation which ultimately leads to greater market share and profit for the organizations. The dictionary definition of commercialization implies applying business methods for profit attainment for a new technology, product or service. The ICT industry is a high-tech induced industry with a lot of uncertainty and rapid changes which sometimes also leads to failure for companies. Therefore, the methods to bring in commercialization success for product or services in the telecom industry becomes crucial (Aslani et al. 2015).

8.1.9  Infrastructure Management The telecommunication operators have been investing a lot into the expansion of their networks. This has led to increase in the number of plant site, maintenance costs associated with it as well as has called for the protection of these critical infrastructures (De Blas et al. 2006; Wang et al. 2012). Hence, the need for infrastructure management comes into play because the operators are required to manage and monitor all the equipment and infrastructure. One of the classic cases is by Emerson, wherein it has developed a solution for the management of existing telecommunications operator infrastructures called ENEC (Emerson Network Energy Centre).

8.1.10  Customer Retention As mentioned by (Jyh-Fu Jeng and Bailey 2012), “While customer satisfaction is an important part of the relationship between a provider and customer, the real value of customer satisfaction is shown in retention”. Due to the evolution in communication

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technologies, the demand for simple and effective communication has increased and due to economies of scale, the prices associated with these telecommunication technologies have dropped dramatically. In this highly competitive arena, the companies that can attract and retain customers are stated to make considerable gains.

8.1.11  Bundling Bundling is a strategy by which companies which were offering separate services or products on different prices give discounts on products to the customers who buy the products as a single combined package. Due to the convergence of media and telecommunication, new market spaces have been created (Bughin and Mendonça, 2007). Especially over the last decade, a growing trend of bundled offers in the telecommunications industry named “triple-play” bundle has emerged which includes telephone, fixed internet and pay-television services (Díaz-Pinés and Vareda 2016). Hence, it can be stated that bundling has become the rule with the advent of quadruple bundling in place as well. Table 8.1 illustrates the identified market drivers along with the rated weightage based on expert opinions from scale 1 to 10 with 1 having the least and 10 with the highest weightage for the telecommunication industry. The average weight is taken for the final illustration.

8.1.12  Roadmapping of Market Drivers After evaluation of the market drivers, the drivers are distributed according to the timeline considering their relative importance. The drivers are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the drivers are ranked, they are placed on the roadmap according to short term and long term, for example, “infrastructure management” as a market driver in telecommunication is a long-term feature since “infrastructure management” would be one of the major factors when it comes down to product acceptance. Figure 8.1 shows the roadmap of market drivers for telecommunication industry.

8.2  Product Feature in Telecommunication The product features in the section deals with the features required in telecommunication which would be necessary to satisfy the market drivers. The product features enlisted in the table below are further segregated into short term (~3 years) features and long term (~7 years) features. The gaps mentioned later on depict the shortcomings in the current product features and which could be addressed by short term and

79

8.2  Product Feature in Telecommunication Table 8.1  Market drivers evaluation—telecommunication Drivers Socio-economic development Mobile network size GDP

Quality of main lines

Size of fixed network

Change of role telecommunication infrastructure—from voice to data Customer relationship

Content innovation and commercialization Infrastructure management

Customer retention Bundling

Diffusion of new technology is dependent on the economic cycles Mobile network size has a great impact on mobile network subscription The acceptance of any product or service offered by an industry also depends on the gross domestic product (GDP) of the country The quality of main line does not only mean the seamless transfer of data from one place to another but it also encompasses speed, capacity, coverage (in other words, quality of experience) Data packets are units of data which are bundled into a single package and then are made to travel along a network path. The size of fixed network can be explained by concept of packet data. Increase of broadband access has enabled the data consumers to reach out to voice over internet protocol (VoIP) and has led to radical changes in the telecommunication market With the onset of relationship marketing, the success of companies is not only reliant on the traditional acquisition of customers but retention and loyalty Commercialization implies applying business methods for profit attainment for a new technology, product or service Infrastructure management is required because the operators are needed to manage and monitor all the equipment and infrastructure The real value of customer satisfaction is represented in the customer retention Is a strategy by which companies which were offering separate services/products on different prices give discounts on products to the customers who buy the products as a single combined package

Fig. 8.1  Roadmapping of market drivers—telecommunication

Average weight 6 7 4

7

8

9

8

7

7

8 6

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8  Value Roadmap Development for Telecommunication Industry

long-term goals. Table 8.2 depicts the technology features summary based on short and long term and current status.

8.2.1  Low Cost to Use 8.2.1.1  Current Feature Global System for Mobile Communications (GSMA) is an association which represents and supports the mobile operators that are using GSM.  Recently GSMA started supporting four new mobile bands that are at WRC-15. The reason of their selection is their ability to be widely harmonized globally and the already existing services is supported in the alternative band spectrum. These bands are referred to as a mixed of cover ages that is frequency and capacity in terms of larger bandwidth in order to ensure that the network is capable of providing a cost-effective service and solution in different areas (GSMA 2015). 8.2.1.2  Gap The main goal of second and third generation of wireless network system was to design systems for voice, connection based and delayed sensitive service for a specified bit rate requirement. However, data services are normally without any connection and are insensitive with respect to delay as well as not having any specific bit-rate requirement. These differences imply that the omni present status of wireless networks is not really a necessity and only complicates the design (Yates and Mandayam 2000).

Table 8.2  Product feature—telecommunication Product features Low cost to use

Current level GSMA

Short-term ~3 years Multi-ant colony optimization LTE-Advanced

Long-term ~7 years Cognitive radio sense

Wi-Fi speed Security

High quality speed & accessibility Network access control Network planning

Professional mobile radio network Genetic algorithms

Round robin technique Object level approach

– Stackable switches

Admission control

HetNet

Tower monitoring system Artificial fish swarm algorithm – Wavelength division multiplexing Self-organizing HetNet

Network coverage Load balancing Network redundancy Radio resource management

Six-port modulators

8.2  Product Feature in Telecommunication

81

8.2.1.3  Short Term With the advent of concepts such as Internet of Things (IoT), the landscape of communication has changed enormously. The connectivity of devices faces challenges such as scalability, reliability and energy consumption and which need to be thoroughly analyzed. One of the ways to establish a model for multi-resource scheduling is based on multi anti colony optimization algorithm (Alam et al. 2018). 8.2.1.4  Long Term The cognitive radio concept is a low-cost solution which allows for reducing spectrum scarcity by the usage of secondary users to make full utilization of the licensed spectrum which is unoccupied (Alam et al. 2018).

8.2.2  Wi-Fi Speed 8.2.2.1  Current Feature Nowadays, it is very important for the consumers of mobile network to have a smooth connection with proper quality where no obstruction or delay is sensed. High quality mobile internet service refers to a provider which is capable of granting an acceptable speed for the end user on some various devices as well as ability of staying connected throughout the desired time (Kim and Steinfield 2004). 8.2.2.2  Short Term By the introduction of fourth generation network (4G), it caused companies to compete with one another in order to satisfy the requirements. LTE-A (Long Term Evolution-Advance) is the upgraded system on the LTE with the goal of boosting capacity and coverage. One provided solution is the multi-hop system relay in the scope of LTE-A with the aim to optimize the capacity especially the cell edge region. Technologies identified in the multi hop system can be divided into two types of relay node: moving relay node (MRN) and fixed relay node (FRN). MRN as the name suggests can be mounted on the moving vehicles with the objective to optimize the data capacity both indoor and outdoor transmission as well as throughput for high speed vehicle. On the other side, FRN technique is implemented for base station in order to grant coverage enhancement at endpoint of cell edge. Performed simulations and calculation illustrated that the spectral efficiency is enhance if multi hop relay is deployed over the single hop. Also, the maximum gain can be achieved by locating the relay at 70% from cell radius (Fayadh 2017).

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8.2.2.3  Long Term The six port modulator for wireless communication performs digital modulation with the usage of electromagnetic wave interferometry in the six-port modulator The six-port architecture in essence is capable of providing higher data rate frequencies when compared to conventional radio technologies (Gong and Karlsson 2016).

8.2.3  Security 8.2.3.1  Current Feature Conventional security solutions target the following use cases: intrusion detection, prevention, anti-virus measures as well as firewall. These traditional security products are not sufficient in today’s world due to advancement in cyber technology which has made a wider range for the network traffic. Recent cyber security survey indicates that insider attack are very detrimental while leading to severe consequences such as intellectual property infringement, disclosure of confidential information, invasion of privacy law as well as monetary damage (Lakbabi et al. 2012). Network Access Control (NAC) is a process for provisioning the network access for users and end devices dynamically. NAC provides authentication, endpoint compliance as well as enforced policy which is done through validation of user identity (credentials) while trying to get access to a network (Lakbabi et al. 2012). 8.2.3.2  Gap The interconnection interface due to this convergence of different technologies exposes the entire network to intruders and increases the potential for attacks caused by virus, worms such as Code-Red, Sasser and malicious software (Agubor et al. 2015). Several technologies are converged to shape telecommunication network from the global perspective. These technologies include: PSTN, 2G, 3G as well as 4G (latest) through important network components. The number of intrusion and cyber-­ attacks have increased due to different interconnection interface where via these technologies are exposed to the whole network. Attacks such as Code-Red, Sasser can be done either through internal sources or external. Hence, the whole telecommunication network is susceptible and vulnerable and each part of it can be compromised (Agubor et al. 2015). 8.2.3.3  Short Term Reliable and secure Professional Mobile Radio or (PMR) network is essential in current communication system in the domain of public safety and security. PMRs are utilized to provide voice services (Carlà et al. 2016).

8.2  Product Feature in Telecommunication

83

There is a huge demand by both governments and organizations for the public safety and security (PSS) globally to ensure the continuous development in the wireless systems based on PMR technologies (Carlà et al. 2016). Despite having efforts to optimize PMR systems to increase its communication capacity, the final achievements could not compete with the recent 3GPP Long Term Evolution (LTE) technologies. Therefore, it has been a justifiable proposal to use the commercial LTE frameworks in order to respond to PSS requirements. Thus, to ensure the success of LTE adaptation, the LTE features shall be introduced in the future release of 3GPP standards as well as ensuring the interoperability with the current narrowband PMR systems (Carlà et al. 2016). 8.2.3.4  Long Term By the advancement of technology and emergence of Machine to Machine (M2M) communication, many devices got connected to one another and can be accessible by various users at the same time. Due to hyper-connected devices, hence the security of data and access and control of data is becoming very crucial (Dalela et al. 2016). Tower Monitoring System (TMS) has a couple of devices that are operating based on non-oneM2M and in order to keep the legacy of the network these devices should be incorporated. Such devices are operating based on hybrid/proprietary protocol for its communication with server. One requirement for these operations to happen is Internetworking Proxy (IWP) to enable the communication with AND/ ASN via Mca reference node. In addition, there are couple of more protocols are used to ensure the safety of system on attack in the view of TMS oneM2M network (Dalela et al. 2016). These are the sub protocols: Encapsulated Security Payload (ESP) Authentication Header Protocol (AHP) IP Payload Compression Protocol (IPComp)

8.2.4  Network Coverage 8.2.4.1  Current Feature Telecommunication network constantly need to adapt to the fast pace of challenges which are imposed on them because of request for having continuous development in their service offerings. In order to address this demand, there are certain problems risen from network coverage or guaranteed quality of service (Alarcón et al. 2008). Planning of network is an iterative process which requires designing in topology and synthesis of network and its realization with the overall objective of meeting the needs of the requirement in the new established network for the both subscriber and

84

8  Value Roadmap Development for Telecommunication Industry

operator. This is a very important requirement which shall be considered prior to the new establishment of telecommunication network. Many factors and parameters shall be analyzed in the network planning process (Alarcón et al. 2008). 8.2.4.2  Gap One of the issues found in sensor network is the problem with its coverage, which corresponds to how the network is being monitored or tracked by its sensors. When quality of service is concerned, there will be two major issues that are: coverage and connectivity in the WSNs (Gupta et al. 2016). When the sensor network is targeted then the coverage is considered as the quality of service measure. The two-main metrics of coverage and the energy consumption are the two main element of evaluating quality of network (Gupta et al. 2016). 8.2.4.3  Short Term There are different methods that could be implemented if the coverage of wireless networks has to be optimized. As of now the work has particularly concentrated on reducing the number of base stations and determining ideal locations. If the base station locations are fixed and the wireless network design can be assumed as a constrained optimized problem. Some of the methods which could be used are genetic algorithms, greedy algorithms and simulated annealing (Fagen et al. 2006). 8.2.4.4  Long Term A very powerful wireless sensor network coverage optimization algorithm has been developed based on PSO genetic algorithm which increases the range of search, the coverage of particles more efficient and strengthens the algorithm optimization. Also, other techniques such as ant colony optimization or chaotic particle swarm algorithm improve the coverage of wireless networks. Artificial fish swarm ­algorithm (AFSA) is new intelligent bionic algorithm and is a modern random search algorithm and is not sensitive to initial value and parameter selection (DaWei and Changliang 2015).

8.2.5  Load Balancing 8.2.5.1  Current Features Load balancing is the method by which the distribution of traffic across networks. One of the aims of load balancing is to provide network redundancy as this method provides a secondary way to access network resources in case there is a WAN link

8.2  Product Feature in Telecommunication

85

outage. Round robin technique is one of the load balancing techniques. Due to the algorithm utilized, the load is distributed equally to all the servers (Mishra and Mishra 2015). 8.2.5.2  Gap Rapid increase in the mobile data traffic has led to a major challenge for the telecom operators. The volume of data has been growing at a rate greater than the ability of the operator. The gap between data demand and network capacity requires innovations. It is expected that the installation of heterogeneous networks fulfills the demands. However, In the case of heterogeneous wireless networks, the problem exists with the elastic data traffic (Liang and Wei 2015).

8.2.6  Network Redundancy 8.2.6.1  Current Features Internet is a platform for transferring a huge amount of information and targeted content continuously. When dealing with repeated data, the efficiency and control over the redundancy becomes important. One technique used for the same goal is ‘protocol independent redundancy elimination’ that eliminates the duplicate strings of data from arbitrary network flows (Anand et al. 2009). Object level approach is an access catching mechanism. An approach in this concept is to divide the files into content-based pieces and to download those pieces that are not already present locally (Anand et al. 2009). The first protocol for eliminating the redundancy was first developed by Spring et al. the study performed by the Spring et al. showed that 20% of bytes of data are redundant in inbound direction and this amount rises to 50% in the outbound ­direction. In addition, the study performed illustrated that protocol independent technique is more efficient compared to object level caching (Anand et al. 2009). 8.2.6.2  Short Term One solution to make sure that the network is redundant and fast is to use stackable switches which is beneficial in terms of STP protocol elimination. In the case of stackable switches as the L3 devices of first hop redundancy protocol (FHRP) could also get ignored while keeping the suitable level of reliability. Despite having some advantages that use of L3 can bring with itself such as cost effectiveness and simpler, they are not an ultimate solution. One of the reason is that a different security level is required such as filtering traffic based on different ports (UDP/TCP), antivirus and so forth (Papić 2016).

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8.2.6.3  Long Term One of the most promising technology with the aim of increasing the capacity of the core networks is the recently emerged Wavelength Division Multiplexing (WDM). Currently, electronic switches are more in persistence than optical fibers and where WDM utilizes method of point to point architecture. On the other hand, it is predicted that in the coming years the WDM core network is going to be adapted into complete optical architecture (Øverby 2004). In Optical Packet switched (OPS) networks the issue which rises is the loss of packets at network layer that is due to contention when some packets have to get transferred via a same output wavelength. In order to fight against the packet losses, a novel approach which is called Network Layer Packet Redundancy Scheme (NLPRS) has been developed with the intention of reducing the end to end packet losses (Øverby 2004).

8.2.7  Radio Resource Management 8.2.7.1  Current Feature With today’s current 2G and 2.5G systems can have the coverage to communication networks up to 90–95%. Also, 3G stations are developed over their previous version of base stations. A novel approach for increasing the capacity is the utilization of time slot. The admission control is the first radio resource management that a user to the network encounters and which decides if the services of the new user can be accommodated in the present traffic situation (Hasu 2007). 8.2.7.2  Gap Future radio resource management (RRM) is having distinct requirement which is used for non-heterogeneous and non-shared network. These features also have radio resource sharing which is the issues that in the future these systems are going to face as the next generation of network system—4G—comes into play. These features have an immense impact on the overall system design as well as radio resource management (Salman and Ashraf 2006). There has been a couple of proposals as to share the network resources. These proposals include the sharing of base station equipment and to roam in other operators that the coverage is not yet supplied. The main goal is to reduce the cost of having higher coverage which improves the speed of transferring from 2G to 3G as well as 4G.  When roaming-based sharing is concerned, the operators can have mutual access to the other operator’s radio access network (RAN) in an indirect manner through a core network. Hence, this denotes that multiple operators share

8.2  Product Feature in Telecommunication

87

and utilize the same RAN and there is a dire need of having radio resource control between the multiple operators (Salman and Ashraf 2006). 8.2.7.3  Short Term Heterogeneous Network also known as HetNet which is a modern deployment from low power nodes within macrocells that forms a paradigm shift in the communication network. HetNet network has become one of the most promising development in better realization of Long Term Evolution (LTE) and LTE-Advanced network and radio resource management (RRM) (Lee et al. 2014, 2015). The low power nodes inside the macrocells shapes a novel communication network. These low power nodes are typically known as small cells (microcells, picocells, femtocells and relay nodes) (Lee et al. 2014, 2015). 8.2.7.4  Long Term It is predicted that the new and novel network cellular are self-organized HetNet that are autonomous and without manual intervention. Self-optimization is one of the concepts discussed in the RRM for different purposes such as radio resource allocation, load balancing. The prerequisite for that includes that all the base stations shall be communicating with its surrounding and the system conditions. This imposes a great deal of challenge for network operators to provide a low complex design of network. There are certain advantages that are associated with such networks, for instance: significant reduction in energy consumption, an effective resource allocation, cost saving and error-free communication. The study which was performed on the proposed idea of RRM scheme suffers from a major setback that is the increased complexity. Hence, technical challenges still remain unresolved which requires further research (Lee et al. 2014, 2015).

8.2.8  Roadmapping of Product Features After evaluation of the product features, the features are distributed according to the timeline considering their relative importance. The product features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the product features are ranked, they are placed on the roadmap according to short term and long term, for instance “Multi ant and colony optimization” could be considered as a short-team produce feature of resource management type in telecommunication whereas “cognitive radio sense” could be determined as a long-term product feature. Figure 8.2 shows the product feature with respect to short and long term.

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8  Value Roadmap Development for Telecommunication Industry

Fig. 8.2  Roadmapping of product features—telecommunication

8.2.9  Mapping of Product Features and Market Drivers The mapping of product features and market drivers, which is the link between product features and market drivers is performed using a quality function deployment. The market drivers are listed on the x-axis and product features are listed on the y-axis. Next, the market drivers which are weighted by the experts are given a correlation with the product features on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation and 3 denotes complete correlation. Henceforth, the summation of the product of market drivers and product features is performed and illustrated in the ‘total’ column and finally a ‘rank’ is given based on the total score. Table 8.3 the QFD matrix for market drivers vs. product features and are rated per experts’ opinions.

8.3  Technology Feature in Telecommunication The technology features in the section deals with the features required in telecommunication which would be necessary to satisfy the market drivers. The technology features enlisted in the table below are further segregated into short term (~3 years) features and long term (~7 years) features. The gaps mentioned later on depict the shortcomings in the current technology features and which could be addressed by short term and long-term goals. Table 8.4 depicts the technology features summary based on short and long term and current status.

8.3.1  Low Cost Equipment 8.3.1.1  Current Feature Wireless network is recognized with an enablement of computers or devices to communicate with one another without any physical cabling involved. Large amount of cost effective solutions have been proposed through industry standard (IEEE

7

D2 1

1

0 3

1

2

1

D1 2

0

0 0

2

0

1

Levels

Wi-Fi speed

Security

Network redundancy

Load balancing

Radio resource management

Network coverage

Low cost to use

Product features

Weight 6

Market driver

0

0

2

0 1

0

D3 3

4

Socio-­ economic Mobile develop network ment size GDP

2

3

2

0 1

2

D4 0

7

1

1

0

0 2

2

D5 0

8

Quality Size of of main fixed lines network

2

1

0

2 2

3

D6 3

9

2

2

1

0 0

1

D7 0

8

2

1

0

1 2

1

D8 1

7

2

1

1

2 2

2

D9 3

7

2

1

2

2 2

0

D10 1

8

1

1

0

1 1

2

D11 0

6

Change of role telecommunication Customer Content Infra infrastructure— relation innovation and structure Customer Bundl from voice to data ship commercialization management retention ing

Table 8.3  QFD matrix for market drivers versus product features—telecommunication

119

96

72

61 116

105

1

4

2

3

Total Rank 94 5

8.3  Technology Feature in Telecommunication 89

8  Value Roadmap Development for Telecommunication Industry

90

Table 8.4  Technology feature—telecommunication Technology features Low cost equipment

Current level Wi-Fi

802.11 IEEE standard 802.11n Wireless equivalent WPA2 privacy Wireless access points 1300 Mbps at 5GHz Network optimization PSO algorithm algorithm Parallel redundancy Network protocol redundancy Packet scheduling Long-term evolution

Short-term ~3 years Five wireless access points Li-fi Hash algorithm Wi-Fi router with 2.4 & 5 Ghz Multiple spanning tree algorithm IP layer parallel redundancy protocol Conservative and adaptive QoS

Long-term ~7 years Aerostats – Extensible authentication protocol – Ant based load balancing algorithm Redundancy controller Cognitive radio resource management

802.11). Wi-Fi system has provided a great amount of flexibility for warehouses and sophisticated applications where wired connectivity is difficult (Sathiya and Dhanalakshmi 2015). 8.3.1.2  Gap It is quite evident that ICT has brought a significant development in the connectivity in rural areas especially in emerging economies. Therefore, there is a necessity to connect rural areas with proper infrastructure (Bilaye et al. 2009). 8.3.1.3  Short Term The paper provided by Deep and Kush describes the five Wireless Access Point known as WAP with omni antennas. Establishing such rural network needs five WAP that comes with two directional (X, Y) omni antennas. In the computer center one of the wireless access point with two antennas (omni and directional) has been installed. Both directional antennas communicate with one another which sometimes the communication is supported often with omni antennas where the line of sight between these antennas should be apparent (Deep and Kush 2010). 8.3.1.4  Long Term Wireless connectivity and network installation in rural areas suffer from two main constraints of high cost of set-up and lack of enough infrastructure platform. These hindrances can act also as an opportunity for the benefit of rural community especially in the situation of communication disruption (Bilaye et al. 2009).

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The solution proposed is to use the aerostats and deploying them while having no disturbance from the line of sight (LOS) for the communication. The cost of deployment is quite more of a one-time investment and very limited and the only slight cost is the gas needed to refill the leakage air over the time. Aerostats can remain almost stable over time due to aerodynamic design which can survive bad weather conditions which then can be a stable LOS connectivity. The relaxation for the antenna direction is achieved by the omni directional antenna which is located beneath the aerostats (Bilaye et al. 2009).

8.3.2  802.11 IEEE Standard 8.3.2.1  Current Feature Operating frequency of main Wi-Fi standards which encompasses A, B, G, N and AC are 2.4 GHz or 5 GHz. Less sensitivity is achieved through this high data rate. To showcase this example, if a thermostat in a house is connected through Wi-Fi and the Wi-Fi router is located quite far then the thermostat cannot easily get Wi-Fi signal using the traditional 802.11n standard. For, IoT purposes where there is not much of requirement for high data rate 802.11ah was introduced. HaLow operates at 900 MHz Wi-Fi which is used for long range data transmission (Ray 2018). 8.3.2.2  Short Term Light Fidelity or simply Li-Fi is a new trend in terms of signal transmission. Li-Fi can be seen as a light-based Wi-Fi or in other words instead of using the radio waves for transmission it utilizes the light. Li-Fi modems use transceivers with mounted LED which can be used for lightning purpose for both transmission and receiving the data. It uses the electromagnetic spectrum which was not used before. Li-Fi tries to overcome the constraint of Wi-Fi as it uses 2.4–5 GHz radio frequency for delivering the wireless access also the bandwidth of Wi-Fi is quite limited up to 50–100 Mbps. On the other hand, Li-Fi delivers higher bandwidth, improved efficiency, accessibility as well as security which is quite comparable to Wi-Fi (Sarkar et al. 2015).

8.3.3  Wireless Equivalent Privacy 8.3.3.1  Current Feature WAP (Wireless Protected Access) is a Wi-Fi security protocol. WPA2 has not yet addressed the security vulnerability authentication in it architecture. The WPA was a response to the constraints that Wired Equivalent Privacy (WEP) suffered. With

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the introduction of WPA the issues of cryptography in WEP was resolved. However, the first version of WPA also had certain flaws to provide a secure wireless communication. Thus, an amendment on the IEEE 802.11 was made which is then known as WPA2 or, IEEE 802.11i. This standard aims to compensate the vulnerabilities of first version WPA (Sakib et al. 2011). 8.3.3.2  Gap Both WPA and WPA2 are vulnerable to PSK attack. PSK is the alternative to 802.1 × PMK that they use the authentication server. PSK is a string format of 256 bits or passphrase of 8–63 characters (Sakib et al. 2011). 8.3.3.3  Short Term Hash algorithm is used for the means of securing the authentication. This process comprises of four distinct steps. In the first step, the client sends a request for communication which sends a string as a challenge to the authenticator. The second step involves in a fact that an authenticator also sends a string to challenge the client too. Third step is when the client server tries to digest the message received through a hash algorithm that sends the string value and the ISSI number to the authenticator. In the last step, the authenticator also calculates the message for its correlating string which then sends it to the client. It is important to know that only the client and the authorized authenticator know the hash algorithm. If both values of string match one another, the client and authenticator will communicate with one another. 8.3.3.4  Long Term Extensible authentication protocol also known as EAP is an authentication protocol which has been defined in RFC 3748 with the aim of providing the framework to handle multiple authentication methods. It is also important to mention that the EAP itself is not a protocol but only a framework that is related to the format of messages. When EAP is enabled in any network the port that is used (port 1812) state relies on the authorization from the server which has been successful. Once the authorization is granted the authenticator opens the port and allows the communication to happen. In case that authentication is rejected by the server, then the message cannot freely flow and there will be no communication happen (Kothaluru and Mecca 2012).

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8.3.4  Wireless Access Points 8.3.4.1  Current Feature Conceptually, the wireless network which operates at 2.4 GHz is able to support 450 or 600  Mbps which also depends on the router class. This transmission speed increases when the wireless operating network operates at 5 GHz that support the higher transmission speed up to 1300 Mbps. The 5 GHz band has lower coverage than the 2.4 GHz. The reason for that is as the frequency increases the penetration to solid material and objects would be difficult. Yet, the higher the frequency, the faster delivery of data transmission is achieved (Albert 2018). 8.3.4.2  Short Term Range of wireless signal also differs from each device to device. There are quite a few factors that affect the range of the access points. For instance, it depends on 802.11 protocol standard, also it depends on the strength of the transmitter device as well as the potential obstruction that might have been encountered by the physical surrounding. Generally speaking, the home connected Wi-Fi routers with the traditional 2.4 GHz operating band is able to support the range of 150 feet (46 m) indoor up to 300 feet (92 m) in outdoor surroundings. The traditional 802.11a which were operating on the 5 GHz bands had faced the one third of the distance. Modern introduced routers (802.11n and 802.11  ac) that are able to operate on both 2.4 and 5  GHz also reach similar. 802.11n routers which has the data transmission of 450 Mbps which is used to download movies, songs and streaming in a faster way (Mitchell 2018).

8.3.5  Network Optimization Algorithm 8.3.5.1  Current Feature PSO is an advanced algorithm in the network routing which uses swarm intelligence. The advantage with PSO is that it has fast convergence speed and the implementation is easy. In general, it is a collection of particles which is based on simple flocking rules and force the particles to move around the best solution. 8.3.5.2  Gap One of the problems existing with the current cellular systems is the manual configuration of networks and its management. The current cellular networks are not only costly but are time consuming and error prone due to the exponentially increasing mobile user increase and nodes (Mishra and Mathur 2014).

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8.3.5.3  Short Term One of the methods to optimize telecommunication networks is by the use of multiple spanning tree algorithm. There are two objectives which get fulfilled by this method viz. Minimization of the maximum link load and minimization of network utilization which impose a worst-case load value. The multiple spanning tree algorithm allows for the routing of traffic flow through the network based on spanning trees (Lee et al. 2014, 2015). 8.3.5.4  Long Term The ant-based load balancing algorithm aims at optimal allocation of the resources. Here, the traffic flow can be allocated to every path as far as possible to ensure that there exists a balanced path load for a better network. An ant colony algorithm can be used to engineer the network traffic by the usage of dynamic pheromone design and implementation of a load balancing function (Goswami et al. 2015).

8.3.6  Parallel Redundancy Protocol 8.3.6.1  Current Feature Network redundancy is a process by which alternate network devices, equipment and means of communication are installed within the network infrastructure. The parallel redundancy protocol (PRP) is an IEC standard which is used to increase the reliability. PRP could be used by devices with double network interfaces. The important condition in case of PRP is that the two networks in PRP need to be copies of each other (Rentschler and Heine 2013). 8.3.6.2  Gap PRP technique works well in controlled environments such as a sub stationed LAN where the setup is done through the substation operator and who ensures that the PRP requirements are met. However, at larger scales, routers are required and the concept of PRP can no longer be implemented. Therefore, a new solution for IP wide area network is required (Popovic et al. 2015). 8.3.6.3  Short Term The current solutions for the usage of network redundancy are not compatible with the IP-layer wide area networks and other solutions such as MPLS-TP do not meet the stringent delay requirements hence to resolve this issue, the IP layer parallel redundancy protocol (iPRP) can be used (Popovic et al. 2015).

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8.3.6.4  Long Term The process of providing resiliency could be through software defined networking. To measure the performance of a path, one of the process could be to count packets to analyze the number of packets dropped along the path. To enable this, a new network element called redundancy controller (RC) can be placed between two hosts. The most significant contribution of this method is to monitor and replace paths that perform poorly relative to other paths (Comer et al. 2016).

8.3.7  Packet Scheduling 8.3.7.1  Current Feature Radio resource management (RRM) include a couple of techniques which allocate services to the users that are in line with the Quality of Service (QoS) which at the end ensure a much better radio resource. The significant algorithm used in RRM is called Long Term Evolution (LTE) that are packet scheduling, used for admission, power and interference control. The 3GPP only provides signaling with respect to these procedures and they might be dependent on the vendor and operator. eNodeB is the element of the LTE radio access network and is the responsibility of the admission control that supports the request Evolved Packet System (EPS) (de Sousa 2016). The requests for new EPS bearers in the respective cell is handled. The decision to admit a new user is made depending on several aspects such as the availability of resources, the QoS requirements of the new bearer and the QoS to current bearers (de Sousa 2016). Cell capacity requires an effective and efficient mechanism that at the same time ensures the high spectral efficiency and guarantees the QoS for its users. The solution provided by LTE is in the resource scheduling for both the channels for downlink and uplink in an intelligent and weighted way (de Sousa 2016). 8.3.7.2  Gap One of the issues that the resource management suffers is the high bandwidth. There are certain constraints that the personal data rates are facing such as multipath as well as the link budget (terminal power consumption). There is a linear relationship between necessary transmitter power and the bandwidth which high speed radio access would have a lower range. In addition, it can be concluded that the bandwidth is not so much of importance to the design of RRM.  However, the traffic characteristics are very vital part. Data traffic which also embeds the speech and file transfer can be perceived as discrete streams of symbol. There exists two distinct issue. The first one is the delay constraints which is the data traffic (digital signal) is

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constrained by the delay and the statistical senses however this issue is not present in electronics and analog circuit switching. The second problem is concerned with insufficient information. For instance, systems that come with an intermittent data transmission have certain issues. One of the problems of discontinuous data transmission is that there is no good link quality can be drawn (Zander 1997). 8.3.7.3  Short Term Revision of the bandwidth is a very time-consuming process which would also impact the QoS which has been already established between the wireless communication channels at the base station and the host. A new scheme has been proposed which is known as Conservative and Adaptive QoS (CAQoS). This scheme allows for a scale down facilitation and faster bandwidth reallocation. This scheme reduces the frequent bandwidth reallocation when the new call arrives which at the end results in a much faster call admission with less computation burden and overhead on the networks (Chin et al. 2006). 8.3.7.4  Long Term The wireless systems are prone to interferences from the adjacent cells of 3 GPP. In order to achieve that, the resource block (RB) in each subframe cannot store data for more than one cell. However, to satisfy that the RB centralized is not a feasible scheme. One of the main reason for that is the complexity in the computational process as well as the lack of proper interface for exchanging the RB stored data within the cells. Hence, the Cognitive Radio Resource Management (CRRM) is introduced in such a way that each cell will obtain the RB occupation for the adjacent cells and the wireless networks through Layer-1 measurements. Then, only the empty (unoccupied) RBs are utilized per measurement results (Lien et al. 2014).

8.3.8  Roadmapping of Technology Features After evaluation of the technology features, the features are distributed according to the timeline considering their relative importance. The technology features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the technology features are ranked, they are placed on the roadmap according to short term and long term, e.g., Hash algorithm is a short-term feature whereas Extensible Authentication Protocol (EAP) which comes under the category of security features in a long-term feature. Figure 8.3 shows the technology features in telecommunication sector.

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97

Fig. 8.3  Roadmapping of technology features—telecommunication

8.3.9  Mapping of Technology Features and Product Features The mapping of product features and technology features, so as to say, the link between product features and technology features is performed using a quality function deployment. The product features are listed on the x-axis and technology features are listed on the y-axis. Next, the product features which are weighted by the experts are given a correlation with the technology features on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation and 3 denotes complete correlation. Henceforth, the summation of the product of product features and technology features is performed and illustrated in the ‘total’ column and finally a ‘rank’ is given based on the total score. Table 8.5 QFD matrix for technology features versus product features.

8.3.10  Roadmapping of Enablers After evaluation of the enablers as mentioned in Sect. 8.3, the enablers are distributed according to the timeline considering their relative importance. The enablers’ features are ranked by the experts on a scale of 1–10 with 10 being the highest and 1 being the lowest. After the enablers are ranked, they are placed on the roadmap accordingly e.g., “cloud computing” could be seen as a long-term prospect for achieving the required technology features. Figure 8.4 shows the timeline of industry 4.0 enablers’ roadmap.

8.3.11  Mapping of Technology Features and Enablers The mapping of technology features and enablers, which is the link between technology features and enablers is performed using a quality function deployment. The technology features are listed on the x-axis and enablers are listed on the y-axis. Next, the technology features which are weighted by the experts are given a correlation

Technology features Low cost equipment 802.11 IEEE equipment Wireless equivalent privacy (WEP) Wireless access points Network optimization algorithms Parallel redundancy protocol Packet scheduling

Product features Weight Levels 2 3 2 1 0 2 1

1 1

0

2

Wi-Fi speed 8 P2

3 1 1

Low cost to use 8 P1

2

1

1 1

1 1 1

Security 8 P3

1

2

2 1

0 2 1

Network coverage 7 P4

0

2

0 1

0 2 3

Network redundancy 6 P5

Table 8.5  QFD matrix for technology features versus product features—telecommunication

0

1

1 0

2 1 0

Radio resource management 5 P6

1

2

1 2

0 0 1

Load balancing 6

53

67

49 41

Total 58 71 63

5

2

Rank 4 1 3

98 8  Value Roadmap Development for Telecommunication Industry

8.3  Technology Feature in Telecommunication

99

Fig. 8.4  Roadmapping of enablers—telecommunication

with the enablers on the y-axis. The correlation is ranked from 0 to 3 where 0 signifies no correlation, 1 signifies low correlation, 2 depicts medium correlation and 3 denotes complete correlation. Henceforth, the summation of the product of technology features and enablers is performed and illustrated in the ‘total’ column and finally a ‘rank’ is given based on the total score. Table 8.6 shows QFD matrix for enablers vs. technology features.

Big data Predictive maintenance Cloud computing Digital twin Autonomous robots Augmented reality Sensors 3D printing

Enablers

Technology features Weight Levels

802.11 IEEE standard 7 T2 0 2 1 0 0 2 1 1

Low cost equipment 6 T1 1 0

0

1 0

1

1 2

0 1

0

2 0

3

Wireless equivalent privacy (WEP) 8 T3 1 1

2 2

1

2 0

0

Wireless access points 6 T4 1 2

Table 8.6  QFD matrix for enablers versus technology features—telecommunication

0 2

0

2 0

2

Network optimization algorithms 7 T5 2 0

1 1

0

1 0

1

Parallel redundancy protocol 5 T6 0 1

0 0

0

1 0

2

Packet scheduling 8 T7 1 0

30 58

26

61 0

66

Total 42 39

3

2

1

Rank 4 5

100 8  Value Roadmap Development for Telecommunication Industry

Chapter 9

Conclusion

Roadmaps have contributed significantly to the identification of key resources within an organization. Technology roadmapping allows to synchronize business activities with strategies of technology. The healthcare, telecommunication, and automotive industries have been sluggish in including the latest technologies because of not having an effective change management system. The similarities and dissimilarities between the three industries are depicted by the table as it is necessary to show how the roadmaps would differ based on the changing market requirements. With respect to similarities, all three industries contribute a major portion to the GDP of any country and have been making a leap towards digitalization. On the other hand, the dissimilarities comprise of slow acceptance of new technologies except the automotive industry and also that technologies fulfilling the demands of the market are not the same for all three industries. Since the customer demands have increased in the automobile, healthcare, and telecommunication segments, hence it becomes necessary for the organizations to adapt to the newer product and service features. This thesis allows to provide light to the market requirements and presents a platform to achieve those requirements. The industries chosen in this thesis deal with a significantly big market size, hence it becomes necessary for the industries to prioritize tasks and have objectives which could bring in early benefits and also enlist tasks which could be designated as future programs. Three technology roadmaps have therefore been built up which focus on identifying the market drivers, the product features, technology features, industry 4.0 as enablers, and resources. These elements are linked to each other via the QFD methodology. After analyzing the each part of the roadmap, the final value roadmap is put up as shown in Figs.  9.1, 9.2, and 9.3. Table  9.1 illustrates the similarities and differences between three evaluated industries.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_9

101

102

9 Conclusion 2018

2019

2020

2021

2022

2023

2024

2025

Cost

DRIVERS

Sustainability Manufacturing process Costumer experience Digitalization New markets

Disruptive model

PRODUCT FEATURE

Fuel efficiency Ni-Mh batteries

Na-S batteries Feul cell

Range extender Alumium

Plastic

TECHNOLOGY FEATURE

Fully autonomous vehicle

Model catalytic converter Legnin

PHEV

Lithium

PHEV with power train mechanism

ABS 3

ABS spoofer

ENABLERS

Smart sensors Digital twin Big data

Cloud computing Augmented reality

Partnership with universities RESOURCES

Connected autonomous road

Turbo charging

R&D Partnership with subcontractors

Tie up with startups Partnership with companies Crowdsourcing

Fig. 9.1  Value and technology roadmap—automotive

Lignocellulosis Silicon based anodes

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9 Conclusion 2018

2019

2020

2021

2022

2023

2024

Demographic changes DRIVERS

Cost Quality

Access to care Waiting time/list

TECHNOLOGY FEATURE

PRODUCT FEATURE

Patient to doctor interaction using apps

Health wearables as a necessity Remote health monitoring & alert

More efficient & robust sensors

High sensitivity Aladdin platform

Colorimetric nanosensors

Portable monitoring device

Faster data mechanism Export of data Reduce health accident User experience

RFID enabled vehicles multimedia

IS active system Li-Fi

IEEE 802.11 WLAN Wearable antenna on a metal

Liquid antenna Electrowetting on dielectric Giant magnetoresistor (GMR) Intelligent biomedial clothing

Smart sensors ENABLERS

Predictive maintenance Digital twin Big data Cloud computing Augmented reality 3D printing

RESOURCES

Partnership with universities R&D Partnership with subcontractors Tie up with startups

Partnership with companies Crowdsourcing

Fig. 9.2  Value and technology roadmap—healthcare

Watchthru

2025

104

9 Conclusion 2018

2019

2020

2021

2022

2023

2024

2025

Costumer retention Customer relationship Change of telecommunication role DRIVERS

Quality of main lines

Infrastructure management Mobile network size

Bundling Content innovation and commercialization Socio economic development

TECHNOLOGY FEATURE

PRODUCT FEATURE

GDP Hetnets

Self organizing Hetnets

Genetic algorithms

Artificial sworm algorithms (AFSA) Six port modulators

Long term evolution advance Load balancing

Genetic algorithms Multi ant colony optimization

Cognitive radio sense

Li-Fi 802.11

Redundancy controller

IP parallel redundancy protocol Wireless equivalent privacy QoS provisioining in IP networks

Cognitive radio resource management

Five wireless access points

Aerostats

Hash algorithm

Extensible authentication protocol

ENABLERS

Cloud computing Digital twin

3D printing Big data Predictive maintenance

RESOURCES

Partnership with universities

R&D Partnership with subcontractors

Tieup with startups Partnership with companies

Crowdsourcing

Fig. 9.3  Value and technology roadmap—telecommunication

Table 9.1  Comparison between three evaluated sectors—value and technology roadmap Automotive, healthcare, telecommunication

Similarities –  Essential industries for the economy of the country –  Large percentage of GDP –  Large strive towards digitalization

Dissimilarities –  Different customer requirements –  Not the same technology fulfilling all three industries –  Automotive shows a faster leap towards new technology acceptance compared to healthcare and telecommunication

Chapter 10

Limitations and Future Research

A risk and uncertainty analysis could be included to the roadmap as the implementation of any technology includes a certain percentage of risk, therefore suitable risk percentage could be applied to the whole roadmap. Moreover, the expertise of suppliers could also be taken into account as a lot of work gets contracted to the service companies. Some of the limitations of the roadmap which could be overcome are by using more expert interviews for the finalization of the roadmap. Also, the timelines for the short- and long-term goals in the roadmap are estimates as knowing the exact timeline is challenging and hence a rough estimate has been put up.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1_10

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Appendix: Survey

The survey was carried out with a total of nine people coming from three different industries viz. automotive, healthcare, and telecommunication. The quality function deployment has been weighted along with the help from experts. The following table depicts the details of the personnel involved. Industry Telecommunication Telecommunication Telecommunication Healthcare Healthcare Healthcare Automotive Automotive Automotive

Designation Vice President Technology Consultant Senior Recruiter Associate IT Strategist Strategic Technologist Calibration Engineer VP Strategy and Business Development Project Manager

Company Deutsche Telekom T-System multimedia solutions Deutsche Telekom IQVIA consulting services Siemens Healthcare GE Healthcare Volvo GTT Benteler Automotive SEG Automotive

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References

Agubor, C., Chukwudebe, G., & Nosiri, O. (2015). Security challenges to telecommunication networks: An overview of threats and preventive strategies. Cyberspace (CYBER-Abuja). Alam, M., et al. (2018). Current and future trends in wireless communications protocols and technologies. Mobile Networks and Applications, 23(3), 377–381. Alarcón, M.  J., Zorzano, F.  J., Jevtić, A., & Andina, D. (2008). Telecommunications network planning and maintenance. s.l., 12th World Multiconference on Systemics, Cybernetics and Informatics (WMSCI 2008). Orlando, USA, from 29 June–2 July. Albert, K. D. (2018). Dignited. [Online]. Retrieved September 2018. AlMohimeed, I., Turkistani, H., & Ono, Y. (2013). Development of wearable and flexible ultrasonic sensor for skeletal muscle monitoring. Ultrasonics Symposium (IUS), IEEE International. Anand, A., Muthukrishnan, C., Akella, A., & Ramjee, R. (2009). Redundancy in network traffic: findings and implications. ACM SIGMETRICS Performance Evaluation Review, 37(1), 37–48. Andwari, A. M., et al. (2017). A review of battery electric vehicle technology and readiness levels. Renewable and Sustainable Energy Reviews, 78, 414–430. Aschilean, I., Varlam, M., Culcer, M., Iliescu, M., Raceanu, M., Enache, A., et al. (2018). Hybrid electric powertrain with fuel cells for a series vehicle. Energies, 11(5), 1294. Asimakopoulos, S., Asimakopoulos, G., & Spillerss, F. (2017). Motivation and user engagement in fitness tracking: Heuristics for mobile healthcare wearables. Infromatics Multidisciplinary Digital Publishing Institute, 4(1), 5. Aslani, A., Eftekhari, H., Hamidi, M., & Nabavi, B. (2015). Commercialization methods of a new product/service in ICT industry: Case of a science & technology park. Organizacija, 48(2), 131–138. Baker, D. A., & Rials, T. G. (2013). Recent advances in low-cost carbon fiber manufacture from lignin. Journal of Applied Polymer Science, 130(2), 713–728. Balan, K., et al. (2017). Analysis of CO2, CO and HC emission reduction in automobiles. IOP Conference Series: Materials Science and Engineering, 197(1), 012012. Bannister, F., & Remenyi, D. (2000). Acts of faith: instinct, value and IT investment decisions. Journal of Information Technology, 15(3), 231–241. Bao, W., & Liang, B. (2015, April). Radio resource allocation in heterogeneous wireless networks: A spatial-temporal perspective. In 2015 IEEE Conference on Computer Communications (INFOCOM) (pp. 334–342). IEEE. Bellalta, B. (2015). IEEE 802.11ax: High-efficiency WLANs. IEEE Wireless Communications, 23(1), 38–46. Belle, A., et al. (2015). Big data analytics in healthcare. Journal of Biomedicine and Biotechnology.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 T. U. Daim, Z. Faili, Industry 4.0 Value Roadmap, SpringerBriefs in Entrepreneurship and Innovation, https://doi.org/10.1007/978-3-030-30066-1

109

110

References

Bilaye, P., et al. (2009). Low cost wireless internet access for rural areas using tethered aerostats. s.l., Industrial and Information Systems, 2008. ICIIS 2008. IEEE Region 10 and the Third International Conference. Biradar, S., Patil, R., & Ullegaddi, M. (1998). Energy storage system in electric vehicle. Power Quality'98. Biswas, S., & Misra, S. (2015). Designing of a prototype of e-health monitoring system. s.l., Research in Computational Intelligence and Communication Networks (ICRCICN), 2015 IEEE International Conference. Blery, E. K., & Michalakopoulos, M. G. (2006). An e-CRM application in the telecommunications sector: A case study from Greece. EuroMed Journal of Business, 1(2), 5–14. Boschert, S., Heinrich, C., & Rosen, R. (2018). Next generation digital twin. s.l., Proceedings of TMCE 2018, 7–11 May, 2018, Las Palmas de Gran Canaria, Spain. Brabazon, P., MacCarthy, B., & Woodcock, A. (2010). Mass customization in the automotive industry: comparing interdealer trading and reconfiguration flexibilities in order fulfillment. Production and Operations Management, 19(5). Bray, O.  H., & Garcia, M.  L. (1997). Technology roadmapping: The integration of strategic and technology planning for competitiveness. Proceedings of the Portland International Conference. Brockfeld, E., Lorkowski, S., Mieth, P., & Wagner, P. (2007). Benefits and limits of recent floating car data technology–an evaluation study. Berkeley, Proceedings of the 11th World Conference Transportation Research, Berkeley, CA. Brown, C. (2018). Forbes—three ways to use wearable technology to enhance the customer experience. [Online]. Retrieved October 2018, from https://www.forbes.com/sites/forbestechcouncil/2018/08/06/three-ways-to-use-wearable-technology-to-enhance-the-customerexperience/#3566c39c3660 Bruynseels, K., Santoni de Sio, F., & Van den Hoven, J. (2018). Digital twins in health care: Ethical implications of an emerging engineering paradigm. Front Genet, 9, 31. Budianto, E., Hafidh, A., Al Afif, F., Wibowo, A., Jatmiko, W., Hardian, B., et  al. (2011). Autonomous telecommunication networks coverage area expansion in disaster area using mobile robots. In 2011 International Symposium on Micro-NanoMechatronics and Human Science. IEEE. Bughin, J. R., & Mendonça, P. (2007). Convergence and triple play bundling: An empirical assessment for European telecommunications. Communications & Strategies, 68, 121. Butler, F. C., & Martin, J. (2016). The auto industry: Adapt to diruptive innovations or risk extinction. Emerald Group Publishing, 32(11), 31–34. Carlà, L., et al. (2016). LTE enhancements for public safety and security communications to support group multimedia communications. IEEE Network, 30(1), 80–85. Chanias, S., & Hess, T. (2016). Understanding digital transformation strategy formation: Insights from Europe’s automotive industry. Proceedings of the 20th Pacific Asia Conference on Information Systems (PACIS), Chiayi, Taiwan. Chen, C. M. (2016). Use cases and challenges in telecom big data analytics. APSIPA Transactions on Signal and Information Processing, 5, e19. Chin, C. M., Tan, C. M., & Sim, M. L. (2006). Future trends in radio resource management for wireless communications. BT Technology Journal, 24(2), 103–110. Chowdhury, M. E., et al. (2018). Wearable realtime heart attack detection and warning system to reduce car accidents in Qatar. Qatar Foundation Annual Research Conference Proceedings, 2018(2). Comer, D., Karandikar, R. H., & Rastegarnia, A. (2016, January). Redundancy control using software defined networking. In 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC) (pp. 638-641). IEEE. Consortium, C. (2018). Roadmapping: The S-plan approach to identifying and exploring strategic, innovation and business opportunities. [Online]. Retrieved August 2018, from https://www.cutter.com/consulting/roadmapping-s-plan-approach-identifying-and-exploring-strategic-innovation-and-business

References

111

Dahlin, A. B. (2012). Size matters: problems and advantages associated with highly miniaturized sensors. Sensors (Basel), 12(3), 3018–3036. Daim, T., et  al. (2018). Strategic roadmapping of robotics technologies for the power industry: A multicriteria technology assessment. Technological Forecasting and Social Change, 131, 49–66. Dalela, P. K., Yadav, A., & Tyagi, V. (2016, November). Security enhancement in tower monitoring system of one M2M network. In 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (pp. 1–5). IEEE. Dattatreya, P.  H. (2016). Invited paper: Future automotive interiors-the 3rd living space. SID Symposium Digest of Technical Papers, 47(1). DaWei, W., & Changliang, W. (2015). Wireless sensor networks coverage optimization based on improved AFSA algorithm. International Journal of Future Generation Communication and Networking, 8(1), 99–108. De Blas, V., et al. (2006). A new advanced management solution for telecom infrastructure equipments and buildings. Telecommunications Energy Conference, 2006. INTELEC'06. 28th Annual International. de Sousa, R. J. T. (2016). Radio resource management strategies in LTE networks, s.l.: Tecnico Lisboa. Deep, G., & Kush, A. (2010). Proposal for low cost wireless networking. International Journal of Computing and Business Research (IJCBR), 1(1). Dhall, R., & Solanki, V. (2017). An IoT based predictive connected car maintenance approach. International Journal of Interactive Multimedia and Artificial Intelligence, 4(3), 16–22. Díaz-Pinés, A., & Vareda, J.  (2016). Bundling behavior in telecoms: What firms do and how European competition authorities have included bundling in their reasoning, s.l.: s.n. Dissel, M.  C., Phaal, R., Farrukh, C., & Probert, D. (2006). Value roadmapping: A structured approach for early stage technology investment decisions. 2006 Technology Management for the Global Future—PICMET 2006 Conference. Dolićanin, Ć., Kajan, E., Randjelović, D., & Stojanović, B. (2015). Handbook of research on democratic strategies and citizen-centered E-government services. Information Science Reference. ElAzhari, M., El Moussaid, N., Toumanari, A., & Latif, R. (2017). Equalized energy consumption in wireless body area networks for a prolonged network lifetime. Wireless Communications and Mobile Computing, 2017, 9. European Commission. (2014). Impact of information on patients’ choice within the context of the Directive 2011/24/EU of the European Parliament and of the Council on the application of patients’ rights in cross-border healthcare. London Economics. European Parliament. (2018). European Parliament cutting EU greenhouse gas emissions: National targets for 2030. [Online]. Retrieved September 2018, from http://www.europarl.europa.eu/news/en/headlines/society/20180208STO97442/ cutting-eu-greenhouse-gas-emissions-national-targets-for-2030 Fagen, D., Vicharelli, P., & Weitzen, J. (2006). Automated coverage optimization in wireless networks. s.l., Vehicular Technology Conference, 2006. VTC-2006 Fall. Faulkner, T.  W. (1996). Applying ‘options thinking’ to R&D valuation. Research-Technology Management, 39(3), 50–56. Fayadh, R. (2017). Performance enhancement of wireless communication at high speeds public transportation vehicles. Journal of Next Generation Information Technology (JNIT), 8(4), 9–16. Feng, K., et al. (2018). Silicon-based anodes for lithium-ion batteries: from fundamentals to practical applications. Small, 14(8). Fenwick, D., Daim, T. D., & Gerdsri, N. (2009). Value driven technology road mapping (VTRM) process integrating decision making and marketing tools: Case of Internet security technologies. Technological Forecasting & Social Change—Elsevier, 76(8), 1055–1077. Ferràs-Hernández, X., Tarrats-Pons, E., & Arimany-Serrat, N. (2017). Disruption in the automotive industry: A Cambrian moment. Business Horizons, 60(6), 855–863. Fleiss, M., Mueller, T. M., Nilsson, M., & Carlsson, J. (2016). Volvo powertrain integration into complete vehicle. ATZ Worldwide, 118(3), 16–21.

112

References

Fletcher, R. R., Poh, M.-Z., & Eydgahi, H. (2010). Wearable sensors: opportunities and challenges for low-cost health care. s.l., Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. Gamper, H., & Lokki, T. (2010). Audio augmented reality in telecommunication through virtual. s.l., The 16th International Conference on Auditory Display. Gao, F., Thiebes, S., & Sunyaev, A. (2018). Rethinking the meaning of cloud computing for health care: A taxonomic perspective and future research directions. Journal of Medical Internet Research, 20(7), e10041. Gatimu, R. M., Cheruiyot, W., & Kimwele, M. (2015). Enhancing data staging as a mechanism for fast data access. International Journal of Computer Applications Technology and Research, 4(8), 584–591. Ghafoor, K. Z., Mohammed, M. A., Bakar, K. A., Sadiq, A. S., & Lloret, J. (2014). Vehicular cloud computing: trends and challenges. In Mobile Networks and Cloud Computing Convergence for Progressive Services and Applications (pp. 262–274). IGI Global. Gong, S., & Karlsson, M. (2016). Pushing the wireless data rate to the Internet speed. IEEE Access, 4, 8787–8792. Goswami, N., Garala, K., & Maheta, P. (2015). Cloud load balancing based on ant colony optimization algorithm. IOSR Journal of Computer Engineering (IOSR-JCE), 3, 11–18. Goulding, C. (2018). 3D printing 5G telecommunication technology. [Online]. Retrieved October 2018, from https://3dprint.com/217744/3d-printing-5g-telecommunication/ Groenveld, P. (1997). Roadmapping integrates business and technology. Research-Technology Management—Taylor & Francis, 40(5). GSMA. (2015). GSMA—mobile spectrum—data demand explained, s.l.: s.n. Gupta, N., Kumar, N., & Jain, S. (2016). Coverage problem in wireless sensor networks: A survey. Signal Processing, Communication, Power and Embedded System (SCOPES). Haensel, K., Wilde, N., Haddadi, H., & Alomainy, A. (2015). Challenges with current wearable technology in monitoring health data and providing positive behavioural support. Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering). Hanelt, A., Piccinini, E., Hildebrandt, B., & Kolbe, M. (2015). Digital transformation of primarily physical industries-exploring the impact of digital trends on business models of automobile manufacturers. Osnabrück: Internationalen Tagung Wirtschaftsinformatik. Hasu, V. (2007). Radio resource management in wireless communication: Beamforming, transmission power control, and rate allocation. Espoo: Helsinki University of Technology Control Engineering Laboratory. Hebbar, G. (2014). NOx from diesel engine emission and control strategies-a review. International Journal of Mechanical Engineering and Robotics Research, 3(4), 471–482. Helmers, E., & Marx, P. (2012). Electric cars: Technical characteristics and environmental impacts. Environmental sciences EuropeBridging science and regulation at the regional and European level. Hermann, M., Pentek, T., & Otto, B. (2015). Design principles for Industrie 4.0 scenarios: A literature review. Technical University of Dortmund, Faculty of Engineering, Audi Endowment Chair Supply Net Order Management, 1. Hess, W. (2006). The telecommunications market: The dawn of a new era, s.l.: Allianz Dresdner Economic Research. Himperich, F. (2007). Applications of augmented reality in the automotive industry. pp. 1–21. Horowitz, M., Rosensweig, J., & Jones, C. (2007). Medical tourism: globalization of the healthcare marketplace. Medscape General Medicine, 9(4), 33. Iclodean, C., et  al. (2017). Comparison of different battery types for electric vehicles. IOP Conference Series: Materials Science and Engineering, 252(1). Ide, C., Niehoefer, B., Knaup, T., Weber, D., Wietfeld, C., Habel, L., & Schreckenberg, M. (2012, September). Efficient floating car data transmission via LTE for travel time estimation of vehicles. In 2012 IEEE Vehicular Technology Conference (VTC Fall) (pp. 1–5). IEEE.

References

113

ILC-UK. (2012). The impact of demographic change on public services. The International Longevity Centre—UK. Ilevbare, I., Phaal, R., Probert, D., & Torres Padilla, A. (2011). Integration of TRIZ and roadmapping for innovation, strategy, and problem solving (pp. 25–30). Cambridge: University of Cambridge. Inertia Technology. (2018). IS-ACTIVE—Inertial Sensing Systems for Advanced Chronic Condition Monitoring and Risk Prevention. [Online]. Retrieved September 2018, from http://inertia-technology.com/project/active-ambient-assisted-living-european-program/ International Energy Agency. (2005). Making cars more fuel efficient. s.l., European Conference of Ministers of Transport. Islam, T., & Mukhopadhayay, S. C. (2017). Wearable sensors for physiological parameters measurement: physics, characteristics, design and applications. In S. C. Mukhopadhyay & T. Islam (Eds.), Wearable sensors: applications, design and implementation (pp.  1–31). Bristol: IOP Publishing. Jain, S., & Garg, R.  K. (2007). Business competitiveness: Strategies for automobile industry. Kozhikode: Indian Institute of Management. Jawad, H. M., et al. (2017). Energy-efficient wireless sensor networks for precision agriculture: A review. Sensors (Basel), 17(8). Jyh-Fu Jeng, D., & Bailey, T. (2012). Assessing customer retention strategies in mobile telecommunications: Hybrid MCDM approach. Management Decision, 50(9), 1570–1595. Kadry, S., Abid, M., & Ionescu, S. (2018). Preventive & predictive maintenance of telecommunication equipment—A review. s.l., Steifedine Kadry. Kahraman, C., Ruan, D., & Tolga, E. (2002). Capital budgeting techniques using discounted fuzzy versus probabilistic cash flows. Information Sciences-Elsevier, 142(1–4), 57–76. Katona, R., & Baier, D. (2005). Customer relationship management in the telecommunications and utilities markets. In Innovations in Classification, Data Science, and Information Systems (pp. 346–354). Berlin, Heidelberg: Springer. Khajavi, S., & Holmstroem, J. (2016). Manufacturing digitalization and its effects on production planning and control practices. Espoo, Finland, s.n. Khorasani-Zavareh, D., Shoar, S., & Saadat, S. (2013). Antilock braking system effectiveness in prevention of road traffic crashes in Iran. BMC Public Health, 13(1), 439. Kim, I., Lai, P.-H., Lobo, R., & Gluckman, B. (2014). Challenges in wearable personal health monitoring systems. s.l., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, vol. 2014. Kim, D., & Steinfield, C. (2004). Consumers mobile internet service satisfaction and their continuance intentions. AMCIS 2004 Proceedings, 332. Kim, B. G., Tredeau, F. P., & Salameh, Z. M. (2008, July). Fast chargeability lithium polymer batteries. In 2008 IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century (pp. 1–5). IEEE. Kollaikal, P., Ravuri, S., & Ruvinsky, E. (2015). Connected cars, s.l.: Sutardja Center for Entrepreneurship & Technology Technical Report. Kostoff, R. N., & Schaller, R. R. (2001). Science and Technology Roadmaps. IEEE Transactions on Engineeringg Management, 48(2), 132–143. Kothaluru, T. R., & Mecca, M. Y. S. (2012). Evaluation of EAP authentication methods in wired and wireless networks. Karlskrona: Blekinge Institute of Technology. Krishna, V., Wu, K., Perez, A., & Wang, J.-P. (2016). Giant magnetoresistance-based biosensor for detection of influenza A virus. Frontiers in Microbiology, 7, 400. Lakbabi, A., Orhanou, G., & ElHajji, S. (2012). Network access control technology—proposition to contain new security challenges. International Journal of Communications, Network and System Sciences, 5(8), 8. Lampón, J. F., Cabanelas, P., & Frigant, V. (2017). The new automobile modular platforms: from the product architecture to the manufacturing network approach. Munich: University of Muenchen.

114

References

Lee, Y. L., Chuah, T. C., Loo, J., & Vinel, A. (2014). Recent advances in radio resource management for heterogeneous LTE/LTE-A networks. IEEE Communications Surveys & Tutorials, 16(4), 2142–2180. Lee, S.  S., Li, K.  Y., & Lin, C.  C. (2015). Modeling and algorithm for multiple spanning tree provisioning in resilient and load balanced ethernet networks. Mathematical Problems in Engineering, 2015, 10. Li, J., & Tang, L. (2017). Plasmon-based colorimetric nanosensors for ultrasensitive molecular diagnostics. ACS Sensors, 2(7), 857–875. Li, Q., Zhang, T., & Yu, Y. (2011). Using cloud computing to process intensive floating car data for urban traffic surveillance. International Journal of Geographical Information Science, 25(8), 1303–1322. Li, G., et al. (2017). A watch strap antenna for the applications of wearable systems. IEEE Access, 5, 10332–10338. Liang, B., & Wei, B. (2015). Radio resource allocation in heterogeneous wireless networks: a spatial-­temporal perspective. Computer Communications (INFOCOM), 2015 IEEE Conference. Lien, S.-Y., Chen, K.-C., Liang, Y.-C., & Lin, Y. (2014). Cognitive radio resource management for future cellular networks. IEEE Wireless Communications, 21(1), 70–79. Luka, G., et al. (2015). Microfluidics integrated biosensors: A leading technology towards lab-on-­ a-chip and sensing applications. Sensors (Basel), 15(12), 30011–30031. Lymberis, A. (2003, September). Smart wearable systems for personalised health management: current R&D and future challenges. In Proc. 25th Ann. Int. Conf. IEEE EMBS (Vol. 4, pp. 3716–3719). Lymberis, A., & Olsson, S. (2003). Intelligent biomedical clothing for personal health and disease management: State of the art and future vision. Telemedicine Journal and e-Health, 9(4), 379–386. Mackert, M., et al. (2016). Health literacy and health information technology adoption: The potential for a new digital divide. Journal of Medical Internet Research, 18(10), e264. Maiwada, B., Muaz, N., & Musa, G. H. (2016). Diesel engine modification techniques to minimize its exhaust emission (theoretical survey). International Journal on Theoretical and Applied Research in Mechanical Engineering, 5(1), 1–7. Majumder, S., Mondal, T., & Deen, M. J. (2017). Wearable sensors for remote health monitoring. Sensors (Basel). 17(1). Malim, G. (2018). The global voice of telecoms IT. [Online]. Retrieved October 2018, from https://www. vanillaplus.com/2018/05/21/38426-can-telecoms-industry-successfully-adopt-digital-twins/ Manghnani, R. (2015). An exploratory study: The impact of additive manufacturing on the automobile industry. International Journal of Current Engineering and Technology, 5(5), 3407–3410. Messerer, A., Rother, D., Poeschl, U., & Niessner, R. (2004). Advances in the development of filterless soot deposition systems for the continuous removal of diesel particulate matter. Topics in Catalysis, 30(1–4), 247–250. Mills, D. (2015). Future medicine: The impact of 3D printing. Journal of Nanomaterials & Molecular Nanotechnology. 4(3). Mishra, S., & Mathur, N. (2014). Load balancing optimization in LTE/LTE-A cellular networks: A review. Mishra, N.  K., & Mishra, N. (2015). Load balancing techniques: need, objectives and major challenges in cloud computing-a systematic review. International Journal of Computer Applications, 131(18), 148–154. Mitchell, B. (2018). The range of a typical Wi-Fi network. [Online]. Retrieved September 2018, from https://www.lifewire.com/range-of-typical-wifi-network-816564 Modwel, G., Rakesh, N., & Mishra, K. K. (2015, December). Wireless body control module. In 2015 Third International Conference on Image Information Processing (ICIIP) (pp. 353–357). IEEE. Monteiro, A. J. M. (2001). Production Cost Modelling for the Automotive Industry. Master Thesis. Retrieved from http://users.isr.ist.utl.pt/~cfb/MSc3-thesis.pdf

References

115

Morschheuser, B., Werder, K., Hamari, J., & Abe, J. (2017). How to gamify? A method for designing gamification. s.l., Proceedings of the 50th Hawaii International Conference on System Sciences. Natalense, J., & Zouain, D. (2013). Technology roadmapping for renewable fuels. Journal of Technology Management & Innovation, 8(4), 143–152. Nath, C. K. (2009). Customers’ expectations towards car in an unorganized environment—A factoral analysis. African Journal of Business Management, 2(4), 160–167. National Energy Strategy. (n.d.) Chapter 4: Efficiency of Energy Conversion. Retrieved from https://personal.ems.psu.edu/~radovic/Chapter4.pdf National Telecom Regulatory Authority. (2003). Wi-Fi technology, s.l.: Technical Affairs & Technology Sector. Oniz, Y., Kayacan, E., & Kaynak, O. (2009). A dynamic method to forecast the wheel slip for antilock braking system and its experimental evaluation. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39(2), 551–560. Øverby, H. (2004). Network layer packet redundancy in optical packet switched networks. Optics Express, 12(20), 4881–4895. Papić, S. (2016). Achieving optimal redundancy in a small business network. International Journal of Digital Technology & Economy, 1(1), 13–23. Peters, S., Chun, J.-H., & Lanza, G. (2016). Digitalization of automotive industry—scenarios for future manufacturing. Manufacturing Review, 3(1), 1–8. Petri, D. (2017). [Online]. Retrieved August 2018, from https://offertaformativa.unitn.it/…a6f3…/ Industry%204.0_%20Petri%20Seminar.pdf Phaal, R. (2005). Justifying and selecting innovation projects—Strategic roadmapping linking technology to markets. The IEE Seminar on Justifying and Selecting Innovation Projects, 2005 (Ref. No. 2005/11260), pp. 6/1–6/14. Phaal, R. (2015). Roadmapping for strategy and innovation. IEEE Seminar on justifying and selecting innovation projects. Phaal, R., Farrukh, C.  J., & Probert, D.  R. (2001a). Characterisation of technology roadmaps: Purpose and format. PICMET '01. Portland International Conference on Management of Engineering and Technology. Proceedings: Book of Summaries (IEEE Cat. No.01CH37199), Volume 1. Phaal, R., Farrukh, C., & Probert, D. (2001b). Technology roadmapping: linking technology resources to business objectives (pp. 1–18). Cambridge: Centre for Technology Management, University of Cambridge. Phaal, R., Farrukh, C., & Probert, D. (2004a). Technology roadmapping—A planning framework for evolution and revolution. Technological Forecasting and Social Change-Science Direct, 71, 5–26. Phaal, R., Farrukh, C., & Probert, D. (2004b). Customizing roadmapping. Research-Technology Management, 47(2), 26–37. Phaal, R., Farrukh, C., & Probert, D.  R. (2013). Technology management and roadmapping (pp. 13–29). Berlin and Heidelberg: Springer. Piumetti, M., Bensaid, S., Fino, D., & Russo, N. (2016). Catalysis in diesel engine NOx after treatment: a review. Catalysis, Structure & Reactivity, 1(4), 155–173. Popovic, M., Mohiuddin, M., Tomozei, D.-C., & Boudec, J.-Y. (2015). iPRP: Parallel redundancy protocol for IP networks. Factory Communication Systems (WFCS), 2015 IEEE World Conference. Pöttner, W.-B. (2014). Reliable end-to-end data transmission in wireless sensor networks (doctoral dissertation). Qiao, G., Lu, R., & McLean, C. (2006). Flexible manufacturing systems for mass customisation manufacturing. International Journal of Mass Customisation, 1(2–3), 374–393. Ranky, P.  G. (2002). Advanced digital automobile sensor applications. Sensor Review, 22(3), 213–217. Raparthi, R. K. (n.d.). mHealth sensors: Innovation in the pharmaceutical & health care therapy. Research and Reviews: Journal of Pharmaceutics and Nanotechnology, 4(2).

116

References

Raposo, A., Ciuffo, M., Makridis, M., & Thiel, C. (2017). The r-evolution of driving: from Connected Vehicles to Coordinated Automated Road Transport (C-ART), s.l.: European Commission. Raut, S. (2016). Simplified analytics—welcome to industry 4.0. [Online]. Retrieved August 2018, from https://simplified-analytics.blogspot.com/2016/04/welcome-to-industry-40.html Raut, S. (2017). Industry 4.0: Digital transformation in manufacturing. [Online]. Retrieved August 2018, from https://www.digitalistmag.com/iot/2017/04/25/ industry-4-0-digital-transformation-in-manufacturing-05041191 Ray, B. (2018). Link labs. [Online]. Retrieved September 2018, from https://www.link-labs.com/ blog/future-of-wifi-802-11ah-802-11ad Rentschler, M., & Heine, H. (2013). The parallel redundancy protocol for industrial IP networks. s.l., s.n. Riasanow, T., Galic, G., & Böhm, M.. (2017). Digital transformation in the automotive industry: Towards a generic value network. In Proceedings of the 25th European Conference on Information System (ECIS), pp. 3191–3201. Riek, L. (2017). Healthcare robotics. Communications of the ACM, 60(11), 68–78. Rivero, A.  R. G., & Daim, T. (2017). Technology roadmap: Cattle farming sustainability in Germany. Journal of Cleaner Production, 143, 4310–4326. Rodrigues Vaz, C., Shoeninger Rauen, T. R., & Rojas Lezana, A. G. (2017). Sustainability and innovation in the automotive sector: A structured content analysis. Sustainability, 9(6), 880. Rojko, A. (2017). Industry 4.0 concept: Background and overview. ECPE European Center for Power Electronics e.V., Nuremberg, Germany, 11(5), 77–87. Rue, T. J. (2015). Modular vehicle design concept (Doctoral dissertation, Virginia Tech). Ruehling, K. (2018). Continnetal. [Online]. Retrieved September 2018, from https://www. continental-tires.com/car/media-services/newsroom/continental-technikforum-2018/ press-releases/20180223-abs-generation-from-continental Ryan, M., & Eyers, D. (n.d.). Digital manufacturing for spare parts: Scenarios for the automotive supply chain. s.l., s.n. Sakib, N., Jaigirdar, F. T., Munim, M., & Akter, A. (2011). Security improvement of WPA 2 (Wi-­ Fi protected access 2). International Journal of Engineering Science and Technology (IJEST), 3(1), 723–729. Saleh, N., et al. (2015). Preventive maintenance prioritization index of medical equipment using quality function deployment. IEEE Journal of Biomedical and Health Informatics, 19(3), 1029–1035. Salkintzis, A. (1999). Packet data over cellular networks: The CDPD approach. IEEE Communications Magazine, 37(6), 152–159. Salman, A., & Ashraf, M. (2006). Radio resource management issues for 3G and beyond cellular wireless networks. s.l., IEEE—GCC Conference (GCC). Sarkar, A., Agarwal, S., & Nath, A. (2015). Li-Fi technology: Data transmission through visible light. International Journal of Advance Research in Computer Science and Management Studies, 3(6), 1–10. Sathiya, M., & Dhanalakshmi, S. (2015). An overview of IEEE802.11 wireless LAN technologies. International Journal of Computer Science and Mobile Computing, 4(1), 85–93. Scholz-Reiter, B., & Freitag, M. (2007). Autonomous processes in assembly systems. CIRP Annals, 56(2), 712–729. Shaikh, T., Chaudhari, S., & Rasania, H. (2013). Air bag: A safety restraint system of an automobile. International Journal of Engineering Research and Application, 3(5), 615–621. Sharma, V., Rajput, S., & Kumar Sharma, P. (2016). Light fidelity (Li-Fi): An effective solution for data transmission. s.l., AIP Conference Proceedings. Shoukry, Y., Martin, P., & Srivastava, M. (2013). Non-invasive spoofing attacks for anti-lock braking systems. International Workshop on Cryptographic Hardware and Embedded Systems. Simonji-Ellias, M., et  al. (2014). KPMG’s global automotive executive survey 2014. [Online]. Retrieved August 2018, from https://www.kpmg.com/DE/de/Documents/global-automotiveexecutive-survey-2014-KPMG.pdf

References

117

Singh, M.  K. (2016). Application of Steel in Automotive Industry. International Journal of Emerging Technology and Advanced Engineering, 6(7), 246–253. Soh, P. J., Vandenbosch, G., & Mercuri, M. (2015). Wearable wireless health monitoring systems (WWHMS): Current developments, challenges and future trends. IEEE Microwave Magazine. Soldo, I., & Malarić, K. (2013). Wi-Fi parameter measurements and analysis. Smolenice, Slovakia, e 9th International Conference. Sourav, K., Daim, T., & Herstatt, C. (2018). Technology roadmap for the single-aisle program of a major aircraft industry company. IEEE Engineering Management Review, 46(2), 103–120. Spil, T., Sunyaev, A., Thiebes, S., & Van Baalen, R. (2017). The adoption of wearables for a healthy lifestyle: Can gamification help?. s.l., Proceedings of the 50th Hawaii International Conference on System Sciences. Swierczewska, M., Liu, G., Lee, S., & Chen, X. (2012). High-sensitivity nanosensors for biomarker detection. Chemical Society Reviews, 41(7), 2641–2655. Szeteiová, K. (2010). Automotive materials planstics in automotive markets today. Bratislava: Institute of Production Technologies, Machine Technologies and Materials, Faculty of Material Science and Technology in Trnava, Slovak University of Technology Bratislava. Tang, S.-L., et al. (1998). Augmented reality systems for medical applications. IEEE Engineering in Medicine and Biology, 17(3), 49–58. Tao, F., et al. (2018). Digital twin-driven product design, manufacturing and service with big data. International Journal of Advanced Manufacturing Technology., 94(9–12), 3563–3576. Taub, A. (2006). Automotive materials: technology trends and challenges in the 21st century. MRS bulletin, 31(4), 336–343. Telecom Domain. (2012). Telecommunications industry—business drivers. [Online]. Retrieved September 2018, from http://www.technofunc.com/index.php/domain-knowledge/ telecom-industry/item/telecommunications-industry-business-drivers Thayananthan, V., & Basuhail, A. (2017). Integration of wearable smart sensor for improving e-healthcare. International Journal of Advanced Computer Science and Applications (IJACSA), 8(12), 389–395. Tontus, O. (2017). Drivers of healthcare globalisation and medical tourism. e-Review of Tourism Research, 15(2/3). Traille, A., Yang, L., & Tentzeris, M. (2008). A novel liquid ionic antenna for bio-signal monitoring applications. s.l., s.n. Traub-Merz, R. (2017). The automotive sector in emerging economies: Industrial policies, market dynamics and trade unions. Bonn: Friedrich Ebert Stiftung. Vajda, A., Baucke, S., Catrein, D., Curescu, C., Halén, J., Kempf, J., et al. (2012, March). Cloud computing and telecommunications: Business opportunities, technologies and experimental setup. In 2012 World Telecommunications Congress (pp. 1–6). IEEE. Valliappan, S., Prithvi Raj Mohan, B., & Rakesh Kumar, S. (2017). Design of low-cost, wearable remote health monitoring and alert system for elderly heart patients. s.l., IoT and Application (ICIOT), 2017 International Conference on. Ventola, L. (2014). Mobile devices and apps for health care professionals: Uses and benefits. Pharmacy and Therapeutics, 39(5), 356–364. Vishnu, P., & Ajaykrishna, R. (2011). Cost efficient and optimized energy solution in plug-in hybrid vehicles (PHEV) for public transport system. Bonfring International Journal of Power Systems and Integrated Circuits, 1, 52–55. Vishnu, P., Ajaykrishna, R., & Thirumalini, D. S. (2012). Recent advancements and challenges in plug-in diesel hybrid electric vehicle technology. International Journal of Electrical Engineering & Technology (IJEET), 3(1), 316–325. Voigt, M., Bennison, C., & Hammerschmidt, M. (2014). Big data in the automotive industry. 360°—the Business Transformation Journal, 10. Wang, H., Alidaee, B., & Wang, W. (2012, December). Critical infrastructure management for telecommunication networks. In International Conference on Active Media Technology (pp. 493–501). Berlin, Heidelberg: Springer. Wang, Q., & Balasingham, I. (2010). Wireless sensor networks—An introduction.

118

References

Wen, H., Xiao, Z., Markham, A., & Trigoni, N. (2015). Accuracy estimation for sensor systems. IEEE Transactions on Mobile Computing, 14(7), 1330–1343. Wenig, D., et  al. (2017). WatchThru: Expanding smartwatch displays with mid-air visuals and wrist-worn augmented reality. s.l., Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. Williams, M., & Minjares, R. (2016). A technical summary of Euro 6/VI vehicle emission standards. International Council for Clean Transportation (ICCT). Washington, DC, Retrieved July 10, 2017, from. World Health Organization. (n.d.). The need for seat-belts and child restraints, s.l.: s.n. Yates, R. D., & Mandayam, N. (2000). Challenges in low-cost wireless data transmission. IEEE Signal Processing Magazine, 17(3), 93–102. Zander, J.  (1997). Radio resource management in future wireless networks: Requirements and limitations. IEEE Communications Magazine, 35(8), 30–36. Zhen, Z. (2015). The effect of mobile cellular network performance and contextual factors on smartphone users’ satisfaction. Stockholm: KTH Royal Institute Of Technology—Information and Communication Technology.