كتاب Mass Customization - Engineering and Managing Global Operations
منتدى هندسة الإنتاج والتصميم الميكانيكى
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منتدى هندسة الإنتاج والتصميم الميكانيكى
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 كتاب Mass Customization - Engineering and Managing Global Operations

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مُساهمةموضوع: كتاب Mass Customization - Engineering and Managing Global Operations    كتاب Mass Customization - Engineering and Managing Global Operations  Emptyالإثنين 10 أبريل 2023, 9:22 pm

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Mass Customization - Engineering and Managing Global Operations
Flavio S. Fogliatto , Giovani J.C. da Silveira
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كتاب Mass Customization - Engineering and Managing Global Operations  M_c_e_14
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Contents
Part I Mass Customization Contexts
1 Designing and Planning for Mass Customization in a Large Scale
Global Production System 3
Roberto F. Lu and Richard L. Storch
1.1 Introduction . 4
1.2 Literature Background . 5
1.3 Methods and Analysis . 8
1.4 Case Study . 20
1.5 Conclusion . 22
References . 23
2 Process Typology of Mass Customizers 29
Rebecca Duray
2.1 Introduction . 29
2.2 Mass Customization and the Product Process Matrix 30
2.2.1 Defining the Product Process Matrix . 30
2.2.2 Strategy of the Diagonal 33
2.2.3 Defining Made-to-order . 34
2.2.4 The Paradox of Mass Customization . 35
2.3 Defining Mass Customization . 35
2.4 Developing the New Model – Volume, Variety, and Variation 37
2.4.1 Volume and Variety . 37
2.4.2 The Third Dimension – Variation 39
2.5 Future Directions . 42
2.6 Conclusion . 43
References . 43xii Contents
3 Service Customization Through Dramaturgy 45
Ian P. McCarthy, Leyland Pitt, and Pierre Berthon
3.1 Introduction . 46
3.2 Background . 47
3.2.1 Customization of Service Operations . 48
3.2.2 Typology Dimensions: Time Pressure to Customize
and Level of Customization Required 49
3.2.3 Dramaturgy 50
3.2.4 The Service Performance: Scripts and Improvisation 52
3.3 A Typology of Service Customization Configurations . 54
3.3.1 Embellished Customization . 55
3.3.2 Predetermined Customization 56
3.3.3 Prompt Customization 57
3.3.4 Intuitive Customization 57
3.4 Discussion and Implications 59
3.4.1 Configuration Fit 59
3.4.2 The Lure of the Diagonal . 60
3.4.3 Global Services and Customizing the Performance . 60
3.5 Conclusion . 61
References . 62
Part II Engineering and Management of Mass Customized Products
4 NPD-SCM Alignment in Mass Customization . 69
Nizar Abdelkafi, Margherita Pero, Thorsten Blecker,
and Andrea Sianesi
4.1 Introduction . 71
4.2 Literature Background . 72
4.2.1 NPD-SCM Alignment 72
4.2.2 Mass Customization . 73
4.3 Aligning NPD and SCM in Mass Customization 75
4.3.1 Innovativeness and Dynamic Variety 77
4.3.2 Supply Chain Configuration, Collaboration,
and Coordination Complexity 78
4.3.3 Supply Chain Performance 78
4.3.4 Alignment Framework and Propositions 79
4.4 Conclusions . 83
References . 84Contents xiii
5 Managing Technological Innovations Affecting Product
Complexity, Modularity, and Supply Chain Structure . 87
Adrian E. Coronado Mondragon and Christian E. Coronado Mondragon
5.1 Introduction . 88
5.2 Modularization, Customization, and Technological
Innovations in the Automotive Industry 91
5.3 Modularity and Mass Customization in Motor Coaches
and Transit Buses 93
5.4 Methodology . 95
5.5 Modular Systems Development for Motor Coaches/
Transit Buses (Heavy Duty Vehicles) . 97
5.6 Findings . 98
5.6.1 Control of Product Architecture . 98
5.6.2 Autonomy of Suppliers 98
5.6.3 Sources of Innovation 99
5.7 Conclusions . 101
Appendix 102
References . 103
6 The Platform Formation Problem . 105
David Ben-Arieh
6.1 Introduction . 106
6.2 Background . 107
6.3 Problem Description 109
6.3.1 The Single Platform Design Formulation 112
6.3.2 The Multiple Platform Problem . 112
6.3.3 Single Platform Design under Stochastic Demand
Problem 114
6.4 An Illustrative Example . 117
6.5 Conclusion and Recommendations for Future Research . 121
References . 122
7 Shape Commonalization to Develop Common Platforms
for Mass Customization 125
Sagar Chowdhury and Zahed Siddique
7.1 Introduction and Background 126
7.2 Literature Review 127
7.2.1 Product Platform 127
7.2.2 Similarity Measurements . 128
7.3 Method . 130
7.3.1 Step 1: Extraction of Information from 3D Models . 131
7.3.2 Step 2: Common Platform Development . 133xiv Contents
7.4 Case Studies 141
7.4.1 Case Study 1 – Cell Phone Casings Product Platform . 141
7.4.2 Case Study 2 – Coffeemaker Product Platform 144
7.5 Concluding Remarks . 148
References . 149
8 A Platform Identification Method for Service Family Design
Using a Process Model and a Clustering Method 151
Seung Ki Moon, Timothy W. Simpson, Jun Shu,
and Soundar R.T. Kumara
8.1 Introduction and Background 153
8.2 Method for Service Module and Platform Identification . 154
8.2.1 Phase 1: Service Analysis and Model 155
8.2.2 Phase 2: Service Ontology . 158
8.2.3 Phase 3: Module and Platform Identification . 160
8.3 Case Study . 162
8.3.1 Phase 1: Service Process Model . 163
8.3.2 Phase 2: Service Ontology . 164
8.3.3 Phase 3: Module and Platform Identification . 167
8.4 Closing Remarks and Future Work . 169
References . 169
9 A STEP-compliant Online Product Digital Library
for Customized Products 171
S.Q. Xie
9.1 Introduction . 172
9.2 Literature Review 173
9.3 System Architecture 175
9.4 STEP-compliant Product Digital Library 177
9.4.1 Product Knowledge Model 178
9.4.2 Product Data Object . 179
9.5 Case Study . 180
9.5.1 Modeling Product Inspection Information . 181
9.5.2 Online Product Digital Library 183
9.5.3 Modeling Product Manufacturing Process Data 186
9.5.4 Modeling Product Assembly Information Data . 187
9.5.5 Discussion 189
9.6 Conclusion and Future Work . 190
References . 191Contents xv
Part III Engineering and Management of Processes
for Mass Customization
10 Production Planning and Control for Mass Customization –
A Review of Enabling Technologies 195
Mitchell M. Tseng and Andreas M. Radke
10.1 Introduction . 196
10.2 Enabling Framework for MC Production Planning and Control . 200
10.3 Enablers for Mass Customization 202
10.3.1 Strategic Enablers in Product Design . 203
10.3.2 Strategic Enablers in Sales and Purchases . 205
10.3.3 Tactical Enablers in Product Design, Sales,
and Purchases . 207
10.3.4 Strategic Enablers in Manufacturing 209
10.3.5 Tactical Manufacturing Enablers . 211
10.4 Conclusion . 213
References . 214
11 Designing and Planning of Material Handling Systems
for Mass Customization 219
Neville K.S. Lee and James B. Dai
11.1 Introduction . 221
11.2 Designing and Planning Considerations on Material Handling
Systems for Mass Customization . 222
11.2.1 Different Flexible Material Handling Systems 222
11.2.2 The Designing and Planning of Flexible Material
Handling Systems 223
11.3 Industrial Application for the Apparel Industry 229
11.3.1 Existing Material Handling Systems
for the Apparel Industry . 229
11.3.2 System Layout Design . 232
11.3.3 Potential Advantages of the Free-ranging Material
Handling System 233
11.3.4 Economical Feasibility Analysis on Free-ranging
MHS . 237
11.3.5 Sensitivity Analysis on Adopting Automatic MHSs 242
11.4 Conclusion . 243
References . 244
12 Design for Changeover (DFC): Enabling Flexible
and Highly Responsive Manufacturing . 247
G.W. Owen, J. Matthews, R.I. McIntosh and S.J. Culley
12.1 Introduction . 248
12.1.1 Change Drivers: Forces to Change
Manufacturing Systems 249xvi Contents
12.1.2 The Nature of Uncertainty . 249
12.1.3 Changeover Assisting Business Response
to Uncertainty . 250
12.2 Modern Manufacturing Paradigms 251
12.3 DFC: Problem Definition and Background . 254
12.4 An Outline of the University of Bath DFC Methodology . 255
12.4.1 A Deliberate Avoidance of the Identification
of Individual Changeover Tasks 257
12.4.2 The Concepts of Resources and Change Elements 257
12.4.3 The Concept of Interfaces 258
12.4.4 Further Description of Change Elements . 258
12.4.5 DFC Indices and DFC Design Rules . 259
12.4.6 The Design Infringement Matrix . 260
12.4.7 The Concept of a Complexity Quotient . 261
12.4.8 Change Drivers 262
12.4.9 Design Improvement Opportunities . 262
12.4.10 Mapping the DFC Indices and the DFC Design Rules . 263
12.4.11 Presenting Summary Information to the Designer . 264
12.5 Industrial Validation: A Case of Study 265
12.5.1 A Brief Description of the Game . 265
12.5.2 Value Adding Stages 266
12.5.3 Target Indices to Achieve 266
12.5.4 Raising the Capability Index 266
12.5.5 Resource Restrictions – Raising Merit Index 3 267
12.5.6 Change Element Restrictions – Raising
Merit Index 4 268
12.5.7 Altered Sequence Restrictions – Raising Merit
Index 5 . 269
12.5.8 Further Industrial Validation 269
12.6 Discussion . 269
12.7 Conclusions . 270
References . 271
13 Additive Manufacturing for Mass Customization . 275
Phil Reeves, Chris Tuck and Richard Hague
13.1 Introduction and Background 276
13.2 AM and the Realization of Mass Customized Internet Content 279
13.3 The Integration of Additive Manufacturing with Computer
Games 281
13.4 Poachers and Gamekeepers . 284
13.5 The Future . 285
13.6 Implications of AM for MC Businesses and Future Research . 287
13.7 Summing Up 287
References . 288Contents xvii
14 Selecting Relevant Clustering Variables in Mass Customization
Scenarios Characterized by Workers’ Learning . 291
Michel J. Anzanello
14.1 Introduction and Background 292
14.1.1 Learning Curves . 293
14.1.2 Clustering Analysis and the Silhouette Index 294
14.2 Method . 296
14.2.1 Step 1 . 296
14.2.2 Step 2 . 297
14.3 Numerical Case . 298
14.4 Conclusion . 302
References . 303
15 Re-examining Postponement Benefits: An Integrated
Production-inventory and Marketing Perspective . 305
Hartanto Wong and Mohamed Naim
15.1 Introduction . 306
15.2 Literature Background . 309
15.2.1 Postponement to Accommodate Mass Customisation . 309
15.2.2 Production-inventory and Marketing Coordination . 310
15.3 The Models 311
15.3.1 Description of Manufacturing Configurations . 311
15.3.2 The Marketing Model 314
15.3.3 The Production-inventory Model . 317
15.3.4 The Integrated Model . 318
15.4 Analyses 319
15.4.1 Cost Minimisation Versus Profit Maximisation . 320
15.4.2 The Impact of Postponement on Profitability 322
15.5 Conclusions . 326
References . 329
Part IV Mass Customization: Case Studies
16 User Participation Within Virtual Worlds . 333
Andreas M. Kaplan
16.1 Introduction: From Traditional via Electronic to Virtual Mass
Customization 334
16.2 Literature Background: About Virtual Worlds and Virtual
Mass Customization 335
16.2.1 Virtual Worlds Are a Special Type of Social Media 335
16.2.2 Virtual World Does Not Equal Virtual World . 336
16.2.3 Second Life Is the Most Prominent Virtual World 337xviii Contents
16.2.4 Second Life Is Not a Game but an Extension
of Real Life 338
16.2.5 Second Life Offers Several Opportunities
for Virtual Mass Customization . 339
16.3 Analyses and Propositions: Dell, Philips, and Sears
as Pioneers of Virtual Mass Customization . 340
16.3.1 Dell: Virtual Mass Customization of RL Products 341
16.3.2 Philips: Understanding the Consumer First,
Then Integrating Him in the Design Process . 342
16.3.3 Sears: Too Much or Not Enough Reality
for a Virtual World? . 343
16.3.4 Key Insights and Lessons: Huge Potential –
Just Not Yet 345
16.4 Conclusion: Virtual Kills the Internet Star? 347
References . 349
17 Contrasting Opportunities for Mass Customisation in Food
Manufacture and Food Processes 353
Jason Matthews, Richard McIntosh and Glen Mullineux
17.1 Introduction . 354
17.2 Research Background 355
17.3 Contemporary Goals for a Manufacturing Organisation . 357
17.3.1 Management of Cross-domain Interaction . 357
17.3.2 Management of Customer Relationships . 358
17.4 Prominent Techniques of Mass Customisation . 358
17.4.1 Manufacturing Flexibility 358
17.4.2 Modularity 359
17.4.3 Postponement . 360
17.5 Case Study Investigations 360
17.5.1 Case Study Processes . 361
17.5.2 Potential for the Application of Mass Customisation 363
17.6 Food and Drinks Manufacturing Constraints . 365
17.6.1 Product Related Constraints . 366
17.6.2 Operation Related Constraints . 367
17.6.3 System Related Constraints 368
17.7 Discussion and Opportunities 368
17.7.1 Packaging and Labelling 370
17.8 Conclusions . 372
References . 372
Index .
Index
A
Additive manufacturing (AM), 276, 277,
280, 281, 283–287
Agility, 6, 202, 205, 249, 254
Analysis of variance (ANOVA), 12
Apparel industry, 220–222, 226, 229–233,
236, 243, 244
application programming interface (API),
149
Application programming interface (API),
132, 149
Assembled-to-order, 34–36, 41, 204
Automotive industry, 74, 81, 83, 87,
90–93, 101, 206, 339
Avatars, 283, 284, 334, 336–349
average assembly platform commonality
index (AAPCI), 140, 148
Average assembly platform commonality
index (AAPCI), 148
B
Batter base puddings, 360
Bill of materials, 108, 110, 204, 211, 228
Bill of materials and operations (BOMO),
205
C
Change drivers, 249, 250, 252, 262, 271
Change elements, 248, 257–259, 262–270,
339
Changeover, 209, 213, 247–255, 257–262,
264–271, 312, 313, 357, 359, 368
Changeoverability, 253, 270, 271
Clustering tools, 292
Collaboration, 70, 78, 80–83, 92, 149,
205, 208, 271
Commercial airplane, 4, 8, 14, 15, 22
Complexity, 7, 11, 78, 80–82, 84, 87, 221,
261, 265, 266, 278, 292, 296, 299, 300,
359, 367
Component commonality, 127, 141, 149,
203, 210
Computer aided design (CAD), 172, 276
Computer Aided Design (CAD), 353
Computer aided process planning (CAPP),
172
Computer integrated manufacturing (CIM),
174
Configuration overload, 207
Configurator, 206–208, 214
Coordination, 30, 70, 72, 78, 80, 82, 83,
91, 307, 308, 310, 311, 327
Customer introduction, 15–17
Customer involvement, 35–37, 155
Customer requirements and expectations,
171, 175
D
Data mining, 152–155, 169
Dell, 335, 338, 340–343, 345–348
Demand reshaping, 208, 211
Demand uncertainty, 82, 105, 121, 205
Demand variability, 73
Design by customer (DBC), 207
Design By Customer (DBC), 207
Design for, 72, 73, 153, 175, 200, 204,
247, 249, 254, 257, 277, 286, 357, 368
Design For Changeover (DFC) rules, 254376 Index
Design rules, 71, 73, 259, 263, 264,
270, 356
DFC design rules, 259, 263, 264, 270
Dimensional commonality indices,
133, 144
Direct digital manufacturing, 277
Dramaturgy, 45–53, 58, 60, 62
Dynamic bill of materials, 228
E
Economic feasibility analysis, 220, 237
Efficiency, 4, 7, 56, 73, 75, 78, 79, 83, 93,
95, 196, 199, 224–226, 229, 243, 291,
293, 296, 302
E-manufacturing, 277
Embellished customization, 46, 47, 55, 56
Enabling technologies, 171, 195, 199
Engineered-to-order, 34, 36, 40, 41
EXPRESS data model (EDM), 176
External change drivers, 250
F
Feature manager design tree, 132
Final delivery, 39
Finite capacity planning, 196, 211
Fixed-track MHS (material handling
system, 221
Fixed-track MHS (material handling
system), 237, 239–243
Flexibility, 31–33, 49, 58, 71, 83, 88, 91,
102, 153, 201, 204, 205, 208, 211, 214,
224, 231, 249–253, 311, 323, 327, 354,
357, 358, 363, 370
Flexible manufacturing, 35, 204, 205, 209,
210, 212, 218, 219, 221, 222, 234,
248, 251
Flexible manufacturing system, 212, 221
Flexible material handling system, 219,
221, 229
Flexible supply chain, 205
Food industry, 353–357, 359, 365, 366,
368, 370
Food processing, 354, 356, 357, 368, 371
Food products, 354, 356, 359, 365,
367–369, 372
Free-ranging automated guided vehicle,
219
Fuzzy clustering, 152, 160, 167
Fuzzy c-means clustering, 154, 160, 169
G
Generic Bill Of Materials (GBOM), 204
H
Hierarchical approach, 139, 149
High product proliferation, 219, 236,
242, 243
I
Improvisation, 46, 51–54, 56–61
Innovation toolkits, 201, 208
Innovativeness, 70, 77, 80, 81, 83, 347
Integration, 4, 6–8, 10, 11, 19, 82, 83,
91–93, 100–102, 129, 172, 174, 175,
189, 190, 203–205, 209–213, 281, 307,
341, 343, 345, 348
Internal change drivers, 250
Intuitive customization, 46, 47, 57
J
Just-in-time, 58, 199, 307, 368
K
K-means clustering technique, 291–293,
303
L
Learning curve, 19–22, 291–293
Learning rate, 6, 291–294, 296, 297,
300, 302
Linden Dollar, 336, 338, 340, 342
Linden Lab, 280, 336, 338
Linear regression, 12, 19, 297
Local positioning system (LPS), 220,
227, 232
Logistics, 4, 6, 8–10, 17, 19, 75, 78, 108,
210, 252, 253, 307, 309, 355
M
Made-to-order, 34
Management, 5, 10, 32–34, 36, 39, 43,
45–51, 53, 54, 56, 59, 70, 71, 74–76,
82, 87, 88, 90–93, 95, 96, 99–101, 108,
121, 178, 183, 200, 206, 209–211, 213,
306, 328, 357–361
Manufacturing flexibility, 49, 354, 358,
363, 370Index 377
Manufacturing system effectiveness,
224, 234, 244
Mass production, 4, 15, 29, 35, 73, 95,
106, 110, 115, 196, 237, 285, 298, 307,
311, 321, 362, 371
Massively multiplayer online role-play
games (MMORPG), 276
Master schedule, 12
Minimum cost, 105
Mixed model assembly line, 39, 41
Modular architecture, 74, 80, 87, 89, 91,
93, 94, 96, 99–101
Modular design, 36, 74, 91, 92, 154,
159, 203
Modular product design, 36, 203
Modularization characteristic curve, 203
Monte Carlo, 11, 14, 220, 233, 244
Multiple platforms, 105, 121
N
New product development (NPD), 11, 70,
71, 90, 277
New Product Development (NPD), 89
Number of clusters, 161, 167, 293,
295–298, 300, 303
O
Object-oriented concepts, 152–157, 169
Ocean vessel, 22
Ontology, 154, 155, 158, 160, 162,
164, 168
Operational improvement practices, 202
Optimal platform, 107, 121
P
Packaging, 75, 284, 306, 309, 356, 357,
360, 362–365, 368, 370, 371
Performance, 4–6, 11, 16, 17, 43, 45–51,
53, 55–60, 62, 71, 72, 76, 77, 79, 82,
88, 89, 91, 98, 102
Platform indices, 139
Platform strategy, 106, 121
Positional commonality indices, 135
Postponement, 73, 83, 87, 88, 202, 205,
209, 210, 214, 287, 305, 307–311, 313,
319–328, 354, 355, 357, 358, 360, 364,
365, 367, 370, 372
Potato crisps, 360, 362, 364, 365
Process commonality, 204, 213
Process lifecycle, 30, 37
Process selection, 204
Process variation, 37, 39, 40
Product architecture, 72, 74, 77, 80, 88,
90–92, 97, 98, 100, 107
Product complexity, 85, 87, 88, 95, 292
Product data object, 179
Product database, 183–185, 188
Product development process, 106,
171–173, 179, 189
Product digital library, 171, 173, 176, 177,
180, 183, 190
Product family, 11, 74, 105–109, 121,
127, 128, 153, 154, 203
Product inspection information,
181, 183, 184
Product knowledge model, 178–180, 190
Product life cycle, 6, 31, 37, 108
Product modeling, 173–175, 191
Product platform, 74, 99, 106–109, 125–
128, 141, 144, 203
Product process matrix (PPM), 30, 32, 34,
35, 37, 41, 43
Product related constraints, 366
Product variant, 74, 105, 106, 127, 198,
308, 311–313, 320, 321, 323, 326, 328
Product variety, 31, 41, 76, 83, 88, 89, 91,
99, 127, 196, 197, 199, 205, 207, 213,
243, 251, 252, 271, 306, 308, 320, 321,
327, 359
Production planning and control,
195, 199, 221
Proliferation, 71, 82, 196, 204, 219, 221,
236, 242–244, 306, 307, 313, 319,
320, 322
Prompt customization, 5, 15, 20
R
Rapid manufacturing, 277
Reconfigurability, 249, 253, 359
Restaurant, 47, 51, 53, 57
S
Scheduler, 202, 213
Scripts, 46, 47, 51–53, 56–61
Second Life (SL), 280, 282, 333–349
Service component, 154, 156, 157, 164
Service design, 155–157, 160, 168
Service family, 152, 153, 155, 156, 159,
162, 168
Service function, 154, 156, 159, 162,
164, 168
Service module, 154, 159
Service platform, 152–154, 168378 Index
Service process, 152, 154–157, 159–161,
163, 164, 169
Service process model, 152, 154, 157,
164, 169
Shape commonality, 125, 133, 148
Shoe manufacturing, 291, 293, 298, 303
Silhouette index (SI), 291–297, 303
Simulation, 3, 5, 6, 11, 12, 14, 19–22, 176,
204, 220, 233–235, 244
Single minute change of die (SMED),
254, 255, 263, 265
Single platform, 105, 107, 111, 112, 114
Small and medium-sized manufacturing
enterprises (SMEs), 171
Social media, 335
Software tools, 174
SolidWorks, 131–133, 143, 146, 149
Standard for the exchange product model
data (STEP), 171
Statistical analysis, 20
STEP-compliant product knowledge,
184, 186, 190
Stochastic demand, 107, 114, 121
Strategy, 4, 8, 32, 33, 61, 71, 73, 78, 83,
89, 99, 105, 106, 121, 127, 155, 172,
200, 203, 211, 213, 307–310, 313,
319–321, 325, 327, 340, 341, 348,
349, 355
Supply chain, 4–11, 70–73, 75–78, 80–83,
88–92, 96–101, 128, 200, 201,
203–213, 252, 276, 280, 285, 287, 306,
307, 309, 322, 326, 355, 359
T
Technological innovations, 87, 89–92,
95–101
Theater, 51
Theatre, 344
Time pressure, 45, 47, 49, 53, 54, 56,
57, 59
Tracking ratio, 76
Transformability, 253
Typology, 29, 30, 36, 45, 47, 49, 50, 54,
55, 59, 60, 62
U
Unit production system, 229, 231
User innovation, 342
User participation, 333, 340, 348
V
Variable selection, 297
Virtual mass customization, 333, 335,
339–341
Virtual world, 280, 333–348
Volume-variety tradeoff, 33
Volume-variety-variation, 30, 42
W
WebATP (Available To Promise), 211
Y
Yoghurt, 360, 362–365, 371


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