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| موضوع: كتاب Process Planning and Scheduling for Distributed Manufacturing الخميس 30 مارس 2023, 6:29 am | |
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أخواني في الله أحضرت لكم كتاب Process Planning and Scheduling for Distributed Manufacturing Lihui Wang and Weiming Shen (Eds.)
و المحتوى كما يلي :
Contents List of Contributors xvii 1 An Effective Approach for Distributed Process Planning Enabled by Event-driven Function Blocks 1 Lihui Wang, Hsi-Yung Feng, Ningxu Cai, Wei Jin 1.1 Introduction 1 1.2 Brief Literature Review 2 1.3 Distributed Process Planning 5 1.3.1 Fundamentals of DPP . 5 1.3.2 Basic Requirements 6 1.3.3 System Architecture 7 1.3.4 Enabling Technologies . 8 1.4 Decision Solutions for Supervisory Planning . 11 1.4.1 EMF for Machining Process Sequencing . 11 1.4.2 EMF Grouping 14 1.4.3 EMF Sequencing 15 1.4.4 Function Block Design . 18 1.5 Setup Merging and Monitoring 22 1.5.1 Setup Merging 23 1.5.2 Detailed Operation Planning . 25 1.5.3 Function Block Execution Control and Monitoring . 26 1.6 Conclusions 27 References 28 2 Web-based Polishing Process Planning Using Data-mining Techniques 31 V.Y.M. Tsang, B.K.K. Ngai, G.Q. Huang, V.H.Y. Lo, K.C. Cheng 2.1 Introduction 31 2.2 Literature Review . 33 2.2.1 Research Works in Polishing 33 2.2.2 Web Application for Knowledge-based Planning 33 2.2.3 Case-based Reasoning 35 2.2.4 Fuzzy Modelling . 35 2.2.5 Genetic Algorithms . 36 2.2.6 GA-Fuzzy Systems . 36x Contents 2.3 Polishing Process Planning . 37 2.3.1 Purpose of Polishing Process Planning . 37 2.3.2 Design of Polishing Process Planning 38 2.4 Web-based Portal System for Polishing . 40 2.4.1 Problem Definition . 41 2.4.2 Objectives . 41 2.4.3 Design of Web-based Portal System . 42 2.4.4 Implementation of Web-based Portal System . 45 2.5 Knowledge-base Development Methodology 45 2.5.1 General Framework 45 2.5.2 Case Study 49 2.6 Results and Discussions 55 2.7 Conclusions 56 References 57 3 Integration of Rule-based Process Selection with Virtual Machining for Distributed Manufacturing Planning . 61 Dusan N. Sormaz, Jaikumar Arumugam, Chandrasekhar Ganduri 3.1 Introduction 61 3.2 IMPlanner Architecture 62 3.3 Knowledge-based Process Selection 64 3.3.1 Knowledge Representation . 64 3.3.2 Process Selection Rules 67 3.3.3 Knowledge Base/Database . 71 3.3.4 Integration of Rule Execution Engine into IMPlanner . 72 3.4 Virtual Machining of Milling Operations . 72 3.4.1 Geometric Model 73 3.4.2 Kinematic Model 74 3.4.3 Animation Model 76 3.4.4 Virtual Machining Scene Graph . 78 3.5 Integration Approaches . 80 3.5.1 Object Visualisation Paradigm . 80 3.5.2 Distributed Approach 81 3.5.3 Integrated Application 83 3.5.4 XML-based Web Distributed Application 83 3.6 Case Study 84 3.7 Related Research 87 3.8 Conclusions 88 References 89 4 CyberCut: A Coordinated Pipeline of Design, Process Planning and Manufacture 91 V. Sundararajan, Paul Wright 4.1 Introduction 91 4.2 Conventional Approach 92Contents xi 4.2.1 Manufacturing-dependent CAD Systems . 93 4.2.2 Bidirectionally Coupled CAD Systems 94 4.3 The CyberCut System . 95 4.3.1 Overview of the CyberCut System . 95 4.3.2 Definition of Features . 96 4.4 Architecture 98 4.4.1 WebCAD 99 4.4.2 Feature Recogniser . 99 4.4.3 Feature Validation 100 4.4.4 Macroplanner and Setup Planner 101 4.4.5 Microplanner 101 4.4.6 Tool-path Planner . 104 4.5 Implementation and Results . 104 4.6 Conclusions 106 References 107 5 Process Planning, Scheduling and Control for One-of-a-Kind Production . 109 Paul Dean, Yiliu Tu, Deyi Xue 5.1 Introduction 109 5.2 Literature Review . 113 5.3 Process Planning . 117 5.3.1 Long-term Process Planning . 117 5.3.2 Short-term Process Planning . 118 5.4 Process Control . 125 5.5 Adaptive Planning and Control 127 5.6 Long-term Resource Planning 131 5.7 Conclusions 134 References 135 6 Setup Planning and Tolerance Analysis . 137 Yiming (Kevin) Rong 6.1 Introduction 137 6.1.1 Current State-of-the-art . 138 6.2 Manufacturing Planning System . 140 6.2.1 Feature-based Part Information Modelling . 140 6.2.2 Feature Manufacturing Strategy . 143 6.2.3 Machine Tool Capability Modelling . 144 6.2.4 Setup Planning 144 6.2.5 Fixture Design in Computer-aided Manufacturing Planning 146 6.2.6 Manufacturing Plan Generation 147 6.3 Automated Setup Planning . 148 6.3.1 Graph Theory and Application in Setup Planning 150 6.3.2 Feature Tolerance Relationship Graph (FTG) 150 6.3.3 Datum and Machining Feature Relationship Graph (DMG) . 152xii Contents 6.3.4 Automated Setup Planning . 153 6.3.5 A Case Study 156 6.4 Information Modelling . 159 6.4.1 A Systematic Information Modelling Methodology . 159 6.4.2 Information Model of CAMP for Mass Customisation 161 6.5 Summary and Discussions 164 References 165 7 Scheduling in Holonic Manufacturing Systems . 167 Paulo Sousa, Carlos Ramos, José Neves 7.1 Introduction 167 7.2 Background 168 7.2.1 Holonic Systems . 168 7.2.2 Holonic Manufacturing Systems 169 7.3 Applications of Holonic Manufacturing Systems . 170 7.4 An Approach: the Fabricare Holonic System 172 7.4.1 General Description 172 7.4.2 Description of Major Holons 173 7.4.3 Negotiation Protocol . 176 7.4.4 A Prototype . 179 7.4.5 Experiments 183 7.5 Conclusions 185 References 187 8 Agent-based Dynamic Scheduling for Distributed Manufacturing . 191 Weiming Shen, Qi Hao 8.1 Introduction 191 8.2 Complexity of Manufacturing Scheduling Problem . 192 8.3 Literature Review . 193 8.4 iShopFloor Framework . 195 8.5 Agent-based Dynamic Manufacturing Scheduling . 198 8.6 Agent Framework – AADE 201 8.7 Proof-of-concept Prototypes . 203 8.7.1 Agent-based Dynamic Scheduling in iShopFloor 203 8.7.2 Real-time Scheduling Service for Enterprise Collaboration . 204 8.8 Key Issues in Technology Deployment in Industry 207 8.9 Conclusions and Future Work 208 References 210 9 A Multi-agent System Implementation of an Evolutionary Approach to Production Scheduling 213 Scott S. Walker, Douglas H. Norrie, Robert W. Brennan 9.1 Introduction 213 9.2 Background 214Contents xiii 9.2.1 HMS Architectures and Scheduling 214 9.2.2 Intelligent Job-shop Scheduling 215 9.3 Implementing the Agent-based Scheduling System . 216 9.3.1 The Benchmark . 216 9.3.2 The System Architecture 218 9.3.3 The Scheduling Algorithm 219 9.4 Experiments 225 9.4.1 Summary of the Experimental System . 225 9.4.2 Stochastic Scenario (Stage 2) Results . 229 9.4.3 Evolving the Mixed-heuristic Scheduler 232 9.5 Conclusions 237 References 239 10 Distributed Scheduling in Multiple-factory Production with Machine Maintenance . 243 Felix Tung Sun Chan, Sai Ho Chung 10.1 Introduction 243 10.2 Literature Review . 246 10.3 Problem Background 249 10.4 Optimisation Methodology: Genetic Algorithm with Dominant Genes 253 10.4.1 Dominant Genes . 253 10.4.2 Encoding of Chromosome 255 10.4.3 Dominant Genes Crossover 256 10.4.4 Mutation Operator 257 10.4.5 Elitist Strategy 258 10.4.6 Prevention of Prematurity and Local Searching . 258 10.5 Example 259 10.6 Conclusions 264 References 264 11 Resource Scheduling for a Virtual CIM System . 269 Sev Nagalingam, Grier Lin, Dongsheng Wang 11.1 Introduction 269 11.2 VCIM System . 270 11.2.1 VCIM Issues . 272 11.2.2 Need for a VCIM Architecture . 274 11.2.3 An Agent-based VCIM Architecture 278 11.2.4 A Java Implementation Environment for a Multi-agent VCIM System . 280 11.3 Resource Scheduling with the VCIM Architecture 283 11.3.1 Resource Scheduling in a VCIM System 283 11.3.2 VCIM Resource Scheduling Process 284 11.4 Conclusions 291 References 292xiv Contents 12 A Unified Model-based Integration of Process Planning and Scheduling . 295 Weidong Li, S.K. Ong, A.Y.C. Nee 12.1 Introduction 295 12.2 Recently Related Works . 296 12.3 A Unified Model to Integrate Process Planning and Scheduling 297 12.4 Simulated Annealing-based Optimisation Approach 303 12.5 Case Studies and Discussions . 305 12.6 Conclusions 307 References 308 13 A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing . 311 Nobuhiro Sugimura, Rajesh Shrestha, Yoshitaka Tanimizu, Koji Iwamura 13.1 Introduction 311 13.2 Literature Review . 312 13.3 Process Planning for Holonic Manufacturing Systems 313 13.3.1 Holonic Manufacturing Systems 313 13.3.2 Integrated Process Planning and Scheduling 315 13.3.3 Target System Configuration 315 13.4 Process Planning by Job Holons . 317 13.4.1 Input Information 317 13.4.2 Objective Functions 318 13.4.3 Procedures Based on GA and DP . 320 13.5 Scheduling by Scheduling Holon . 323 13.5.1 Objective Functions 323 13.5.2 Scheduling Method Based on GA and Dispatching Rules 325 13.5.3 Process Plan Modification 326 13.6 Case Studies . 328 13.6.1 Process Planning . 328 13.6.2 Verification of Dispatching Rules 329 13.6.3 Verification of Process Plan Modification 330 13.7 Conclusions 332 References 332 14 Managing Dynamic Demand Events in Semiconductor Manufacturing Chains by Optimal Control Modelling . 335 Yon-Chun Chou 14.1 Introduction 335 14.2 Problem Description . 339 14.3 Full-load Production Functions 343 14.3.1 A Full-load Production Function Based on Alternative Routing . 346 14.4 A Dynamic System Model . 349Contents xv 14.4.1 A Formulation of Optimal Control . 350 14.4.2 Closed Control Set 354 14.5 Numerical Examples and Application 356 14.6 Conclusions 362 References 362 15 A Parameter-perturbation Approach to Replanning Operations 365 Nazrul I. Shaikh, Michael Masin, Richard A. Wysk 15.1 Introduction 365 15.2 AHFM Approach 366 15.2.1 AHFM for Production Planning . 367 15.2.2 Solution Approach to AHFM . 374 15.2.3 Scalability of AHFM 379 15.3 Plan Perturbation due to New Customers Orders . 382 15.3.1 Estimation of New Order Cost 382 15.3.2 New Order Insertion Case Study 386 15.4 Extending the Applicability of AHFM . 389 15.5 Conclusions 391 References 391 16 STEP into Distributed Manufacturing with STEP-NC 393 Xun Xu 16.1 Introduction 393 16.2 Impediments of Current CNC Technologies 395 16.3 The STEP-NC Standard 396 16.4 STEP-NC Implementation Methods . 398 16.4.1 Part 21 Physical File Implementation Method 399 16.4.2 Data Access Implementation Methods . 400 16.4.3 XML Implementation Method (Part 28 Edition 1) . 401 16.4.4 XML Implementation Method (Part 28 Edition 2) . 402 16.4.5 Recap – Issues Concerning STEP-NC in XML Format 402 16.4.6 Recent Research Publications . 403 16.5 A STEP-compliant CAPP System for Distributed Manufacturing . 403 16.5.1 System Model . 406 16.5.2 Native STEP-NC Adaptor and Native CNC Databases 411 16.5.3 System Development 412 16.6 Conclusions 417 References 419 Index 423 Index adaptability, 2, 4–5, 27, 115, 180, 185–186, 208, 305, 308, 394–396 adaptation, 44, 56, 181, 207–208 adaptive planning, 130 adaptor, 409, 411–412, 415–416, 418 aesthetics, 37, 92 agent agent framework, 186, 201, 203, 208–209, 212, 297 agent-based system, 189, 195, 210–211, 216, 264, 274–275, 277, 293 autonomy, 3, 10, 167–170, 185–186, 193, 275, 313–314 customer agent, 278–280, 282–284, 291 facilitator agent, 278–291 mediator agent, 205–206, 218–219, 277 resource agent, 196–199, 204–206, 208, 213, 218–219, 222–223, 232, 276, 278–285, 287–292 assembly, 29, 39, 90, 92–93, 115, 136, 170, 194, 215, 239–240, 279, 283–284, 309, 312, 314, 333, 410, 415, 418 bar code, 122 batch production, 110–111, 137, 311 benchmarking, 40, 237, 307 best practice, 17, 137, 139, 143–144, 146, 150, 153, 156, 159, 162–164, 186 bill of materials, 112, 117, 119, 125, 134 binding, 356, 400–402, 413, 420 business case, 42, 44–45, 56 CAMP, 137–138, 140–141, 159–164 capacity, 1, 4, 10, 103, 114–115, 118–121, 130, 134–136, 169, 172, 193, 201, 207, 213, 220, 245, 252, 291, 335–336, 338, 340, 342–351, 354–357, 362–363, 368–369, 373–378, 382, 391 case-based reasoning, 35 classification, 4, 57–59, 74–76, 136 collaboration, 193, 196–197, 204, 243–244, 273, 277, 294, 335, 418 collision check, 102 constraint, 28, 93, 98, 139, 146, 149, 155, 157, 163, 174, 177, 252, 276, 303–304, 309, 347, 350, 354, 370–372, 374 contract net, 4, 167, 170, 174, 176, 185, 189, 194, 199, 206, 210, 277, 284, 294, 313, 333 control adaptive control, 130–131 computer numerical control, 5, 15, 27, 88, 90–91, 95, 109, 111, 113–114, 116, 121, 125, 134, 139, 146, 150, 311, 367, 393–398, 402–404, 406, 411–412, 416, 418–421 execution control, 7, 10–11, 18, 21–22, 26–27, 30, 219, 313 optimal control, 335, 350, 356–357, 359–360, 362–363 process control, 2, 134, 276, 366 controller CNC controller, 5, 27, 396, 403, 406, 418 fuzzy logic controller, 36424 Index open architecture controller, 25, 196 PLC controller, 10, 395 cooperation, 3, 81, 167–170, 176, 187–189, 193–194, 207–208, 214–215, 239–240, 273, 275, 289, 297, 314 customer requirement, 50–51, 109, 111, 114, 269, 271, 291 data mining, 31 database, 32, 44–45, 61, 64, 70–71, 87, 96, 100–101, 113, 180, 197, 202, 274, 278, 281–283, 285, 289–290, 393, 404–407, 409–417 decision making, 1–4, 7, 11, 33, 41, 148, 163–164, 193–195, 198, 210–211, 214–215, 294–295, 311–314, 332, 379 decision support, 31–32, 42, 57, 265 dispatching rule, 246–247, 276, 312, 325–326, 329–330, 332 distributability, 394, 396 disturbance, 171, 191, 209 dynamic programming, 323, 332 dynamic system, 335, 339–340, 342, 349–350, 362 dynamism, 1–2, 4, 170, 177, 185, 192 e-business, 34, 272, 274 efficiency, 110–121, 126–128, 137, 159, 169, 186, 191, 208, 228, 243–246, 249, 272, 274–275, 280, 327, 335, 338, 344, 393–394 enterprise collaboration, 198, 204, 206 ERP, 207, 209, 212 evolutionary algorithm, 58, 215, 223, 225–226, 228, 232–234, 236, 238, 297, 307–309 expert system, 3, 28, 33, 59, 89–90, 113, 134, 136, 139, 165, 190, 265, 281, 333 EXPRESS, 398–403, 410, 413, 420 feature constraint, 104 feature graph, 96, 98–101 feature hierarchy, 101, 104–105 feature recognition, 61, 69, 73, 87, 91, 94, 99–100, 107, 406, 409 feature specification, 2, 7, 9, 11, 30, 32, 38 FIPA, 195, 197, 201, 203, 209, 212, 218, 277, 280, 282 fixture design, 2, 30, 61, 69, 138–140, 146–148, 150, 153, 156, 161, 165–166 flow shop, 2, 210, 267 flow time, 267, 336, 343–344, 346 forecasting, 131–132, 134, 136 full-load production, 335, 343–346, 348–349, 356, 362 function block, 1–2, 6–11, 18–22, 25–27, 30, 313 fuzzy fuzzification, 53 fuzzy logic controller, 36 fuzzy modelling, 32, 35–36 fuzzy rule, 36–37, 45, 49, 51–55, 57, 59 fuzzy set, 36, 48, 51–52 membership function, 36–37, 45, 48–49, 51–53, 55, 59 universe of discourse, 48, 51 genetic algorithm chromosome, 36, 48, 51–56, 234–235, 247–248, 253, 255–260, 264 crossover, 36, 48, 55, 223, 234–235, 246–248, 253–258, 264, 297, 307–308, 322 decoding, 55, 255, 282 dominant gene, 267 encoding, 53, 202, 220, 223, 235, 248, 255–256, 260, 420 evolution, 30, 35, 55, 166, 168, 181, 188, 223, 235, 239–240, 248, 254, 256, 258, 266, 307, 363 fitness, 36, 48, 53–56, 200, 234–236, 253–257, 307Index 425 genetic parameter, 247–248, 253, 264 mutation, 36, 48, 55, 223, 234–235, 247–248, 253, 257–259, 297, 304, 307–308, 322 offspring, 254–257, 264, 322 Roulette wheel, 235 termination criteria, 36, 49, 55 global search, 36, 247, 258 graph theory, 138, 149–150, 166 heuristic approach, 246, 248, 266 hierarchical structure, 30, 38, 44 holonic system, 170, 186, 214, 218–219, 225 IEC 61499, 9, 30, 186 inference engine, 67–68, 72, 86, 281–282, 289 information sharing, 31–32, 42, 296 interoperability, 3, 186, 280–281, 394–396 inventory, 95, 113, 118, 132–133, 209, 245, 264, 335, 337–342, 349, 352–353, 357, 359–360, 363, 387–388 ISO 10303, 332, 395–396, 398–400, 403, 409–410, 419–420 ISO 14649, 332, 396, 398, 409–410, 418–420 ISO 6983, 27, 395–396, 404, 419 JADE, 172, 201, 203, 208, 280–282 Java 3D, 62–63, 73, 77, 84, 88, 90 Jess, 62–64, 69–70, 83–84, 86, 88–89, 280–282, 289 job delay, 1, 5 job tardiness, 295–296, 301, 308 just-in-time, 113, 115, 117, 121–123, 135, 211, 217, 221–223, 227–228 Kanban, 125 knowledge engineering knowledge, 112, 113, 134 knowledge acquisition, 34, 40–41, 68 knowledge base, 7, 25, 31–34, 36–37, 45, 48–50, 56–57, 62, 65, 67–69, 72, 87, 121, 162, 167, 173, 190, 197, 203, 211, 278, 281–283, 289 knowledge discovery, 31, 41 knowledge exchange, 45 knowledge management, 33–34, 40, 57, 59 lead time, 111, 114, 116, 119–122, 136, 244–245, 260, 338, 391 line balancing, 115, 117 local search, 247, 258 machine machine tool, 14, 23, 69, 95–96, 104, 138, 143–144, 146, 148, 150, 153, 155–156, 158, 160, 162, 314–315, 317–320, 322–323, 328, 393–396, 398, 402–403, 405–407, 409–412, 415–419 machine utilisation, 264, 295–297, 299–301, 303–304, 308 machining centre, 158–159, 412 machine backup planning, 344 machine grouping, 344 machine learning, 265, 403 machining cutting parameter, 6, 8, 10, 19, 21, 25, 70–71, 76, 96, 148 drilling, 5, 8, 64, 66–67, 99, 147, 157, 415 G-code, 25, 27, 88, 395–396, 403 machining cost, 102, 104, 315, 317–320, 323–324, 328, 330, 332, 334 machining feature, 1–2, 4–9, 11–14, 16–21, 23, 25, 29–30, 62–64, 79–80, 84, 139–140, 152, 154, 312–313, 315, 317–323, 328, 332, 397–398, 402, 404–405, 409, 418, 420 machining process, 1, 5–7, 11, 16, 21, 27, 61, 64–65, 67, 69, 72, 88, 91, 138, 154, 166, 317, 319–320, 323–326, 328, 403426 Index machining sequence, 5, 7, 11, 15, 17, 20, 25, 312, 315, 317, 320–322, 328, 332, 406 milling, 5, 8, 10, 64–67, 69–75, 78, 86–88, 90, 92, 95, 99, 101, 147, 149, 157, 211, 367, 399, 401, 403, 409, 412, 419, 421 surface finish, 2, 37, 49, 51, 57, 64–65, 138, 371 tool path, 2, 4–8, 10, 17, 20, 25, 28, 74–76, 79, 86–87, 90–91, 94, 101–105, 139–140, 142–144, 156, 162, 165, 371, 397 virtual machining, 61–63, 72–73, 78–84, 87–88 manufacturability, 38, 93–95, 99, 112, 219, 303 manufacturing computer integrated manufacturing, 28–30, 89–90, 107, 135–136, 188, 212, 265, 269–274, 291–293, 308, 333, 367, 420–421 flexible manufacturing, 4, 109, 113, 134, 136–138, 140, 150, 164, 167–168, 210, 215, 265, 267, 393 holonic manufacturing HMS, 30, 167–172, 185–189, 194, 214–216, 239–240, 275, 311–315, 317–318, 323, 325, 330, 332–334 holarchy, 169–173, 176, 186, 189, 218–219, 277, 314 holon, 168–181, 184, 189, 211, 214–215, 218, 277, 313, 315, 323, 325, 329–330, 332 intelligent manufacturing, 28–29, 168–169, 187–190, 195, 210–211, 239–240, 264–266, 276, 291, 293–294, 308–309, 333 manufacturing constraint, 15, 25, 93, 139, 297, 303–305 manufacturing cost, 148, 295–297, 299, 301, 303–305, 308 manufacturing feature, 30, 63, 93–94, 96, 140–143, 148, 152–153, 398 manufacturing rule, 93, 99 manufacturing service, 3, 204, 206, 335–336, 340, 342 virtual manufacturing, 88, 265 mass customisation, 109–110, 112–113, 117–118, 122, 134–135, 137–140, 144, 146–147, 159, 161, 164–166, 195, 271 mass production, 109, 111–112, 118, 137, 139, 147, 155–156, 159, 167, 393 model animation model, 62–63, 72, 78, 88 application interpreted model, 396, 401, 404, 409, 418, 420 application reference model, 396, 399, 420 CAD model, 63, 72–73, 83, 107, 138, 140, 142, 161, 315, 395 dynamic model, 240, 338, 363, 376 feature model, 8–9, 30, 61, 63, 72–73, 75, 101 geometric model, 63, 72–74, 88 solid model, 28, 63, 73, 107, 407 time-delay model, 338 time-varying model, 338–339 monitoring process monitoring, 1–2, 10, 22, 27 real-time monitoring, 26 remote monitoring, 196 Monte Carlo, 216 MRP, 117, 164, 207, 209 multi-functional environment, 40–41 negotiation, 3, 170, 173, 175–178, 180, 189, 194–195, 198–200, 203, 206, 212, 276–277, 284, 287, 289, 291, 297 neural network, 2–3, 29, 131, 136, 139, 149, 194, 309, 403, 421 object-oriented, 2, 4, 28, 62, 89, 274, 398Index 427 objective-oriented, 226, 238 OKP, 3, 29, 109–112, 114, 117–118, 130–132, 134–136 optimisation linear optimisation, 125, 376 optimal solution, 4, 35, 104, 146, 155, 192–193, 213, 246, 253–254, 305, 307, 325, 371, 383–384, 386, 390, 402 parameter optimisation, 31, 49 particle swarm optimisation, 307 order insertion, 386 perturbation, 366, 382, 386–389 Petri net, 2, 28, 115, 130, 136, 194, 277 physical file, 398–399, 406, 413 polishing abrasive polishing, 33 polishing feature, 38, 41, 44–45 polishing operation, 32, 37–38, 41, 44 polishing process, 32–33, 37–39, 41–45, 49, 56–57 polishing quality, 37, 42 wheel speed, 33, 50–53 portal, 31–34, 40–43, 45, 56–59, 205 precedence, 5, 14, 64, 66–67, 69–70, 90, 101, 104, 139, 149, 154, 157, 177, 194, 217, 220–222, 224, 226–227, 248, 252, 266, 297, 394 process planning CAPP, 1–5, 26, 28–30, 61–62, 68, 87, 89–90, 109, 148, 165–166, 275, 308, 395, 403, 405–411, 415, 418–420 distributed process planning, 1–2, 4–7, 9–11, 14–15, 18, 21, 23, 26–27, 30, 61, 88, 90, 313, 333, 403 long-term planning, 117, 131, 187 operation planning, 1, 5–7, 17, 20, 22, 25–27, 29, 313 operation sequencing, 200, 295–296, 298–299, 308 operation sheet, 38, 42, 44–45 postprocessor, 396 process parameter, 32, 38, 40, 44–45, 48, 50–51, 61, 148, 165, 366, 375–376 process selection, 61–72, 80–84, 86–89, 95 process sequencing, 1, 2, 6, 11, 27–28, 69, 146, 150, 153, 155, 158 replanning, 365 short-term planning, 117, 134 supervisory planning, 1, 5–7, 11, 22, 27, 313 processing algorithm, 11, 44 processing flexibility, 295–296, 298–299, 308 product product customisation, 31, 167 product design, 3–4, 6, 29, 31, 45, 89, 109, 111, 135, 137–138, 159, 201, 214, 277, 283, 395 product development, 29, 32, 34, 41, 45, 56–57, 61, 110, 112, 159, 163, 277, 293, 295, 307, 397, 421 product improvement, 110 product structure, 32, 42, 44–45, 159, 417 production cost, 37, 110–112, 137, 228, 245, 297, 369, 371, 373 production cycle, 110, 123 production line, 116, 118–127, 130, 132–134, 136, 247 production planning, 117, 164–195, 207, 211, 239, 245, 277, 293, 309, 365–366, 368, 374–375, 378, 391 production rate, 111, 118, 123–125, 130, 146, 245, 338 rapid prototyping, 91, 95, 201 recognition, 2, 7, 9, 11, 30, 91, 94, 113, 409 reconfigurability, 394 reliability, 37, 244–246, 248, 269, 280, 283, 337, 367 repository, 84, 90, 173428 Index resource plan, 114, 135, 272, 274–275, 278–279, 281, 290–291 responsiveness, 5, 112, 193, 198, 243, 295, 313 rule-based system, 64, 68 SCADA, 207 scene graph, 77–79, 81 scheduling delivery date, 117–119 distributed scheduling, 239, 243–245, 248–249, 265, 267, 333 dynamic scheduling, 5, 7, 22, 26, 136, 189, 192–195, 198–200, 203–205, 207–208, 210–211, 293 flight scheduling, 366 job allocation, 244, 248–250 job scheduling, 95, 336 makespan, 131, 228, 230–231, 233, 249, 251, 259–260, 264, 295–297, 300–305, 308, 326 production scheduling, 117, 135–136, 211, 213, 243–245, 249–250, 253, 267, 308, 313, 315, 333, 373 real-time scheduling, 193, 201, 209, 266, 312, 315, 332–333 routing, 112, 116, 125, 182, 243, 245, 248, 256, 265, 267, 336, 343–344, 346–347, 373 scheduling flexibility, 295–296, 298–299, 308 scheduling heuristics, 172, 213, 221, 224, 229 scheduling policy, 245 semantic net, 62, 65 sequence of machining equipment, 321–322, 328 sequencing and optimisation, 38 setup merging, 15, 22–23, 25, 27 setup planning, 2, 5–6, 28, 30, 69, 101, 137–140, 144–145, 148–150, 152–156, 158, 161–165, 409 shop time, 315, 317–320, 322–323, 328, 332, 334 similarity, 57, 137, 140, 246, 258–259 simulated annealing, 160, 165, 194, 218–219, 246, 248, 266, 269, 276, 295–296, 303–304, 307, 309 simulation, 36, 88, 116, 130, 164, 194, 225–226, 238, 243, 267, 276, 339, 367, 374–378, 396 single point of access, 34, 56 specification, 9, 32, 37–38, 45, 64, 110, 112, 118, 122, 150, 189, 313, 369, 418 standard time, 118–119 STEP AP203, 395, 405, 409 AP214, 395, 405, 409 AP224, 397, 409, 410 SDAI, 400–401 STEP-compliant NC, 420 STEP-NC, 393–394, 396–399, 402–407, 409, 411, 413, 415, 418–421 Workingstep, 397, 402, 407–409 Workplan, 397, 399 structured dataset, 40 synchronisation, 63, 72, 123–124, 127, 134 system analysis, 160, 166, 218 Tabu search, 246, 265, 276, 285, 287–288, 297, 318–319, 420 TAD, 11, 15, 17, 23–24, 146, 155–157, 297, 299–300, 304, 394 tardiness, 245, 297, 303–304, 315, 325, 327, 330, 334 threshold, 258–259, 291, 360 time-to-market, 45 tolerance, 2, 8, 14, 28, 61, 64–65, 67, 69–70, 95, 137–140, 145–146, 149–155, 157–158, 161, 163, 165–166, 197, 209, 413 tool database, 96, 410, 417 total quality management, 33Index 429 uncertainty, 1, 2, 6, 27, 265, 335, 337, 339 virtual CIM, 269–284, 286, 289–294 virtual enterprise, 172, 187, 189, 196, 244, 269–270, 272–274, 283, 292, 294 VRML, 88 workpiece, 8, 11, 14, 19, 61, 63, 73–79, 88, 91, 138, 154, 318, 374, 412, 417–418 World Wide Web, 29, 274 XML, 62–63, 67, 70, 72, 80, 82–85, 88, 90, 198, 201, 204, 212, 398–399, 401–404, 407, 409–411, 413–415, 418, 420–421
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