《系統仿真及ProModel軟體套用（第2版）》是2005年1月1日華大學出版社出版的圖書，作者是（美）哈勒爾、（美）高蒂、（美）鮑登。
基本介紹
- 書名：系統仿真及ProModel軟體套用（第2版）
- 作者：（美）哈勒爾、（美）高蒂、（美）鮑登
- ISBN：9787302099826
- 定價：68.00
- 出版社：清華大學出版社
- 出版時間：2005年1月1日
- 裝幀：平裝
- 開本：16開
- 印次：1-2
內容簡介,圖書前言,圖書目錄,
內容簡介
本書從分析離散事件系統的動態特性開始，介紹了系統仿真的基本概念與方法。結合ProModel仿真軟體的使用，討論了數據收集與分析、仿真模型構建、模型驗證與確認的方法與過程。對輸出分析的基本方法、不同系統配置的性能比較、仿真過程最佳化的策略與方法也進行了詳細的闡述。針對製造系統、物料搬運、服務系統的特點，描述了仿真套用的典型問題，提供了建模的方法與技巧。
本書用了近一半的篇幅，為讀者提供了14個教學實驗的指導，從開始動手使用ProModel軟體，到最後能夠進行複雜系統的建模與仿真分析，實現了從基本理論到套用實踐的順利過渡。本書在最後還提供了8個套用案例，供學習者一試身手。
本書用了近一半的篇幅，為讀者提供了14個教學實驗的指導，從開始動手使用ProModel軟體，到最後能夠進行複雜系統的建模與仿真分析，實現了從基本理論到套用實踐的順利過渡。本書在最後還提供了8個套用案例，供學習者一試身手。
圖書前言
本教材系列的出版正值中國學術界工業工程學科經歷巨大發展、實際工作中對工業工程的概念、方法和工具的使用興趣日漸濃厚之時。在實際工作中有效地套用工業工程的手段將無疑會提高生產率、工作質量、合作的滿意度和效果。
該系列中的書籍對工業工程的本科生、研究生和工業界中需要解決工程系統設計、運作和管理諸方面問題的人士最為適用。
加弗瑞爾·沙爾文迪
清華大學工業工程系
普渡大學工業工程學院（美國）
2002年4月
該系列中的書籍對工業工程的本科生、研究生和工業界中需要解決工程系統設計、運作和管理諸方面問題的人士最為適用。
加弗瑞爾·沙爾文迪
清華大學工業工程系
普渡大學工業工程學院（美國）
2002年4月
圖書目錄
PARI I STUDY CHAPTERS
1 Introduction to Simulation 3
1．1 Introduction 3
1．2 What Is Simulation? 5
1．3 Why Simulate? 6
1．4 Doing Simulation 8
1．5 Use of Simulation 10
1．6 When Simulation Is Appropriate 12
1．7 Qualifications for Doing Simulation 1 4
1．8 Economic Justification of Simulation 15
1．9 Sources of Information on Simulation 19
1．10 How to Use This Book 19
1．11 Summary 20
1．12 Review Questions 20
References 21
2 System Dynamics 23
2．1 Introduction 23
2．2 System Definition 24
2．3 System Elements 25
2．3．1 Entities 26
.2．3．2 Activities 26
2．3．3 Resources 26
2．3．4 Controls 27
2．4 System Complexity 27
2．4．1 Interdependencies 28
2．4．2 Variability 29
2．5 System Performance Metrics 31
2．6 System Variables 33
2．6．1 Decision Variables 33
2．6．2 Response Variables 34
2．6．3 State Vailables 34
2．7 System Optimization 34
2．8 The Systems Approach 36
2．8．1 Identifying Problems and Opportunities 37
2．8．2 Developing Alternative Solutions 37
2．8．3 Evaluating the Solutions 38
2．8．4 Selecting and Implementing the Best Solution 38
2．9 Systems Analysis Techniques 38
2．9．1 Hand Calculations 40
2．9．2 Spreadsheets 40
2．9．3 Operations Research Techniques 41
2．9．4 Special Computerized Tools 44
2．10 Summary 45
2．11 Review Questions 45
References 46
3 Simulation Basics 47
3．1 Introduction 47
3．2 Types of Simulation 47
3．2．1 Static versus Dynamic Simulation 48
3．2．2 Stochastic versus Deterministic Simulation 48
3．3 Random Behavior 49
3．4 Simulating Random Behavior 50
3．4．1 Generating Random Numbers 50
3．4．2 Generating Random Variates 55
3．5 Simple Spreadsheet Simulation 59
3．5．1 Simulating Random Variates 60
3．5．2 Simulating Dynamic，Stochastic Systems 64
3．5．3 Simulation Replications and Output Analysis 66
3．6 Summary 67
3．7 Review Questions 68
References 69
4 Discrete-Event Simulation 71
4．1 Introduction 71
4．2 Discrete-Event versus Continuous Simulation 72
4．2．1 Differential Equations 73
4．2．2 Difference Equations 73
4．2．3 Combined Continuous and Discrete Simulation 74
4．3 How Discrete-Event Simulation Works 74
4．4 A Manual Discrete-Event Simulation Example 77
4．4．1 Simulation Model Assumptions 77
4．4．2 Setting Up the Simulation 78
4．4．3 Running the Simulation 80
4．4．4 Calculating Results 86
4．4．5 Issues 89
4．5 Commercial Simulation Software 89
4．5．1 Modeling Interface Module
4．5．2 Model Processor 90
4．5．3 Simulation Interface Module 90
4．5．4 Simulation Processor 91
4．5．5 Animation Processor 91
4．5．6 Output Processor 92
4．5．7 Output Interface Module 92
4．6 Simulation Using ProModel 93
4．6．1 Building a Model 93
4．6．2 Running the Simulation 93
4．6．3 Output Analysis 94
4．7 Languages versus Simulators 97
4．8 Future of Simulation 98
4．9 Summarv 99
4．10 Review Questions 100
References 101
5 Getting Started 103
5．1 Introductin 103
5．2 Preliminary Activities 104
5．2．1 Selecting an Application 104
5．2．2 Personnel Identification 105
5．2．3 Software Selection 106
5．3 Simulation Procedure 107
5．4 Defining the Objective 109
5．5 Defining the Scope of Work 112
5．5．1 Determining Model Scode 113
5．5．2 Deciding on Level of Detail 113
5．5．3 Assigning Data—Gathering Resnonsibilities 114
5．5．4 Planning the Experimentation 115
5．5．5 Determining the Form of Results 115
5．6 Defining Project Requirements 116
5．7 Reasons Why Simulation Projects Fail 117
5．8 Summary 117
5．9 Review Questions 118
5．10 Case Studies 119
Case Study A: AST Computes Big Benefits Using Simulation 119
Case Study B: Durham Regional Hospital Saves $150，000 Annually Using Simulation Tools 122
References 124
6 Data Collection and Analysis 125
6．1 Introduction 125
6．2 Guidelines for Data Gathering 126
6．3 Determining Data Requirements 128
6．3．1 Structural Data 128
6．3．2 Operational Data 128
6．3．3 Numerical Data 129
6．3．4 Use of a Questionnaire 129
6．4 Identifying Data Sources 130
6．5 Collecting the Data 131
6．5．1 Defining the Entity Flow 131
6．5．2 Developing a Description of Operation 132
6．5．3 Defining Incidental Details and Refining Data Values 133
6．6 Making Assumptions 134
6．7 Statistical Analysis of Numerical Data 135
6．7．1 Tests for Independence 137
6．7．2 Tests for Identically Distributed Data 142
6．8 Distribution Fitting 144
6．8．1 Frequency Distributions 145
6．8．2 Theoretical Distributions 146
6．8．3 Fitting Theoretical Distrjbutions to Data 152
6．9 Selecting a Distribution in the Absence of Data 158
6．9．1 Most Likely or Mean Value 158
6．9．2 Minimum and Maximum Values 159
6．9．3 Minimum，Most Likely，and Maximum Values 159
6．10 Bounded versus Boundless Distributions 161
6．11 Modeling Discrete Probabilities Using Continuous Distributions 161
6．12 Data Documentation and Approval 1 62
6．12．1 Data Documeiltation Example 162
6．13 Summary 165
6．14 Review Ouestioils 165
6．15 Case Study：Collecting and Documenting Data for Harry's Drive-Through Restaurant 167
References 169
7 Model Building 171
7．1 Introduction 171
7．2 Converting a Conceptual Model to a Simulation Model 172
7．2．1 Modeling Paradigms 172
7．2．2 Model Definition 174
7．3 Structural Elements 175
7．3．1 Entities 175
7．3．2 Locations 177
7．3．3 Resources 179
7．3．4 Paths 181
7．4 Operational Elements 181
7．4．1 Routings 181
7．4．2 Entity Operations 182
7．4．3 Entity Arrivals 185
7．4．4 Entity and Resource Movement 187
7．4．5 Accessin Locations and Resotlrces 188
7．4．6 Resource Scheduling 190
7．4．7 Downtimes and Repairs 191
7．4．8 Use of Programming Logic 195
7．5 Miscellaneous Modeling Issues 197
7．5．1 Modeling Rare Occurrences 197
7．5．2 Large-Scale Modeling 197
7．5．3 Cost Modeling 198
7．6 Summary 199
7．7 Review Questions 199
References 201
8 Model Verification and Validation 203
8．1 Introduction 203
8．2 Importance of Model Verification and Validation 204
8．2．1 Reasons for Neglect 204
8．2．2 Practices That Facilitate Verification and Validation 205
8．3 Model Verification 206
8．3．1 Preventive Measures 207
8．3．2 Establishing a Standard for Comparison 208
8．3．3 Verification Techniques 208
8．4 Model Validation 212
8．4．1 Determining Model Validity 213
8．4．2 Maintaining Validation 215
8．4．3 Validation Examples 215
8．5 Summary 219
8．6 Review Questions 220
References 220
9 Simulation Output Analysis 221
9．1 Introduction 221
9．2 Statistical Analysis of Simulation Output 222
9．2．1 Simulation Replications 223
9．2．2 Performance Estimation 224
9．2．3 Number of Replications (Sample Size) 228
9．2．4 Real-World Experiments versus Simulation Experiments 231
9．3 Statistical Issues with Simulation Output 232
9．4 Terminating and Nonterminating Simulations 235
9．4．1 Terminating Simulations 236
9．4．2 Nonterminating Simulations 236
9．5 Experimenting with Terminating Simulations 237
9．5．1 Selecting the Initial Model State 238
9．5．2 Selecting a Terminating Event 238
9．5．3 Determining the Number of Replications 238
9．6 Experimenting with Nonterminating Simulations 239
9．6．1 Determining the Warm-up Period 239
9．6．2 Obtaining Sample Observations 244
9．6．3 Determining Run Length 249
9．7 Summary 250
9．8 Review Questions 251
References 252
10 Comparing Systems 253
10．1 Introduction 253
10．2 Hypothesis Testing 254
10．3 Comparing Two Alternative System Designs 257
10．3．1 Welch Confidence Interval for Comparing Two Systems 258
10．3．2 Paired-t Confidence Interval for Comparing Two Systems 260
10．3．3 Welch versus the Paired-t Confidence Interval 262
10．4 Comparing More Than Two Alternative System Designs.. 263
10．4．1 The Bonferroni Approach for Comparing More Than Two Alternative Systems
10．4．2 Advanced Statistical Models for Comparing More Than Two Alternative Systems 268
10．4．3 Factorial Design and Optimization 274
10．5 Variance Reduction Techniques 276
10．5．1 Common Random Numbers 276
10．5．2 Example Use of Common Random Numbers 279
10．5．3 Why Common Random Numbers Work 281
10．6 Summary 281
10．7 Review Questions 282
References 283
12 Modeling Manufacturing Systems 311
12．1 Introduction 311
12．2 Characteristics of Manufacturing Systems 312
12．3 Manufacturing Terminology 313
12．4 Use of Simulation in Manufacturing 315
12．5 Applications of Simulation in Manufacturing 316
12．5．1 Methods Analysis 317
12．5．2 Plant Layout 318
12．5．3 Batch Sizing 320
12．5．4 Production Control 321
12．5．5 Inventory Control 324
12．5．6 Supply Chain Management 325
12．5．7 Production Scheduling 326
12．5．8 Real-Time Control 327
12．5．9 Emulation 327
12．6 Manufacturing Modeling Techniques 328
12．6．1 Modeling Machine Setup 328
12．6．2 Modeling Machine Load and Unload Time 328
12．6．3 Modeling Rework and Scrap 329
12．6．4 Modeling Transfer Machines 329
12．6．5 Continuous Process Systems 331
12．7 Summary 332
12．8 Review Ouestions 332
References 332
13 Modeling MateriaI Handling Systems 335
13．1 Introdtiction 335
13．2 Material Handling Principles 335
13．3 Material Handling Classification 336
13．4 Conveyors 337
13．4．1 Conveyor Types 337
13．4．2 Operational CharactedsticS 339
13．4．3 Modeling Conveyor Systems 340
13．4．4 Modeling Single-Section Conveyors 341
13．4．5 Modeling Conveyor Networks 342
13．5 Industrial Vehicles 342
13．5．1 Modeling Industrial Vehicles 343
13．6 Automated Storage/Retrieval Systems 343
13．6．1 Configuring an AS/RS 344
13．6．2 Modeling AS/RSs 346
13．7 Carousels 347
13．7．1 Carousel Configurations 347
13．7．2 Modeling Carousels 347
13．8 Automatic Guided Vehicle Systems 348
13．8．1 Designing an AGVS 349
13．8．2 Controllingan AGVS 350
13．8．3 Modeling an AGVS 35l
13．9 Cranes and Hoists 352
13．9．1 Crane Management 352
13．9．2 Modeling Bridge Cranes 352
13．10 Robots 353
13．10．1 Robot Control 353
13．10．2 Modeling Robots 354
13．11 Summarv 355
13．12 Review Questions 355
References 356
14 Modeling Service Systems 357
14．1 Introduciton 357
14．2 Characteristics of Service Systems 358
14．3 Performance Measures 359
14．4 Use of Simulation in Service Systems 360
14．5 Applications of Simulation in Service Industries 362
14．5．1 Process Design 362
14．5．2 Method Selection 362
14．5．3 System Layout 363
14．5．4 Staff Planning 363
14．5．5 Flow Control 364
14．6 Types of Service Systems 364
14．6．1 Service Factory 364
14．6．2 Pure Service Shop 365
14．6．3 Retail Service Store 365
14．6．4 Professional Service 366
14．6．5 Telephonic Service 366
14．6．6 Delivery Service 367
14．6．7 Transportation Service 367
14．7 Simulation Example: A Help Desk Operation 367
14．7．1 Background 368
14．7．2 Model Description 368
14．7．3 Results 371
14．8 Summary 372
14．9 Review Questions 372
References 372
PART II LABS
1 Introduction to ProModel 6．0 377
L I．1 ProModel 6．0 Opening Screen 378
L I．2 Simulation in Decision Making 379
LI．2．1 Average Waiting Time 380
LI．2．2 Maximum Queue Length 281
L1．3 Exercises 382
2 ProModel World View，Menu，and Tutorial 383
L2．1 Introduction to the ProModel Menu 383
L2．1．1 The Title and the Menu Bars 383
L2．1．2 File Menu 384
L2．1．3 Edit Menu 384
L2．1．4 Build Menu 385
L2．1．5 Simulation Menu 386
L2．1．6 Output Menu 387
L2．1．7 Tools Menu 387
L2．1．8 View Menu 388
L2．1．9 Window Menu 389
L2．1．10 Help Menu 389
L2．2 Basic Modeling Elemellts 390
L2．2．1 Letatioils 390
L2．2．2 Entities 390
L2．2．3 Arrivals 39l
L2．2．4 Precessing 392
L2．3 Innovative Feattires in ProModel 393
L2．3．1 Logic Builder 393
L2．3．2 Dynamic Plots 395
L2．3．3 Customize 397
L2．3．4 Ouick Bar 397
L2．4 A Tutorial On PreModel 6．0 399
L2．5 Exercises 400
3 Running a ProModel Simulation 403
L3．1 ATM System Specincatioils and Problem Statement 403
L3．1．1 Queuing Theory's Answer to the ATM System 404
L3．1．2 PreModel's Answer to the ATM Svstem 404
L3．2 Exercises 406
4 Building Your First Model 409
L4．1 Building Your First Simulation Model 409
L4．2 Building the Bank of USA ATM Model 416
L4．3 Locations，Entities，Precessing，and Arrivals 423
L4．4 Add Location 428
L4．5 Effect of Variability on Model Performance 430
L4．6 Blocking 431
L4．7 Exercises 433
5 ProModel's Output Module 437
L5．1 The Output Program Manager 437
L5．1．1 ReportView 439
L5．1．2 Category Chart 439
L5．1．3 State Chart 441
L5．1．4 Histogram and Time Plot 445
L5．1．5 Sheet Properties 448
L5．2 Classic View 448
L5．2．1 Time Series Plot 450
L5．2．2 Time Series Histogram 450
L5．2．3 Location State Graphs 450
L5．3 Exercises 453
6 Fitting Statistical Distributions to Input Data 455
L6．1 An Introduction to Stat::Fit 455
L6．2 An Example Problem 458
L6．3 Auto::Fit Input Data 460
L6．4 Exercises 463
7 Basic Modeling Concepts 465
L7．1 Multiple Locations，Multiple Entity Types 465
L7．2 Multiple Parallel Identical Locations 468
L7．3 Routing Rules 471
L7．4 Variables 475
L7．5 Uncertainty in Routing--Track Defects And Rework 478
L7．6 Batching Multiple Entities of Similar Type 480
L7．6．1 Temporary Batching--GROUP/UNGROUP 480
L7．6．2 Permanent Batching--COMBINE 482
L7．7 Attaching one or More Entities to Another Entity 484
L7．7．1 PeFmanent Attachment--JOIN 484
L7．7．2 Temporarv Attachment—LOAD/UNLOAD 486
L7．8 Accumulation of Entities 489
L7．9 Splitting of One Entity into Multiple Entities 490
L7．10 Decision Statements 492
L7．10．1 IF-THEN-ELSE Statement 492
L7．10．2 WHILE-Do Loop 494
L7．10．3 DO-WHILE Loop 495
L7．10．4 GOTO Statement 496
L7．11 Periodic System Shutdown 498
L7．12 Exercises 500
8 Model Verification and Validation 509
L8．1 Verifcation of an Inspection and Rework Model 509
L8．2 Verification by Tracing the Simulation Model 511
L8．3 Debugging the Simulation Model 513
L8．3．1 Debugging ProModel Lgic 514
L8．3．2 Basic Debugger Options 514
L8．3．3 Advanced Debugger Options 516
L8．4 Exercises 517
9 Simulation Output Analysis 51 9
L9．1 Terminating versus NonteFminating Simulations 519
L9．2 Terminating Simulation 520
L9．2．1 Starting and Terminating Conditions (Run Length) 521
L9．2．2 Replications 522
L9．2．3 Required Number of Replications 526
L9．2．4 Simulation Output Assumptions 526
L9．3 Nonterminating Simulation 529
L9．3．1 Warm-up Time and Run Length 531
L9．3．2 Replications or Batch Intervals 535
L9．3．3 Required Batch Interval Length 538
L9．4 Exercises 540
10 Comparing Alternative Systems 543
L10．1 Overview of Statistical Methods 543
LI0．2 Three Alternative Systems 544
L10．3 Common Random Numbers 547
L10．4 BonferroniApproach with Paired-t Confidence Intervals 548
L10．5 Exercises 551
12 Intermediate Modeling Concepts 579
LI2．1 Attributes 579
L12．1．1 Using Attributes to Track Customer Types 580
L12．2 CycleTime 582
L12．3 Sorting， Inspecting a Sample， and Rework 583
L12．4 Merging a Submodel 584
L12．5 Preventive Maintenance and Machine Breakdowns 586
L12．5．1 Downtime Using MTBF and MTTR Data 587
L12．5．2 Downtime Using MTTF and MTTR Data 588
L12．6 Operator Shifts 591
L12．7 Job Shop 594
L12．8 Modeling Priorities 596
L12．8．1 Selecting among Upstream Processes 596
L12．8．2 Selecting Resources 598
L12．9 MOdeling a Pull System 602
L12．9．1 Pull Based on Downstream Demand 602
L12．9．2 Kanban Svstem 603
L12．10 Trackjng Cost 607
L12．11 Importing a Background 6l1
L12．12 Denning and Displaying Views 612
L12．13 Creating a Model Package 615
L12．14 Exercises 617
13 Material HandIi ng Concepts 623
L13．1 Convevors 623
L13．1．1 Multiple Coliveyors 624
L13．2 Resources，Path Networks，and Interfaces 625
L13．2．1 Manual Material Handljng Svstems 626
L13．2．2 Manual versus Automated Material Handing Systems 628
L13．2．3 Using Operator for Processing 632
L13．2．4 Automated Manufacturing Cell 632
L13．3 Crane Svstems 636
L13．4 Exercises 638
Reference 645
14 Additional Modeling Concepts 647
L14．1 Balking of Customers 647
L14．2 Macros and Runtime Interface 649
L14．3 Generating Scenarios 653
L14．4 External Files 655
L14．5 Arravs 658
L14．6 Table Functions 663
L14．7 Subroutines 666
L14．8 Arrival Cycles 670
L14．9 User Distributions 673
L14．10 Random Number Streams 675
L14．11 Exercises 677
PART III
CASE STUDY ASSIGNMENTS
Case 1 Toy Airplane Manufacturing 683
Case 2 Mi Cazuela--Mexican Restaurant 683
Case 3 Jai Hind Cycles Inc． Plans New Production Facility 685
Case 4 The FSB Coin System 688
Case 5 Automated Warehousing at Athletic Shoe Company 690
Case 6 Concentrate Line at Florida Citrus Company 692
Case 7 Balancing the Production Line at Southern California Door Company 698
Case 8 Material Handling at California Steel Industries， Inc． 705
Appendix A Common Continuous and Discrete Distributions 709
Appendix B Critical Values for Student's t Distribution and Standard Normal Distribution 724
Appendix C F Distribution for α=0．05 725
Appendix D Critical Values for Chi-Square Distribution 726
Index ...727
1 Introduction to Simulation 3
1．1 Introduction 3
1．2 What Is Simulation? 5
1．3 Why Simulate? 6
1．4 Doing Simulation 8
1．5 Use of Simulation 10
1．6 When Simulation Is Appropriate 12
1．7 Qualifications for Doing Simulation 1 4
1．8 Economic Justification of Simulation 15
1．9 Sources of Information on Simulation 19
1．10 How to Use This Book 19
1．11 Summary 20
1．12 Review Questions 20
References 21
2 System Dynamics 23
2．1 Introduction 23
2．2 System Definition 24
2．3 System Elements 25
2．3．1 Entities 26
.2．3．2 Activities 26
2．3．3 Resources 26
2．3．4 Controls 27
2．4 System Complexity 27
2．4．1 Interdependencies 28
2．4．2 Variability 29
2．5 System Performance Metrics 31
2．6 System Variables 33
2．6．1 Decision Variables 33
2．6．2 Response Variables 34
2．6．3 State Vailables 34
2．7 System Optimization 34
2．8 The Systems Approach 36
2．8．1 Identifying Problems and Opportunities 37
2．8．2 Developing Alternative Solutions 37
2．8．3 Evaluating the Solutions 38
2．8．4 Selecting and Implementing the Best Solution 38
2．9 Systems Analysis Techniques 38
2．9．1 Hand Calculations 40
2．9．2 Spreadsheets 40
2．9．3 Operations Research Techniques 41
2．9．4 Special Computerized Tools 44
2．10 Summary 45
2．11 Review Questions 45
References 46
3 Simulation Basics 47
3．1 Introduction 47
3．2 Types of Simulation 47
3．2．1 Static versus Dynamic Simulation 48
3．2．2 Stochastic versus Deterministic Simulation 48
3．3 Random Behavior 49
3．4 Simulating Random Behavior 50
3．4．1 Generating Random Numbers 50
3．4．2 Generating Random Variates 55
3．5 Simple Spreadsheet Simulation 59
3．5．1 Simulating Random Variates 60
3．5．2 Simulating Dynamic，Stochastic Systems 64
3．5．3 Simulation Replications and Output Analysis 66
3．6 Summary 67
3．7 Review Questions 68
References 69
4 Discrete-Event Simulation 71
4．1 Introduction 71
4．2 Discrete-Event versus Continuous Simulation 72
4．2．1 Differential Equations 73
4．2．2 Difference Equations 73
4．2．3 Combined Continuous and Discrete Simulation 74
4．3 How Discrete-Event Simulation Works 74
4．4 A Manual Discrete-Event Simulation Example 77
4．4．1 Simulation Model Assumptions 77
4．4．2 Setting Up the Simulation 78
4．4．3 Running the Simulation 80
4．4．4 Calculating Results 86
4．4．5 Issues 89
4．5 Commercial Simulation Software 89
4．5．1 Modeling Interface Module
4．5．2 Model Processor 90
4．5．3 Simulation Interface Module 90
4．5．4 Simulation Processor 91
4．5．5 Animation Processor 91
4．5．6 Output Processor 92
4．5．7 Output Interface Module 92
4．6 Simulation Using ProModel 93
4．6．1 Building a Model 93
4．6．2 Running the Simulation 93
4．6．3 Output Analysis 94
4．7 Languages versus Simulators 97
4．8 Future of Simulation 98
4．9 Summarv 99
4．10 Review Questions 100
References 101
5 Getting Started 103
5．1 Introductin 103
5．2 Preliminary Activities 104
5．2．1 Selecting an Application 104
5．2．2 Personnel Identification 105
5．2．3 Software Selection 106
5．3 Simulation Procedure 107
5．4 Defining the Objective 109
5．5 Defining the Scope of Work 112
5．5．1 Determining Model Scode 113
5．5．2 Deciding on Level of Detail 113
5．5．3 Assigning Data—Gathering Resnonsibilities 114
5．5．4 Planning the Experimentation 115
5．5．5 Determining the Form of Results 115
5．6 Defining Project Requirements 116
5．7 Reasons Why Simulation Projects Fail 117
5．8 Summary 117
5．9 Review Questions 118
5．10 Case Studies 119
Case Study A: AST Computes Big Benefits Using Simulation 119
Case Study B: Durham Regional Hospital Saves $150，000 Annually Using Simulation Tools 122
References 124
6 Data Collection and Analysis 125
6．1 Introduction 125
6．2 Guidelines for Data Gathering 126
6．3 Determining Data Requirements 128
6．3．1 Structural Data 128
6．3．2 Operational Data 128
6．3．3 Numerical Data 129
6．3．4 Use of a Questionnaire 129
6．4 Identifying Data Sources 130
6．5 Collecting the Data 131
6．5．1 Defining the Entity Flow 131
6．5．2 Developing a Description of Operation 132
6．5．3 Defining Incidental Details and Refining Data Values 133
6．6 Making Assumptions 134
6．7 Statistical Analysis of Numerical Data 135
6．7．1 Tests for Independence 137
6．7．2 Tests for Identically Distributed Data 142
6．8 Distribution Fitting 144
6．8．1 Frequency Distributions 145
6．8．2 Theoretical Distributions 146
6．8．3 Fitting Theoretical Distrjbutions to Data 152
6．9 Selecting a Distribution in the Absence of Data 158
6．9．1 Most Likely or Mean Value 158
6．9．2 Minimum and Maximum Values 159
6．9．3 Minimum，Most Likely，and Maximum Values 159
6．10 Bounded versus Boundless Distributions 161
6．11 Modeling Discrete Probabilities Using Continuous Distributions 161
6．12 Data Documentation and Approval 1 62
6．12．1 Data Documeiltation Example 162
6．13 Summary 165
6．14 Review Ouestioils 165
6．15 Case Study：Collecting and Documenting Data for Harry's Drive-Through Restaurant 167
References 169
7 Model Building 171
7．1 Introduction 171
7．2 Converting a Conceptual Model to a Simulation Model 172
7．2．1 Modeling Paradigms 172
7．2．2 Model Definition 174
7．3 Structural Elements 175
7．3．1 Entities 175
7．3．2 Locations 177
7．3．3 Resources 179
7．3．4 Paths 181
7．4 Operational Elements 181
7．4．1 Routings 181
7．4．2 Entity Operations 182
7．4．3 Entity Arrivals 185
7．4．4 Entity and Resource Movement 187
7．4．5 Accessin Locations and Resotlrces 188
7．4．6 Resource Scheduling 190
7．4．7 Downtimes and Repairs 191
7．4．8 Use of Programming Logic 195
7．5 Miscellaneous Modeling Issues 197
7．5．1 Modeling Rare Occurrences 197
7．5．2 Large-Scale Modeling 197
7．5．3 Cost Modeling 198
7．6 Summary 199
7．7 Review Questions 199
References 201
8 Model Verification and Validation 203
8．1 Introduction 203
8．2 Importance of Model Verification and Validation 204
8．2．1 Reasons for Neglect 204
8．2．2 Practices That Facilitate Verification and Validation 205
8．3 Model Verification 206
8．3．1 Preventive Measures 207
8．3．2 Establishing a Standard for Comparison 208
8．3．3 Verification Techniques 208
8．4 Model Validation 212
8．4．1 Determining Model Validity 213
8．4．2 Maintaining Validation 215
8．4．3 Validation Examples 215
8．5 Summary 219
8．6 Review Questions 220
References 220
9 Simulation Output Analysis 221
9．1 Introduction 221
9．2 Statistical Analysis of Simulation Output 222
9．2．1 Simulation Replications 223
9．2．2 Performance Estimation 224
9．2．3 Number of Replications (Sample Size) 228
9．2．4 Real-World Experiments versus Simulation Experiments 231
9．3 Statistical Issues with Simulation Output 232
9．4 Terminating and Nonterminating Simulations 235
9．4．1 Terminating Simulations 236
9．4．2 Nonterminating Simulations 236
9．5 Experimenting with Terminating Simulations 237
9．5．1 Selecting the Initial Model State 238
9．5．2 Selecting a Terminating Event 238
9．5．3 Determining the Number of Replications 238
9．6 Experimenting with Nonterminating Simulations 239
9．6．1 Determining the Warm-up Period 239
9．6．2 Obtaining Sample Observations 244
9．6．3 Determining Run Length 249
9．7 Summary 250
9．8 Review Questions 251
References 252
10 Comparing Systems 253
10．1 Introduction 253
10．2 Hypothesis Testing 254
10．3 Comparing Two Alternative System Designs 257
10．3．1 Welch Confidence Interval for Comparing Two Systems 258
10．3．2 Paired-t Confidence Interval for Comparing Two Systems 260
10．3．3 Welch versus the Paired-t Confidence Interval 262
10．4 Comparing More Than Two Alternative System Designs.. 263
10．4．1 The Bonferroni Approach for Comparing More Than Two Alternative Systems
10．4．2 Advanced Statistical Models for Comparing More Than Two Alternative Systems 268
10．4．3 Factorial Design and Optimization 274
10．5 Variance Reduction Techniques 276
10．5．1 Common Random Numbers 276
10．5．2 Example Use of Common Random Numbers 279
10．5．3 Why Common Random Numbers Work 281
10．6 Summary 281
10．7 Review Questions 282
References 283
12 Modeling Manufacturing Systems 311
12．1 Introduction 311
12．2 Characteristics of Manufacturing Systems 312
12．3 Manufacturing Terminology 313
12．4 Use of Simulation in Manufacturing 315
12．5 Applications of Simulation in Manufacturing 316
12．5．1 Methods Analysis 317
12．5．2 Plant Layout 318
12．5．3 Batch Sizing 320
12．5．4 Production Control 321
12．5．5 Inventory Control 324
12．5．6 Supply Chain Management 325
12．5．7 Production Scheduling 326
12．5．8 Real-Time Control 327
12．5．9 Emulation 327
12．6 Manufacturing Modeling Techniques 328
12．6．1 Modeling Machine Setup 328
12．6．2 Modeling Machine Load and Unload Time 328
12．6．3 Modeling Rework and Scrap 329
12．6．4 Modeling Transfer Machines 329
12．6．5 Continuous Process Systems 331
12．7 Summary 332
12．8 Review Ouestions 332
References 332
13 Modeling MateriaI Handling Systems 335
13．1 Introdtiction 335
13．2 Material Handling Principles 335
13．3 Material Handling Classification 336
13．4 Conveyors 337
13．4．1 Conveyor Types 337
13．4．2 Operational CharactedsticS 339
13．4．3 Modeling Conveyor Systems 340
13．4．4 Modeling Single-Section Conveyors 341
13．4．5 Modeling Conveyor Networks 342
13．5 Industrial Vehicles 342
13．5．1 Modeling Industrial Vehicles 343
13．6 Automated Storage/Retrieval Systems 343
13．6．1 Configuring an AS/RS 344
13．6．2 Modeling AS/RSs 346
13．7 Carousels 347
13．7．1 Carousel Configurations 347
13．7．2 Modeling Carousels 347
13．8 Automatic Guided Vehicle Systems 348
13．8．1 Designing an AGVS 349
13．8．2 Controllingan AGVS 350
13．8．3 Modeling an AGVS 35l
13．9 Cranes and Hoists 352
13．9．1 Crane Management 352
13．9．2 Modeling Bridge Cranes 352
13．10 Robots 353
13．10．1 Robot Control 353
13．10．2 Modeling Robots 354
13．11 Summarv 355
13．12 Review Questions 355
References 356
14 Modeling Service Systems 357
14．1 Introduciton 357
14．2 Characteristics of Service Systems 358
14．3 Performance Measures 359
14．4 Use of Simulation in Service Systems 360
14．5 Applications of Simulation in Service Industries 362
14．5．1 Process Design 362
14．5．2 Method Selection 362
14．5．3 System Layout 363
14．5．4 Staff Planning 363
14．5．5 Flow Control 364
14．6 Types of Service Systems 364
14．6．1 Service Factory 364
14．6．2 Pure Service Shop 365
14．6．3 Retail Service Store 365
14．6．4 Professional Service 366
14．6．5 Telephonic Service 366
14．6．6 Delivery Service 367
14．6．7 Transportation Service 367
14．7 Simulation Example: A Help Desk Operation 367
14．7．1 Background 368
14．7．2 Model Description 368
14．7．3 Results 371
14．8 Summary 372
14．9 Review Questions 372
References 372
PART II LABS
1 Introduction to ProModel 6．0 377
L I．1 ProModel 6．0 Opening Screen 378
L I．2 Simulation in Decision Making 379
LI．2．1 Average Waiting Time 380
LI．2．2 Maximum Queue Length 281
L1．3 Exercises 382
2 ProModel World View，Menu，and Tutorial 383
L2．1 Introduction to the ProModel Menu 383
L2．1．1 The Title and the Menu Bars 383
L2．1．2 File Menu 384
L2．1．3 Edit Menu 384
L2．1．4 Build Menu 385
L2．1．5 Simulation Menu 386
L2．1．6 Output Menu 387
L2．1．7 Tools Menu 387
L2．1．8 View Menu 388
L2．1．9 Window Menu 389
L2．1．10 Help Menu 389
L2．2 Basic Modeling Elemellts 390
L2．2．1 Letatioils 390
L2．2．2 Entities 390
L2．2．3 Arrivals 39l
L2．2．4 Precessing 392
L2．3 Innovative Feattires in ProModel 393
L2．3．1 Logic Builder 393
L2．3．2 Dynamic Plots 395
L2．3．3 Customize 397
L2．3．4 Ouick Bar 397
L2．4 A Tutorial On PreModel 6．0 399
L2．5 Exercises 400
3 Running a ProModel Simulation 403
L3．1 ATM System Specincatioils and Problem Statement 403
L3．1．1 Queuing Theory's Answer to the ATM System 404
L3．1．2 PreModel's Answer to the ATM Svstem 404
L3．2 Exercises 406
4 Building Your First Model 409
L4．1 Building Your First Simulation Model 409
L4．2 Building the Bank of USA ATM Model 416
L4．3 Locations，Entities，Precessing，and Arrivals 423
L4．4 Add Location 428
L4．5 Effect of Variability on Model Performance 430
L4．6 Blocking 431
L4．7 Exercises 433
5 ProModel's Output Module 437
L5．1 The Output Program Manager 437
L5．1．1 ReportView 439
L5．1．2 Category Chart 439
L5．1．3 State Chart 441
L5．1．4 Histogram and Time Plot 445
L5．1．5 Sheet Properties 448
L5．2 Classic View 448
L5．2．1 Time Series Plot 450
L5．2．2 Time Series Histogram 450
L5．2．3 Location State Graphs 450
L5．3 Exercises 453
6 Fitting Statistical Distributions to Input Data 455
L6．1 An Introduction to Stat::Fit 455
L6．2 An Example Problem 458
L6．3 Auto::Fit Input Data 460
L6．4 Exercises 463
7 Basic Modeling Concepts 465
L7．1 Multiple Locations，Multiple Entity Types 465
L7．2 Multiple Parallel Identical Locations 468
L7．3 Routing Rules 471
L7．4 Variables 475
L7．5 Uncertainty in Routing--Track Defects And Rework 478
L7．6 Batching Multiple Entities of Similar Type 480
L7．6．1 Temporary Batching--GROUP/UNGROUP 480
L7．6．2 Permanent Batching--COMBINE 482
L7．7 Attaching one or More Entities to Another Entity 484
L7．7．1 PeFmanent Attachment--JOIN 484
L7．7．2 Temporarv Attachment—LOAD/UNLOAD 486
L7．8 Accumulation of Entities 489
L7．9 Splitting of One Entity into Multiple Entities 490
L7．10 Decision Statements 492
L7．10．1 IF-THEN-ELSE Statement 492
L7．10．2 WHILE-Do Loop 494
L7．10．3 DO-WHILE Loop 495
L7．10．4 GOTO Statement 496
L7．11 Periodic System Shutdown 498
L7．12 Exercises 500
8 Model Verification and Validation 509
L8．1 Verifcation of an Inspection and Rework Model 509
L8．2 Verification by Tracing the Simulation Model 511
L8．3 Debugging the Simulation Model 513
L8．3．1 Debugging ProModel Lgic 514
L8．3．2 Basic Debugger Options 514
L8．3．3 Advanced Debugger Options 516
L8．4 Exercises 517
9 Simulation Output Analysis 51 9
L9．1 Terminating versus NonteFminating Simulations 519
L9．2 Terminating Simulation 520
L9．2．1 Starting and Terminating Conditions (Run Length) 521
L9．2．2 Replications 522
L9．2．3 Required Number of Replications 526
L9．2．4 Simulation Output Assumptions 526
L9．3 Nonterminating Simulation 529
L9．3．1 Warm-up Time and Run Length 531
L9．3．2 Replications or Batch Intervals 535
L9．3．3 Required Batch Interval Length 538
L9．4 Exercises 540
10 Comparing Alternative Systems 543
L10．1 Overview of Statistical Methods 543
LI0．2 Three Alternative Systems 544
L10．3 Common Random Numbers 547
L10．4 BonferroniApproach with Paired-t Confidence Intervals 548
L10．5 Exercises 551
12 Intermediate Modeling Concepts 579
LI2．1 Attributes 579
L12．1．1 Using Attributes to Track Customer Types 580
L12．2 CycleTime 582
L12．3 Sorting， Inspecting a Sample， and Rework 583
L12．4 Merging a Submodel 584
L12．5 Preventive Maintenance and Machine Breakdowns 586
L12．5．1 Downtime Using MTBF and MTTR Data 587
L12．5．2 Downtime Using MTTF and MTTR Data 588
L12．6 Operator Shifts 591
L12．7 Job Shop 594
L12．8 Modeling Priorities 596
L12．8．1 Selecting among Upstream Processes 596
L12．8．2 Selecting Resources 598
L12．9 MOdeling a Pull System 602
L12．9．1 Pull Based on Downstream Demand 602
L12．9．2 Kanban Svstem 603
L12．10 Trackjng Cost 607
L12．11 Importing a Background 6l1
L12．12 Denning and Displaying Views 612
L12．13 Creating a Model Package 615
L12．14 Exercises 617
13 Material HandIi ng Concepts 623
L13．1 Convevors 623
L13．1．1 Multiple Coliveyors 624
L13．2 Resources，Path Networks，and Interfaces 625
L13．2．1 Manual Material Handljng Svstems 626
L13．2．2 Manual versus Automated Material Handing Systems 628
L13．2．3 Using Operator for Processing 632
L13．2．4 Automated Manufacturing Cell 632
L13．3 Crane Svstems 636
L13．4 Exercises 638
Reference 645
14 Additional Modeling Concepts 647
L14．1 Balking of Customers 647
L14．2 Macros and Runtime Interface 649
L14．3 Generating Scenarios 653
L14．4 External Files 655
L14．5 Arravs 658
L14．6 Table Functions 663
L14．7 Subroutines 666
L14．8 Arrival Cycles 670
L14．9 User Distributions 673
L14．10 Random Number Streams 675
L14．11 Exercises 677
PART III
CASE STUDY ASSIGNMENTS
Case 1 Toy Airplane Manufacturing 683
Case 2 Mi Cazuela--Mexican Restaurant 683
Case 3 Jai Hind Cycles Inc． Plans New Production Facility 685
Case 4 The FSB Coin System 688
Case 5 Automated Warehousing at Athletic Shoe Company 690
Case 6 Concentrate Line at Florida Citrus Company 692
Case 7 Balancing the Production Line at Southern California Door Company 698
Case 8 Material Handling at California Steel Industries， Inc． 705
Appendix A Common Continuous and Discrete Distributions 709
Appendix B Critical Values for Student's t Distribution and Standard Normal Distribution 724
Appendix C F Distribution for α=0．05 725
Appendix D Critical Values for Chi-Square Distribution 726
Index ...727
