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عدد المساهمات : 18962 التقييم : 35392 تاريخ التسجيل : 01/07/2009 الدولة : مصر العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى
| موضوع: كتاب Mass Customization - Engineering and Managing Global Operations الإثنين 10 أبريل 2023, 9:22 pm | |
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أخواني في الله أحضرت لكم كتاب Mass Customization - Engineering and Managing Global Operations Flavio S. Fogliatto , Giovani J.C. da Silveira Editors
و المحتوى كما يلي :
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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