标题：系统仿真及ProModel软件应用（第2版）
图书信息
作者：Charles Harrell, Biman K. Ghos 
图书详细信息： ISBN：9787302099826 定价：68元 印次：1-2 装帧：平装 印刷日期：2007-5-17
图书简介
本书从分析离散事件系统的动态特性开始，介绍了系统仿真的基本概念与方法。结合ProModel仿真软件的使用，讨论了数据收集与分析、仿真模型构建、模型验证与确认的方法与过程。对输出分析的基本方法、不同系统配置的性能比较、仿真过程优化的策略与方法也进行了详细的阐述。针对制造系统、物料搬运、服务系统的特点，描述了仿真应用的典型问题，提供了建模的方法与技巧。 本书用了近一半的篇幅，为读者提供了14个教学实验的指导，从开始动手使用ProModel软件，到最后能够进行复杂系统的建模与仿真分析，实现了从基本理论到应用实践的顺利过渡。本书在最后还提供了8个应用案例，供学习者一试身手。
图书前言
本教材系列的出版正值中国学术界工业工程学科经历巨大发展、实际工作中对工业工程的概念、方法和工具的使用兴趣日渐浓厚之时。在实际工作中有效地应用工业工程的手段将无疑会提高生产率、工作质量、合作的满意度和效果。该系列中的书籍对工业工程的本科生、研究生和工业界中需要解决工程系统设计、运作和管理诸方面问题的人士最为适用。加弗瑞尔·沙尔文迪清华大学工业工程系普渡大学工业工程学院（美国）2002年4月
图书目录
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]