كتاب Process Planning and Scheduling for Distributed Manufacturing
منتدى هندسة الإنتاج والتصميم الميكانيكى
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منتدى هندسة الإنتاج والتصميم الميكانيكى
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 كتاب Process Planning and Scheduling for Distributed Manufacturing

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Process Planning and Scheduling for Distributed Manufacturing
Lihui Wang and Weiming Shen (Eds.)

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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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