Customization 4.0 (eBook)

Stephan Hankammer is a research associate at the Technology and Innovation Management Group at RWTH Aachen University since 2014. He conducts research on ecologically sustainable business models, collaborative value creation, and sustainable consumption. He has been coordinator of a European ECO INNOVERA research project on sustainable mass customization in the consumer electronics industry. Moreover, he has worked on larger mass customization projects in several other industries in both B2C and B2B settings. His field of expertise is sustainable collaborative value creation and he is an enthusiastic interdisciplinary scientist interested in combining different research topics related to sustainable management, innovation management, and business ethics. Kjeld Nielsen is an Associate Professor for the Department of Materials and Production at Aalborg University. Kjeld Nielsen is head of the Mass Customization Research Group. His research interests include mass customization, product configuration, reconfigurable manufacturing systems, and product architecture. Frank T. Piller has headed the Technology and Innovation Management Group at RWTH Aachen University since 2007. Earlier, he worked at the MIT Sloan School of Management and was an assistant professor of management at the TUM Business School (1999-2004). Frank Piller graduated with a Ph.D. in operations management from the University of Würzburg in 1999. His post-doctoral Habilitation degree is from the TUM Business School. Frank Piller has worked as a consultant and delivered executive workshops for many international companies, including several DAX30 and Fortune 500 corporations. As a member of their board of directors or board of scientific advisors, he works with a number of innovative technology companies to bring his research into practice. His current research focuses on the need of established corporations to cope with the challenge of digital transformation and similar disruptive technological innovations. This includes a growing stream of research on digital business models and the systematic design of platform-based business ecosystems, but also research on Leadership for Industrie 4.0 and the establishment of organizational structures and cultures that allow for change. He is the Chairman of a cross-industry group hosted by VDI (Verein Deutsche Ingenieure) to develop standards in the field of platform-based digital business models ("Fachausschuss Geschäftsmodelle für Industrie 4.0"). Günther Schuh is a German engineer and has held the Chair for Production Systems at the RWTH Aachen since 2002. He is also Director of the Research Institute for Rationalization , a member of the Board of Directors of the Machine Tool Laboratory (WZL) of RWTH Aachen University and the Fraunhofer Institute for Production Technology (IPT). A further academic task is the management of RWTH Aachen Campus GmbH. Since 2004, he has also been on the directorate of the Research Institute for Operations Management (FIR) at the RWTH. From 2008 to 2012 he was Vice-President for Industry and Economics of RWTH Aachen University. Prof. Schuh has additionally worked in several supervising and management boards. Ning Wang is a research associate at the Technology and Innovation Management Group at the RWTH Aachen University since 2014. She conducts research in the area of mass customization & personalization, consumer co-creation and user toolkits design. Her research tries to extend the conventional mass customization and personalization understanding from a new perspective: smart products for customized product-services beyond the point of sales. She has been working on research projects of cross-cultural toolkits development for online customization, design parameters of the smart product-service system (Smart PSS) and how to achieve user satisfied customization and data-driven service personalization via a new form of smart product and user interaction design.

Preface 5
Organization 7
Reviewer 7
Acknowledgments 9
Contents 10
About the Editors 15
Part I Customization and Personalization via Smart Products and Smart Services 17
User-Centered Service Innovation for Commercial Vehicles: Plugging in the Handyman Market 18
1 Introduction 18
2 From User Insights to Service Opportunities 20
3 Mass Customisation for Commercial Vehicles: The Plugs Concept 23
3.1 Involving Third Parties in the Plugs Concept 24
3.2 Creating an Open Platform Around the Plugs Concept 25
3.3 Overcoming Open-Source Challenges 27
3.4 Facilitating an Open-Source Development Process 28
4 Conclusion 29
5 Discussion and Implications 30
References 32
Design for Mass Individualisation: Introducing Networked Innovation Approach 33
1 Introduction 33
2 Product Customisation 34
2.1 Customisation Concepts 34
2.2 User-Centered Customisation 35
2.3 Product Design for Mass Individualisation 35
3 Methodology 38
3.1 Overview of the Research Methodology 38
3.2 Industrial Questionnaire Survey 38
4 Results and Discussion 40
4.1 Changes in Traditional Product Design and Customisation Approaches that Need to Be Focused on 40
4.2 Components that Need to Be Focused on 41
4.3 Technologies that Need to Be Integrated 41
4.4 Industrial Questionnaire Survey 42
5 Conclusion and Outlook 45
A.1 Appendix I: Questionnaire Survey with Responses 46
References 48
An Exploratory Study of User Interaction with Smart Products for Customization in the Usage Stage 50
1 Introduction 51
2 Product Customization in the Usage Stage (PCUS) 52
3 Smart Products for Customization in the Usage Stage 52
4 Theoretical Background for User and Smart Product Interaction Design 54
4.1 Product Autonomy 54
4.2 User Perceptions from Autonomous Customization by SPs 55
4.3 User Adaptability and System Adaptivity 57
5 Design Principles for User and Smart Product Interaction Design for PCUS 58
5.1 Cooperative Adaptation: Shared Control Between Users and Smart Products 59
5.1.1 User and SP Coadaptation: Cooperation Between Users and SPs to Better Fulfill Customization Needs 59
5.1.2 SPs Perform Routine Tasks to Reduce Effort for Users and Prepare Support and Suggestions for Users, but Users Are Empowered to Make Decisions [39] 60
5.1.3 Provide Possibilities for Users to Override or Change an Autonomic Adaptation from SPs 60
5.2 Empower Users with Control by Product-to-User Communication About the Product Progress 61
5.2.1 Present Sufficient Indicators and Feedback About the Product Progress, so that Users Can Feel in Control of Smart Product Actions 61
5.2.2 Increase the Process Transparency of How the Different Product/Service Adaptation Is Generated 61
5.3 Trial-and-Error Learning by Both SPs and Users 62
5.3.1 SPs Learn to Continuously Adapt to Users and Provide Exciting Features for Users 62
5.3.2 User Learning About the Meaning and the Value of the Data 63
5.3.3 Smart Products as Tools to Facilitate the Trial-and-Error Learning Process of User Co-creation in the Usage Stage 63
6 Conclusions 63
References 64
Datamodels for PSS Development and Configuration: Existing Approaches and Future Research 67
1 Introduction 67
2 Methodology 68
3 Product-Service Systems (PSS) 69
3.1 PSS Development 70
3.2 Computer-Aided PSS Design 71
3.3 Computer-Aided PSS Configuration 72
3.4 Modularization 73
3.5 Intermediate Result 74
4 PSS Modeling Principles 74
4.1 Modeling Principles in Product Development 75
4.2 Parametric Models in Product Development 76
4.3 The Extension of Steinbach's Approach 77
4.4 Limits of the Approach 81
4.5 The Extension by a Modular Model 82
5 Conclusion and Further Research 83
5.1 Conclusion 83
5.2 Further Research 84
References 84
Demand Engineering in Mass Customization Using Data-Driven Approach 87
1 Introduction 87
2 Related Work 88
3 Methodology (Framework) 90
3.1 Demand Identification 91
3.2 Product Function/Matching 93
3.3 Design, Process, and Logistic Optimization 94
3.4 Verification 94
4 Scope of Use 95
5 Conclusion and Discussion 96
References 97
Adapting Product-Service System Methods for the Digital Era: Requirements for Smart PSS Engineering 99
1 Introduction 99
1.1 Motivation and Research Approach 99
1.2 Research Background 100
1.2.1 Product-Service Systems 100
1.2.2 Smart Products and Smart Services 101
1.2.3 Smart Product-Service System 102
2 Analysis of Methods for PSSE 102
2.1 Recent Work and Literature Review 102
2.1.1 Result Matrix for PSS Development Methods 103
3 Results and Discussion 105
3.1 Influence of Digitalization on Characteristic Occurrences 105
3.2 Conclusion 106
References 108
Part II Digital Manufacturing and Industrie 4.0 112
A Marketplace for Smart Production Ecosystems 113
1 Introduction and Motivation 113
2 Smart Production Marketplace 115
2.1 Marketplace Artifacts 115
2.2 Marketplace Services 116
3 Modeling for the Marketplace 117
3.1 Ontology Creation and Maintenance 117
3.2 Equipment Modeling 118
3.3 Product Modeling 121
4 Configuration Activities 122
4.1 Product Configuration 122
4.2 Factory Configuration 123
4.3 Producibility Tests 124
5 Evaluation of the Approach 126
5.1 Marketplace Implementation 126
5.2 Example Capability Ontology 126
5.3 Product Modeling 127
5.4 Equipment and Factory Models 128
5.5 Product Configuration 129
6 Related Work 129
7 Lessons Learned and Future Work 131
References 132
Exploring Barriers Toward the Development of Changeable and Reconfigurable Manufacturing Systems for Mass-Customized Products: An Industrial Survey 134
1 Introduction 134
2 Related Research 136
3 Research Method 137
3.1 Questionnaire Design 138
3.2 Data Collection and Respondents 139
3.3 Data Analysis 139
4 Survey Results 141
5 Discussion 142
6 Conclusion 146
References 147
3D Avatar Platforms: Tomorrow's Gateways for Digitized Persons into Virtual Worlds 150
1 Introduction 150
2 Background 152
3 CeBIT 2017 Avatar Platform Showcase 156
4 3D Avatar Platform Generalization 159
5 Conclusion 162
References 163
Automated Processing of Planning Modules in Factory Planning by Means of Constraint Solving Using the Example of Production Segmentation 165
1 Introduction 165
2 State of the Art 167
3 Constraint Solving in a Modularized Planning Approach 169
4 Scenario: Parts Family Formation and Cluster Analysis as Part of Production Segmentation 170
5 Constraint Solving Basics 171
6 Software Architecture 172
7 Summary and Outlook 177
References 178
A Digital Fabrication Infrastructure Enabling Distributed Design and Production of Custom Furniture 181
1 Introduction 181
2 Digital Manufacturing in the Furniture Sector 183
3 A Digital Manufacturing Infrastructure for the Production of Mass-Customized Furniture 184
3.1 Overall Architecture 184
3.2 Data Management and Production Flow 186
3.3 The Gateway Data Model 187
3.4 Order Acquisition Process 189
4 Scalability of the Implementation Scenarios 191
4.1 Implementing the IT Infrastructure in a Shopping Mall 192
4.2 The Mini-factory Organization and Customer Experience 192
4.3 Assessing the IT Infrastructure Implementation 195
5 Conclusions 196
References 197
Mass Customization 4.0 in AEC: Additive Manufacturing for Innovative Building Systems 199
1 The New Conditions for Mass Customization 4.0 in AEC 199
2 Innovation Drivers for AEC 201
3 Experimentation on Design for Fabrication with Additive Manufacturing 202
3.1 Functionally Graded Lattice Structures 203
3.2 Additive Moulding for Complex Casting 207
4 What If: Conditions for a Wide Diffusion of Mass Customization with AM in AEC 209
References 210
Managing Customized and Profitable Product Portfolios Using Advanced Analytics 211
1 Introduction 212
2 Relevant Terminology 213
2.1 Product Portfolio Management 213
2.2 Advanced Analytics for Demand and Profitability Predictions 214
3 Related Work 216
3.1 Product Portfolio Management 216
3.2 Advanced Analytics 217
3.3 Knowledge Discovery Methodologies 218
4 Methodology Design 219
4.1 The Model Derivation Process 219
5 Conclusion and Future Work 221
References 222
Impacts of Industry 4.0 on the Specific Case of Mass Customization Through Modeling and Simulation Approach 225
1 Introduction 226
1.1 Problem Description 227
2 Research Questions 227
3 Conceptual Design 228
3.1 Conceptual Model Characteristics 228
3.2 Discrete Event Simulation Model 229
4 Simulation Model Development 232
5 Simulation Output Analysis 232
5.1 Simulation Methodology 234
5.2 Key Performance Indicators (KPIs) 234
5.2.1 Order Completion Time (OCT) 235
5.2.2 Waiting Time in Queues (WTQ) 236
5.2.3 Utilization Rate of Machines (UR) 236
5.2.4 Customer Satisfaction (CS) 238
5.3 Result Summary 240
6 Conclusion 241
References 242
Part III Mass Customization and Sustainability 243
Mass Customization and Personalization: A Way to Improve Sustainability Beyond a Common Paradox 244
1 Introduction 245
2 The Paradox of the Modern Society: Be Sustainable in the Wasteland 247
2.1 Trash and Waste 247
3 A Concrete Example of the Paradox: The Shoe Production, Use, Trash, and Waste 249
3.1 The Energy Waste for Unused Shoes 250
4 The Paradox Solution: Changing the Production Paradigm 250
4.1 The Mass Customization and Sustainability 251
5 Beyond the Paradox with Mass Customization Shoe Production 252
5.1 Further Change Through the Paradigm: From the “Consumer-Product” to the “Consumer-Producer” Relationship 253
6 Conclusion 255
References 256
Mass Customization and Environmental Sustainability: A Large-Scale Empirical Study 258
1 Introduction 258
2 Literature Review 259
2.1 Organizational Capabilities and Routines 259
2.2 Environmental Sustainability Management and Its Enabling Capabilities 260
2.3 Mass Customization and Its Enabling Capabilities 261
3 Hypothesis Development 262
3.1 Product Stewardship and Environmental Performance 262
3.2 Parts Commonalization and Environmental Performance 262
3.3 Synergies Between Parts Commonalization and Product Stewardship 263
4 Method 264
4.1 Data Description 264
4.2 Measures 264
5 Results 264
6 Conclusions 267
References 269
Opportunities and Challenges of Product-Service Systems for Sustainable Mass Customization: A Case Study on Televisions 272
1 Introduction 273
2 Mass Customization and Sustainability 274
3 Product-Service Systems 275
4 Product-Service Systems in Mass Customization 275
4.1 Opportunities for Sustainable Mass Customization Through PSS 276
4.2 Challenges of Sustainable Mass Customization Through PSS 279
5 Case Study: Television and Sustainable PSS in Mass Customization 282
5.1 Literature Review on Environmental Impacts of Television 282
5.2 Life Cycle Assessment and Comparative Scenarios 283
6 Discussion and Conclusion 288
6.1 Key Findings and Major Contributions 288
6.2 Limitations and Further Research 289
References 289
Effects of Mass Customization on Sustainability: A Literature-Based Analysis 292
1 Introduction 293
2 Related Work 294
2.1 Sustainability 294
2.2 Sustainability and Mass Customization 295
3 Methodology 297
4 Literature Analysis and Synthesis 298
4.1 Classification of Results 298
4.2 Synthesis of Effects 300
5 Discussion and Further Research 300
5.1 Discussion 300
5.2 Further Research 303
6 Conclusion 304
References 305
Exploring Drivers and Barriers for Sustainable Use of Resources: The Case of High-Tech Mass Customizers in the German TextileIndustry 308
1 Introduction 308
2 Theoretical Underpinnings 310
3 Research Design 311
3.1 Field Setting 311
3.2 Data Analysis 312
4 Findings 312
4.1 Drivers 313
4.2 Barriers 315
5 Discussion and Conclusion 316
Appendix I: Data Supporting Interpretations of Second-Order Themes 318
References 319
A Preparatory Approach to Environmental Assessment for Sustainable Mass Customization 321
1 Introduction 322
2 Background 322
2.1 Environmental Assessment Methods 322
2.2 Mass Customization 323
2.3 Mass Customization and Sustainability 325
2.4 Requirements for Environmental Assessment Methods in the Context of Mass Customization 326
3 SMC Excel Sustainability Approach (SESA) for the Environmental Assessment of Sustainable Mass Customization 327
3.1 Scope and Methodology of the SMC Excel Sustainability Approach (SESA) 329
3.2 Data Collection and Assumptions 332
4 Comparative Validation of SESA with a Full-Scale LCA 338
5 Know-How and Communication 339
6 Conclusion 340
6.1 Key Findings and Major Contributions 340
6.2 Limitations and Further Research 340
References 341
Part IV Choice Navigation and Customer Interactions for MCP 344
The Importance of Choice Navigation in Starting ConfiguratorProjects 345
1 Introduction 345
2 Research Context and Methods 347
3 Designing Choice Navigation 348
3.1 Choice Navigation 348
3.2 Existing Process Model for Product Configurator Development 349
3.3 Success Factors and Pitfalls for Configurator Projects 351
4 Proposed Framework for Designing Choice Navigation 352
5 Empirical Data from Applying the Framework 354
6 Common Traits and Challenges 356
7 Discussion 356
8 Conclusion 358
References 359
User Interface Trends for Mobile-Optimized Product Configurators 361
1 Introduction 361
2 Relevance of Mobile Optimization for Configurators 362
2.1 Status Quo of Mobile Usage in General 362
2.2 Millennials as Potential Customer Group 363
2.3 Relevance and Experience of Online Customization by Millennials 364
2.4 Importance of Mobile Customization by Millennials 365
3 Empirical Analysis 365
3.1 Research Aims 365
3.2 Status Quo of Online Product Configurators Regarding Mobile Optimization 366
3.3 Method and Setting 367
4 Results and Key Findings 368
4.1 Quantitative Data Evaluation Within the Apparel Industry 368
4.2 Qualitative Data Evaluation Classification of User Interface Design 371
4.3 Premise of the Analysis 373
5 Conclusion and Outlook 374
Appendix 375
References 377
An Evaluation Model for Web-based 3D Mass Customization Toolkit Design 378
1 Introduction 378
2 Literature Review 379
2.1 Solution Space 380
2.2 Interaction Design 381
2.3 Enabling Technologies: 3D Modelling and Web Technologies 382
2.4 Individual Differences 383
3 A Model for Evaluating Web-Based 3D Mass Customization Toolkits 384
3.1 Solution Space Design 384
3.2 Interaction Design 385
3.3 3D Modelling and Web Technologies 385
3.4 Individual Differences 387
4 A Heuristic Evaluation of Online 3D Toolkits 387
5 Conclusion and Future Work 389
References 391
Front-End/Back-End Integration in Mass Customization: Challenges and Opportunities 394
1 Introduction 395
2 Methodological Considerations 395
3 Research Framework 396
4 Challenges and Opportunities of Integration 398
4.1 Solution Space and Product Development 399
4.2 Choice Navigation 400
4.3 Back-End Systems 402
4.4 Visual Factory 403
5 Discussion and Conclusion 404
References 406
Design and Development of the CEM-Dashboard: A Diagnostic Tool to Determine Your Current Position and Improvement Directions in Customer Experience Management 407
1 Introduction 408
2 Research Design and Method 409
3 Research Process Results 410
3.1 Step 1: (Initial) Literature Review 410
3.2 Step 2: Survey on CEM Implementation in Dutch Organizations 411
3.3 Step 3: Interviews 411
3.4 Step 4: Additional Literature Research 412
3.5 Step 5: Tool Design 415
3.6 Step 6: Design Validation 418
4 Discussion 420
5 Conclusion 421
References 421
Product Configuration in the ETO and Capital Goods Industry: A Literature Review and Challenges 424
1 Introduction 424
2 Research Method 426
3 Challenges for Product Configuration in ETO and Capital Goods Industries 428
3.1 Product Characteristics Are Gradually Determined Over Time 428
3.2 Long Order Horizons Increase Product Demand Mix Uncertainties 428
3.3 Product Configurator Drives Supply Chain Activities 429
3.4 High Product Complexity and Comprehensive Product Variations 430
3.5 Solutions Outside the Configurable Solution Space Are Required to a Large Extent 430
4 Solutions for Product Configuration in the ETO Industry 431
4.1 Comprehensive Solutions Covering Multiple Challenges 431
4.2 Specific Solutions Focusing on the Individual Challenges 432
4.3 Solution Review Summary 434
4.4 Research Gap 435
5 Conclusion 435
References 437
The Individualization of Mass Customization: Exploring the Value of Individual Thinking Style Through Consumer Neuroscience 440
1 Introduction 441
2 That Holy Grail, Loyalty 441
3 Individual Thinking Style and the MC Consumer Experience 442
4 Individual Differences and Thinking Style in Neuroscience 443
5 Individualization and Mass Customization: Like 23andMe? 445
6 Limitations 447
7 Theoretical and Managerial Implications 447
8 Conclusions and Future Research 448
References 449
User Interface Modifications in Established Product Configurators 452
1 Introduction 452
2 The Product Configurator Landscape 453
2.1 Status Quo of Web-Based Product Configurators 453
3 Empirical Analysis 457
3.1 Research Aims 457
3.2 Method and Setting 457
4 Results and Key Findings 459
4.1 User Interface Changes of Product Configurators from 2015 to 2016 459
4.2 User Interface Changes of Car Configurators 460
4.3 Premise of the Analysis 463
5 Summary and Outlook 464
Appendix 465
References 466
Part V Solution Space Development and Variety Management 468
Data-Driven Product Family Modeling with Feedback 469
1 Introduction 469
2 Methods 471
3 Review of Current Product Family Modeling Methods 472
4 Potentials in Data-Driven Family Modeling 473
4.1 Product Configuration Process 474
4.2 Part Production 475
4.3 Assembly 475
4.4 Usage 476
5 Conclusions and Future Work 476
References 477
Production Platform Development Through the Four Loopsof Concern 479
1 Introduction 479
2 Background 481
2.1 Architecture Descriptions 481
2.2 Platform Descriptions 482
3 Four Loops of Concern 484
3.1 Loop 1: Creating a Functional View 486
3.2 Loop 2: Creating a Core Technology View 487
3.3 Loop 3: Creating a Core Platform View 487
3.4 Loop 4: Creating a Domain Platform View 488
4 Case Studies 489
4.1 Scope 490
4.2 Implications 490
5 Discussion 491
References 492
Integrate Customer Order Decoupling Point and Mass Customisation Concepts: A Literature Review 494
1 Introduction 495
2 Research Methodology 497
3 The Customer Order Decoupling Point: What, How and Why 499
3.1 Descriptive Analysis 499
3.2 What 502
3.3 How 504
3.4 Why 505
4 The Mass Customisation Strategy: What, How and Why 506
5 Integration of MC and CODP Concepts 508
6 Discussion and Conclusions 509
References 513
Mass Customization in Food Industries: Case and Literature Study 517
1 Introduction 518
2 Research Method 519
3 Literature Study 520
3.1 Food Manufacturing Processes 520
3.2 Product Configuration 521
3.3 Supply Chain 521
3.4 Findings 522
4 Case Study 522
4.1 Solution Space Development 523
4.2 Robust Process Design 524
4.3 Choice Navigation 525
5 Conclusion 526
References 526
Can the SME Successfully Adopt Mass Customization? 528
1 Introduction 528
2 SME Definition and Characteristics 531
3 Research Design 533
4 Findings 535
4.1 Environment 535
4.2 Design, Internal, and External Integration 537
4.3 Organizational, Manufacturing, and Quality Action Programs 539
5 Conclusions and Further Research 542
References 544
Productivity, Challenges, and Applying Mass Customization in the Building and Construction Industry 547
1 Introduction 547
2 Productivity Trend Similarities 549
3 Challenges in the Building and Construction Industry 553
4 Applying Mass Customization 555
5 Conclusion 559
References 560
Flexibility in Mass Customization of Houses 562
1 Introduction 562
2 Housing Industrialization 563
3 Mass Customization Space in the Housing Industry 564
3.1 Design Space 565
3.2 Customization Space 566
3.3 Manufacturing Space 569
4 Challenges 571
5 Conclusion and Future Research 572
References 573
Product and Service Variety Versus Internal Performance: Toward New Balances 576
1 Introduction 576
2 Literature Review 577
2.1 Research Methodology 577
2.2 Conceptual Framework 577
2.2.1 MC Rationale and Capabilities 578
2.2.2 External and Internal Varieties 578
2.2.3 Standardization and Flexibility Oxymoron 579
2.2.4 Modularity and Commonality 579
2.2.5 Customer Satisfaction 580
2.3 Systematic Literature Review 580
3 A Reference Model for Variety Management 582
3.1 Products and Services Mass Customization (PSMC) Capabilities 582
3.2 Variety Management Drivers 583
4 Discussion and Research Perspectives 585
5 Conclusion 586
References 587
Validation of Metrics for Mass Customization: A Pre-study of Validation Methods 590
1 Introduction 590
2 Research Approach 591
2.1 Validation Methods 591
2.2 Case Study Design 593
3 Results and Findings 594
4 Conclusion 595
References 595
Teaching Solution Space Development: Experiences from the Hanover Knowledge-Based-Design-Lab 597
1 Introduction 597
1.1 Motivation 598
1.2 Structure of the Paper 598
2 Knowledge-Based-Design in TU9 Curricula 599
3 A Review of Problem-, Project-, and Case-Based Learning 600
4 The Hanover Knowledge-Based-Design-Lab 601
4.1 Educational Objectives 601
4.2 Course of Action 602
4.3 Spreadsheet-Driven Design and iLogic 602
4.4 Achievements 606
5 Summary and Outlook 607
References 608
Part VI Mass Customization of Textiles and Fashion Products as a Special Field of Application 610
Fashion Apparel Industry 4.0 and Smart Mass Customization Approach for Clothing Product Design 611
1 Fashion Apparel Industry Faces Disruption from Outside 612
1.1 Fashion Apparel Industry 4.0 Challenge 612
1.2 Mass Customization Approach 613
2 Literature Reviews 614
2.1 The Increase in Purchase Returns 615
2.2 Smart Configuration for Clothing Product Design 617
3 Methodology 619
4 Results Analysis 621
5 Discussion 623
6 Conclusion 623
References 624
Individual On-Demand Produced Clothing: Ultrafast Fashion Production System 626
1 Introduction 626
2 Concept Description and Requirements 628
3 Thermosetting 630
4 Converter Unit 630
5 Results of the Analysis: Comparison of Local Production and Conventional Production 631
6 Conclusion 634
References 634
myShopNET: Personalized Consumer Goods e-Commerce Platform 636
1 Introduction 636
1.1 COSME: Design-Based Consumer Goods Call 636
1.2 The Consortium 637
1.3 Problem and Solution 638
2 Business Context 639
2.1 Personalizable Design-Driven Consumer Goods Market 639
2.2 Platform Clients 640
3 myShopNET Platform 640
3.1 myShopNET Conceptual Model 640
3.2 myShopNET Architecture Design 641
3.3 Co-design Tool 643
3.4 Smart Sizing Tool 643
3.5 Visualization as a Service 644
4 Discussion and Conclusions 645
References 646
Mass Customization Practices of Malaysian SMEs Apparel Sector: An Exploratory Survey 647
1 Introduction 648
1.1 A Subsection Sample 648
2 Literature Review 649
2.1 Overview of Malaysian SMEs Apparel 649
2.2 The Advantages of Mass Customization Implementation in Small and Medium Enterprises (Apparel Sector) 650
2.3 Mass Customization Readiness 651
3 Research Framework 653
4 Methodology and Data Analysis 653
5 Result and Discussions 655
6 Future Direction 655
References 656
Attitudes Toward Apparel Mass Customization: Canadian Consumer Segmented by Lifestyle and Demographics 660
1 Introduction 661
2 Literature Review 662
2.1 Attitudes 662
2.2 Willingness 662
2.3 Consumer Segmentation 663
2.4 Summary 664
3 Research Method 664
4 Data Analysis 665
4.1 Participants' Multilayer Segmentation 665
4.2 Consumer Attitude 666
4.3 Willingness 668
5 Conclusion 671
References 672
Erratum to: Customization 4.0:Proceedings of the 9thWorld MassCustomization & PersonalizationConference (MCPC 2017), Aachen,Germany, November 20th-21st, 2017
Name Index 675
Subject Index 677