Process Planning and Scheduling for Distributed Manufacturing

Front Cover
Lihui Wang, Weiming Shen
Springer Science & Business Media, May 14, 2007 - Technology & Engineering - 429 pages
Manufacturing has been one of the key areas that support and influence a nation’s economy since the 18th century. Being the primary driving force in economic growth, manufacturing constantly serves as the foundation of and contributes to other industries with products ranging from heavy-duty machinery to hi-tech home electronics. In the past centuries, manufacturing has contributed significantly to modern civilisation and created momentum that is used to drive today’s economy. Despite various revolutionary changes and innovations in the 20th century that contributed to manufacturing advancements, we are still facing new challenges when striving to achieve greater success in winning global competitions. Today, distributed manufacturing is unforeseeably coming into being due to recent business decentralisation and manufacturing outsourcing. Manufacturers are competing in a dynamic marketplace that demands short response time to changing markets and agility in production. In the 21st century, manufacturing is gradually shifting to a distributed environment with increasing dynamism. In order to win a competition, locally or globally, customer satisfaction is treated with priority. This leads to mass customisation and even more complex manufacturing processes, from shop floors to every level along manufacturing supply chains. At the same time, outsourcing has forged a multi-tier supplier structure with numerous small-- medium-sized enterprises involved, where highly-mixed products in small batch sizes are handled simultaneously in job-shop operations.
 

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Contents

82 Complexity of Manufacturing Scheduling Problem
192
83 Literature Review
193
84 iShopFloor Framework
195
85 Agentbased Dynamic Manufacturing Scheduling
198
86 Agent Framework AADE
201
87 Proofofconcept Prototypes
203
872 Realtime Scheduling Service for Enterprise Collaboration
204
88 Key Issues in Technology Deployment in Industry
207

143 EMF Sequencing
15
144 Function Block Design
18
15 Setup Merging and Monitoring
22
151 Setup Merging
23
152 Detailed Operation Planning
25
153 Function Block Execution Control and Monitoring
26
16 Conclusions
27
References
28
Webbased Polishing Process Planning Using Datamining Techniques
31
22 Literature Review
33
223 Casebased Reasoning
35
225 Genetic Algorithms
36
23 Polishing Process Planning
37
232 Design of Polishing Process Planning
38
24 Webbased Portal System for Polishing
40
241 Problem Definition
41
243 Design of Webbased Portal System
42
244 Implementation of Webbased Portal System
45
252 Case Study
49
26 Results and Discussions
55
27 Conclusions
56
References
57
Integration of Rulebased Process Selection with Virtual Machining for Distributed Manufacturing Planning
60
32 IMPlanner Architecture
62
33 Knowledgebased Process Selection
64
332 Process Selection Rules
67
333 Knowledge BaseDatabase
71
334 Integration of Rule Execution Engine into IMPlanner
72
341 Geometric Model
73
342 Kinematic Model
74
343 Animation Model
76
344 Virtual Machining Scene Graph
78
35 Integration Approaches
80
352 Distributed Approach
81
353 Integrated Application
83
36 Case Study
84
37 Related Research
87
38 Conclusions
88
References
89
CyberCut A Coordinated Pipeline of Design Process Planning and Manufacture
91
42 Conventional Approach
92
421 Manufacturingdependent CAD Systems
93
422 Bidirectionally Coupled CAD Systems
94
43 The CyberCut System
95
432 Definition of Features
96
44 Architecture
98
441 WebCAD
99
443 Feature Validation
100
444 Macroplanner and Setup Planner
101
446 Toolpath Planner
104
46 Conclusions
106
References
107
Process Planning Scheduling and Control for OneofaKind Production
109
52 Literature Review
113
53 Process Planning
117
532 Shortterm Process Planning
118
54 Process Control
125
55 Adaptive Planning and Control
127
56 Longterm Resource Planning
131
57 Conclusions
134
References
135
Setup Planning and Tolerance Analysis Yiming Kevin Rong
137
611 Current StateoftheArt
138
62 Manufacturing Planning System
140
622 Feature Manufacturing Strategy
143
623 Machine Tool Capability Modelling
144
625 Fixture Design in Computeraided Manufacturing Planning
146
626 Manufacturing Plan Generation
147
63 Automated Setup Planning
148
631 Graph Theory and Application in Setup Planning
150
633 Datum and Machining Feature Relationship Graph DMG
152
634 Automated Setup Planning
153
635 A Case Study
156
64 Information Modelling
159
642 Information Model of CAMP for Mass Customisation
161
65 Summary and Discussions
164
References
165
Scheduling in Holonic Manufacturing Systems
167
72 Background
168
722 Holonic Manufacturing Systems
169
73 Applications of Holonic Manufacturing Systems
170
the Fabricare Holonic System
172
742 Description of Major Holons
173
743 Negotiation Protocol
176
744 A Prototype
179
745 Experiments
183
75 Conclusions
185
References
187
Agentbased Dynamic Scheduling for Distributed Manufacturing
191
89 Conclusions and Future Work
208
References
210
A Multiagent System Implementation of an Evolutionary Approach to Production Scheduling
213
92 Background
214
922 Intelligent Jobshop Scheduling
215
93 Implementing the Agentbased Scheduling System
216
932 The System Architecture
218
933 The Scheduling Algorithm
219
94 Experiments
225
942 Stochastic Scenario Stage 2 Results
229
943 Evolving the Mixedheuristic Scheduler
232
95 Conclusions
237
References
239
Distributed Scheduling in Multiplefactory Production with Machine Maintenance
243
102 Literature Review
246
103 Problem Background
249
Genetic Algorithm with Dominant Genes
253
1042 Encoding of Chromosome
255
1043 Dominant Genes Crossover
256
1044 Mutation Operator
257
1045 Elitist Strategy
258
105 Example
259
106 Conclusions
264
Resource Scheduling for a Virtual CIM System Sev Nagalingam Grier Lin and Dongsheng Wang
268
112 VCIM System
270
1121 VCIM Issues
272
1122 Need for a VCIM Architecture
274
1123 An Agentbased VCIM Architecture
278
1124 A Java Implementation Environment for a Multiagent VCIM System
280
113 Resource Scheduling with the VCIM Architecture
283
1132 VCIM Resource Scheduling Process
284
114 Conclusions
291
References
292
A Unified Modelbased Integration of Process Planning and Scheduling Weidong Li1 SK Ong2 and AYC Nee2
295
122 Recently Related Works
296
123 A Unified Model to Integrate Process Planning and Scheduling
297
124 Simulated Annealingbased Optimisation Approach
303
125 Case Studies and Discussions
305
126 Conclusions
307
References
308
A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing
311
132 Literature Review
312
133 Process Planning for Holonic Manufacturing Systems
313
1332 Integrated Process Planning and Scheduling
315
134 Process Planning by Job Holons
317
1342 Objective Functions
318
1343 Procedures Based on GA and DP
320
135 Scheduling by Scheduling Holon
323
1352 Scheduling Method Based on GA and Dispatching Rules
325
1353 Process Plan Modification
326
136 Case Studies
328
1362 Verification of Dispatching Rules
329
1363 Verification of Process Plan Modification
330
137 Conclusions
332
Managing Dynamic Demand Events in Semiconductor Manufacturing Chains by Optimal Control Modelling
335
142 Problem Description
339
143 Fullload Production Functions
343
Thus 2 yfwawbwc where 2 u baw and 2 00 0 2u
346
144 A Dynamic System Model
349
1441 A Formulation of Optimal Control
350
1442 Closed Control Set
354
145 Numerical Examples and Application
356
146 Conclusions
362
A Parameterperturbation Approach to Replanning Operations
364
152 AHFM Approach
366
1521 AHFM for Production Planning
367
1522 Solution Approach to AHFM
374
1523 Scalability of AHFM
379
153 Plan Perturbation due to New Customers Orders
382
1532 New Order Insertion Case Study
386
154 Extending the Applicability of AHFM
389
155 Conclusions
391
STEP into Distributed Manufacturing with STEPNC
393
162 Impediments of Current CNC Technologies
395
163 The STEPNC Standard
396
164 STEPNC Implementation Methods
398
1641 Part 21 Physical File Implementation Method
399
1642 Data Access Implementation Methods
400
1643 XML Implementation Method Part 28 Edition 1
401
1644 XML Implementation Method Part 28 Edition 2
402
1646 Recent Research Publications
403
1651 System Model
406
1652 Native STEPNC Adaptor and Native CNC Databases
411
1653 System Development
412
166 Conclusions
417
References
419
Index
423
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About the author (2007)

Lihui Wang is a professor of virtual manufacturing at the University of Skövde’s Virtual Systems Research Centre in Sweden. He was previously a senior research scientist at the Integrated Manufacturing Technologies Institute, National Research Council of Canada. He is also an adjunct professor in the Department of Mechanical and Materials Engineering at the University of Western Ontario, and a registered professional engineer in Canada. His research interests and responsibilities are in web-based and sensor-driven real-time monitoring and control, distributed machining process planning, adaptive assembly planning, collaborative design, supply chain management, as well as intelligent and adaptive manufacturing systems. Dr Weiming Shen is an Senior Research Officer in the Integrated Manufacturing Technologies Institute, National Research Council of Canada. He is also an Adjunct Full Professor of Systems Design Engineering at the University of Waterloo. His research interests are in Agents and Multi-Agent Systems, Concurrent Engineering, Collaborative Design and Manufacturing, Virtual Design and Manufacturing, Virtual Enterprises and Supply Chain Management, e-Commerce / e-Businesses, and Knowledge-Based Systems.