Simulation of industrial systems (1)

SIMULATION OF INDUSTRIAL SYSTEMS CRC_AU6744_Fm.indd i 11/12/2007 9:08:59 PM ENGINEERING AND MANAGEMENT INNOVATION SERIES Hamid R Parsaei and Ali K Kamrani, Series Advisors University of Houston, Houston, TX Facility Logistics: Approaches and Solutions to Next Generation Challenges Maher Lahmar ISBN: 0-8493-8518-0 Simulation of Industrial Systems: Discrete Event Simulation Using Excel/VBA David Elizandro and Hamdy Taha ISBN: 1-4200-6744-3 Additional Titles in RESOURCE MANAGEMENT SERIES Rightsizing Inventory by Joseph L Aiello ISBN: 0-8493-8515-6 Integral Logistics Management: Operations and Supply Chain Management in Comprehensive Value-Added Networks, Third Edition by Paul Schönsleben ISBN: 1-4200-5194-6 Supply Chain Cost Control Using Activity-Based Management Sameer Kumar and Matthew Zander ISBN: 0-8493-8215-7 Financial Models and Tools for Managing Lean Manufacturing Sameer Kumar and David Meade ISBN: 0-8493-9185-7 RFID in the Supply Chain Judith M Myerson ISBN: 0-8493-3018-1 Handbook of Supply Chain Management, Second Edition by James B Ayers ISBN: 0-8493-3160-9 ERP: Tools, Techniques, and Applications for Integrating the Supply Chain by Carol A Ptak with Eli Schragenheim ISBN: 1-57444-358-5 Introduction to e-Supply Chain Management: Engaging Technology to Build Market-Winning Business Partnerships by David C Ross ISBN: 1-57444-324-0 Supply Chain Networks and Business Process Orientation by Kevin P McCormack and William C Johnson with William T Walker ISBN: 1-57444-327-5 Collaborative Manufacturing: Using Real-Time Information to Support the Supply Chain by Michael McClellan ISBN: 1-57444-341-0 The Supply Chain Manager s Problem-Solver: Maximizing the Value of Collaboration and Technology by Charles C Poirier ISBN: 1-57444-335-6 The Portal to Lean Production: Principles & Practices for Doing More With Less by John Nicholas and Avi Soni ISBN: 0-8493-5031-X Lean Performance ERP Project Management: Implementing the Virtual Lean Enterprise, Second Edition by Brian J Carroll ISBN: 0-8493-0532-2 Supply Market Intelligence: A Managerial Handbook for Building Sourcing Strategies by Robert B Handfield ISBN: 0-8493-2789-X Integrated Learning for ERP Success: A Learning Requirements Planning Approach by Karl M Kapp, with William F Latham and Hester N Ford-Latham ISBN: 1-57444-296-1 The Small Manufacturer s Toolkit: A Guide to Selecting the Techniques and Systems to Help You Win by Steve Novak ISBN: 0-8493-2883-7 Basics of Supply Chain Management by Lawrence D Fredendall and Ed Hill ISBN: 1-57444-120-5 Velocity Management in Logistics and Distribution: Lessons from the Military to Secure the Speed of Business by Joseph L Walden ISBN: 0-8493-2859-4 Supply Chain for Liquids: Out of the Box Approaches to Liquid Logistics by Wally Klatch ISBN: 0-8493-2853-5 Supply Chain Architecture: A Blueprint for Networking the Flow of Material, Information, and Cash by William T Walker ISBN: 1-57444-357-7 CRC_AU6744_Fm.indd ii Lean Manufacturing: Tools, Techniques, and How to Use Them by William M Feld ISBN: 1-57444-297-X Back to Basics: Your Guide to Manufacturing Excellence by Steven A Melnyk and R.T Chris Christensen ISBN: 1-57444-279-1 Enterprise Resource Planning and Beyond: Integrating Your Entire Organization by Gary A Langenwalter ISBN: 1-57444-260-0 ISBN: 0-8493-8515-6 11/12/2007 9:09:00 PM SIMULATION OF INDUSTRIAL SYSTEMS Discrete Event Simulation Using Excel/VBA David Elizandro • Hamdy Taha New York CRC_AU6744_Fm.indd iii London 11/12/2007 9:09:00 PM Microsoft, Windows, and Excel are registered trademarks of Microsoft Corporation in the United States and/ or other countries DEEDS is a copyright of David Elizandro CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2007 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S Government works Version Date: 20140313 International Standard Book Number-13: 978-1-4200-6745-3 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint Except as permitted under U.S Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers For permission to photocopy or use material electronically from this work, please access www.copyright com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400 CCC is a not-for-profit organization that provides licenses and registration for a variety of users For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Dedication To Marcia and Karen CRC_AU6744_Fm.indd v 11/12/2007 9:09:00 PM CRC_AU6744_Fm.indd vi 11/12/2007 9:09:01 PM Contents Preface xv Acknowledgments xxi The Authors xxiii PART I SIMULATION FUNDAMENTALS Simulation Modeling 1.1 Why Simulate? .3 1.2 Types of Simulation .5 1.3 The Simulation Clock 1.4 Randomness in Simulation 1.5 Discrete Simulation Languages 1.6 Design Environment for Event-Driven Simulation .8 1.7 The Two Sides of Simulation 1.8 Organization of the Book 10 For Further Reading 11 Problems .11 Probability and Statistics in Simulation .13 2.1 Role of Probability and Statistics in Simulation 13 2.2 Characterization of Common Distributions in Simulation 14 2.2.1 Properties of Common Distributions .14 2.2.1.1 Uniform Distribution 14 2.2.1.2 Negative Exponential Distribution 15 2.2.1.3 Gamma (Erlang) Distribution 16 2.2.1.4 Normal Distribution 17 2.2.1.5 Lognormal Distribution 17 2.2.1.6 Weibull Distribution 18 2.2.1.7 Beta Distribution .19 2.2.1.8 Triangular Distribution 19 2.2.1.9 Poisson Distribution 20 vii CRC_AU6744_Fm.indd vii 11/12/2007 9:09:01 PM viii ■ Contents 2.2.2 Identifying Distribution on the Basis of Historical Data 21 2.2.2.1 Building Histograms 21 2.2.2.2 Goodness-of-Fit Tests 23 2.2.2.3 Maximum Likelihood Estimates of Distribution Parameters .26 2.3 Statistical Output Analysis 27 2.3.1 Confidence Intervals .27 2.3.1.1 Satisfying the Normality Assumption in Simulation 29 2.3.2 Hypothesis Testing 29 2.4 Summary 32 References 32 Problems .33 Elements of Discrete Simulation 37 3.1 Concept of Events in Simulation 37 3.2 Common Simulation Approaches .38 3.2.1 Event-Scheduling Approach 38 3.2.2 Activity-Scanning Approach 44 3.2.3 Process-Simulation Approach 46 3.3 Computations of Random Deviates 48 3.3.1 Inverse Method 48 3.3.2 Convolution Method 51 3.3.3 Acceptance–Rejection Method .53 3.3.4 Other Sampling Methods .55 3.3.5 Generation of (0, 1) Random Numbers 56 3.4 Collecting Data in Simulation 57 3.4.1 Types of Statistical Variables 57 3.4.2 Histograms .59 3.4.3 Queue and Facility Statistics in Simulation 63 3.4.3.1 Queue Statistics .63 3.4.3.2 Facility Statistics 65 3.5 Summary 68 References 68 Problems .68 Gathering Statistical Observations in Simulation 73 4.1 Introduction .73 4.2 Peculiarities of the Simulation Experiment .73 4.2.1 Issue of Independence 74 4.2.2 Issue of Stationarity (Transient and Steady-State Conditions) .74 4.2.3 Issue of Normality 76 CRC_AU6744_Fm.indd viii 11/12/2007 9:09:01 PM Contents ■ ix 4.3 Peculiarities of the Simulation Experiment .76 4.3.1 Normality and Independence 77 4.3.2 Transient Conditions 78 4.4 Gathering Simulation Observations 80 4.4.1 Subinterval Method 80 4.4.2 Replication Method 83 4.4.3 Regenerative Method 84 4.5 Variance Reduction 86 4.6 Summary 87 References 88 Problems .88 Overview of DEEDS .89 5.1 5.2 5.3 5.4 Introduction .89 DEEDS Modeling Philosophy 89 Basic Elements of DEEDS 91 Basic Features of DEEDS 93 5.4.1 Network Representation 93 5.4.2 Time Management (Simulation Clock) 93 5.4.3 DEEDS Class Definitions 94 5.4.4 User’s Files Management 94 5.4.5 Generation of Random Samples .96 5.4.6 Statistical Observations Gathering 96 5.4.7 Interactive Debugging and Trace 96 5.4.8 Computations of Mathematical Expressions .98 5.4.9 Initialization Capabilities .98 5.4.10 Output Capabilities 98 5.4.11 Model Documentation 99 5.5 Develop and Execute a DEEDS Model 99 5.6 Summary 99 DEEDS Network Representation 101 6.1 Components of the DEEDS Model 101 6.1.1 DEEDS Nodes .101 6.1.2 DEEDS Transactions 102 6.1.3 DEEDS Lists 102 6.1.4 DEEDS Classes and Procedures 103 6.1.5 DEEDS Simulation Program .104 6.2 Program Initial Conditions 108 6.3 Summary 110 CRC_AU6744_Fm.indd ix 11/12/2007 9:09:01 PM Index facility sheet, 211–212 forced model termination, 208 messages, 207 model verification, 214–218 observation gathering, 205–207 queue sheet, 209–210 source sheet, 209 standard output, 209–214 statistics sheet, 212–213 trace report, 215–217 user-defined simulator messages, 214–215 UserOutput sheet, 213–214 VBA interactive debugger, 218–223 simulation project management constants, decision variables, and constraints, 283–286 data specifications, 286–288 design/conduct experiments, 291–292 design validation, 290 model development, 290–291 overview, 281 preliminary design, 290 problem definition, 289–290 specifications, 281–283 summarize/present results, 292 verify model, 291 simulation results analysis collection report, 217–218 delay sheet, 212 execution monitoring, 207–208 facility sheet, 211–212 forced model termination, 208 messages, 207 misuse of, 225–227 model verification, 214–218 observation gathering, 205–207 queue sheet, 209–210 source sheet, 209 standard output, 209–214 statistics sheet, 212–213 trace report, 215–217 transient conditions, 227–232 user-defined simulator messages, 214–215 UserOutput sheet, 213–214 VBA interactive debugger, 218–223 statistical observations gathering, 96 time management, 93–94 user’s fi les management, 94–96 CRC_AU6744_Index.indd 499 ■ 499 Visual Basic for Applications (VBA) software arrays, 128–131 assignment statements, 117–119 constants, 115–116 control structures, 119–124 Case structure, 121–123 Do structure, 123–124 If structure, 119–121 logical operators, 119 For structure, 123 data types, 113–114 expressions, 116–117 procedures, 124–128 functions, 128 sub procedure, 125–128 programming features, names, 113 summary of features, 131–132 variable definitions, 114–115 destination function model development applications, transaction attributes, 181 select routing, 261–265 Detach function, model development applications, queue nodes and transactions, 166–169 discount store inventory control model, 343–348 discrete distribution inverse method, 50–51 model development applications, 183–185 discrete simulation acceptance-rejection method, 53–55 activity-scanning approach, 44–46 basic elements of, 37 classification, clock model, 6–7 convolution method, 51–53 data collection, 57–68 facility statistics, 65–68 histograms, 59–63 queue statistics, 63–65 statistical variables, 57–59 event-scheduling approach, 38–44 inverse method, 48–51 languages, 7–8 process-simulation approach, 46–48 quality control models, 397–410 random deviate computations, 48–57 randomness, random number generation, 56–57 sampling methods, 55–56 10/29/2007 7:12:37 PM 500 ■ Index distribution characterization, simulation modeling, 14–27 beta distribution, 19 chi-square test, 23–25 gamma (Erlang) distribution, 16 goodness-of-fit tests, 23 histograms, 21–23 historical data identification, 21 Kolmogrov-Smirnov test, 26 lognormal distribution, 17–18 maximum likelihood estimates, 26–27 negative exponential distribution, 15–16 normal distribution, 17 Poisson distribution, 20 triangular distribution, 19–20 uniform distribution, 14–15 Weibull distribution, 18 distribution functions, model development applications, 186–187 documentation process, design environment for event-driven simulation (DEEDS), 99 DoorSearch function, cross dock supply model, 438–439 DoorSwitchDelayEvent, cross dock supply model, 435–439 Do structure, Visual Basic for Applications (VBA) programming, 123–124 DropOff Job, facilities layout models, flexible manufacturing environment, 313 DuplicateChromosome sub function, genetic algorithm, 459–464 E End-of-Run statistics, simulation output, 213–214 EngageAndService function, model development applications, facility nodes and transactions, 171–176 Engage function, model development applications, facility nodes and transactions, 171–176 Erlang distribution discrete simulation acceptance-rejection method, 54–55 convolution method, 51–52 simulation modeling, 16 CRC_AU6744_Index.indd 500 event-driven simulation design environment, 8–9 event-scheduling approach, 38–44 event-scheduling languages, discrete simulation, Excel software design environment for event-driven simulation (DEEDS), 91–99 development and execution routines, 99 mathematical computation, 98 histograms, 489–494 model development applications, WorksheetFunction examples, 188–191 VBA interactive debugger, 219–223 exclusive routing, advanced routing transactions, 267–269 execution, simulation monitoring during, 207–208 experimental design, advanced analysis techniques, 448–450 expressions, Visual Basic for Applications (VBA) programming, 116–117 F facilities layout models flexible manufacturing environment, 306–317 line balancing, 296–305 process layout, 295 product layout, 295 facilities output function automatic warehouse operation model, 429–430 belt conveyor-plywood mill operation, 341–342 carrousel conveyor materials handling model, 333–334 continuous inventory review, 356–357 discount store inventory control model, 347–348 facilities layout models, flexible manufacturing environment, 317 job shop scheduling model, 367 maintenance models, 395–396 manpower scheduling models, 378–379 overhead crane materials-handling model, 329–330 10/29/2007 7:12:37 PM Index port supply chain models, 420 reliability models, 386–387 facility nodes and transactions activity-scanning approach, 44–46 classes and procedures, 482–483 controlled blockage, 248–250 design environment for event-driven simulation (DEEDS) approach, 89–91 discrete simulation, 65–68 event-scheduling model, 38–44 model development applications, 169–176 process-simulation approach, 46–48 ProgramManager user interface, 137–138 simulation output, 211 transporter car materials-handling model, 322–323 facility preemption operation, special effects modeling, 240–242 FailedAssemblyInspection, quality control models, 403 FailedAxleInspection function, quality control models, 401–403 FailedWheelInspection function, quality control models, 402–403 FailureDelayEvent, maintenance models, 390–391 F1Facility function forced model termination, 208 independent facilities representation, multiserver facility, 238–239 model development applications, facility nodes and transactions, 173–176 queue waiting time limits, 242–243 time-dependent intercreation times, 244–246 FillOrdersDelayEvent continuous inventory review, 353–357 periodic review inventory control model, 350–352 FindAnAGV function, facilities layout models, flexible manufacturing environment, 315–316 first-in, first-out (FIFO) queue discrete simulation, 63–64 model development applications, 166–169 flexible manufacturing environment, facilities layout models, 306–317 forced model termination, characteristics of, 208 forgetfulness property, simulation modeling, 15–16 CRC_AU6744_Index.indd 501 ■ 501 for structure, Visual Basic for Applications (VBA) programming, 123 Frame1SourceEvent, queue nodes and transactions, 250–252 frequency histograms, characteristics of, 21–22 Function-Name function, select routing, 262–265 functions, Visual Basic for Applications (VBA) programming, 128 FunctionServiceTime, maintenance models, 389–390 F1-Utilization function, simulation output, 230–232 G gamma distribution See Erlang distribution GeneralCenterFacility, facilities layout models, flexible manufacturing environment, 311–317 GeneralSegmentFacilityEvent, facilities layout models, flexible manufacturing environment, 310–317 GenerateActivities sub function, PERT project scheduling model, 371–372 genetic algorithms advanced analysis techniques, 455–464 search sub functions, 456–464 GetNextJob subroutine, discount store inventory control model, 346–347 goodness-of-fit tests, simulation modeling, 23–26 H histograms construction, 21 discrete simulation data, 59–63 PERT project scheduling model, 372 historical data, distribution identification, 21 housekeeping routines, design environment for event-driven simulation (DEEDS), 92–99 hypothesis testing simulation modeling, 29–32 simulation results, 235–236 10/29/2007 7:12:37 PM 502 ■ Index I If structure, Visual Basic for Applications (VBA) programming, 119–121 If-Then-Else-End-If structure, synchronized queues, 270–272 incidence matrix, reliability models, 383–385 initial conditions, design environment for event-driven simulation (DEEDS) programming, 108–109 initialization, design environment for eventdriven simulation (DEEDS), 98 subs and functions, 106–108 InitialModel spreadsheet advanced analysis techniques, 447–448 carrousel conveyor materials handling model, 330–334 controlled facility blockage, 248–250 facility preemption operation, 240–242 facility sheet, 211 independent facilities representation, multiserver facility, 237–239 Jackson network modeling, 252–254 model development applications delay nodes and transactions, 176–177 statistics class, 182 observation gathering, 205–207 ProgramManager user interface, 138–149 Initial Resources segment, 152–153 sequential operations, 150–153 queue sheet, 209–210 waiting time limits, 242–243 simulation project management, data specifications, 286–288 sources output, 209 trace report, 215–217 InitialModel spreadsheet, design environment for event-driven simulation (DEEDS), 104–108 initial population, genetic algorithm, 464 Initial Resources segment, ProgramManager user interface, 146–149 InitialWorkStations, maintenance models, 394–396 inspection program quality control models, 397–403 search and simulation algorithms, 450–451 simulation project management, 285–286 data specifications, 287–288 surface plots, 451 three-factor design model, 448–450 CRC_AU6744_Index.indd 502 interactive debugging and trace, design environment for event-driven simulation (DEEDS) approach, 96–97 interarrival time discrete simulation randomness, time-dependent variables, 244–246 InterruptDelayEvent, facility preemption operation, 241–242 interrupt function, model development applications, facility nodes and transactions, 169–176 InTransit function, manpower scheduling models, 378–379 InTransitSameCustomer function, manpower scheduling models, 377–379 inventory control models continuous review model, 352–357 discount store model, 343–348 periodic review model, 348–352 ItemSourceEvent, carrousel conveyor materials handling model, 331–334 J jackknife estimator, statistical analysis, simulation modeling, regenerative method, 84–86 Jackson networks, special effects modeling, 252–254 JobCompletionEvent facilities layout models, line balancing, 301–305 maintenance models, 389–390 JobOneSourceEvent, job shop scheduling model, 361–367 JobSequence function, facilities layout models, flexible manufacturing environment, 307–317 job shop scheduling model, characteristics, 359–367 JobSiteFacilityEvent, manpower scheduling models, 375–379 JobSourceEvent, facilities layout models, flexible manufacturing environment, 309–317 JoinFront function, model development applications, queue nodes and transactions, 168–169 10/29/2007 7:12:37 PM Index Join function, model development applications, queue nodes and transactions, 168–169 K Kolmogrov-Smirnov test, simulation modeling, 26 L Last Choice destinations advanced routing transactions, 267–269 select routing, 262–265 last-in-first-out (LIFO) queue, model development applications, 166–169 “last-resort” sampling, discrete simulation, normal distribution, 56 lean manufacturing, evolution of, 3–4 line balancing, facilities layout models, 296–305 LineFacilityEvent, facility preemption operation, 241–242 LineServerFacilty Event, facilities layout models, line balancing, 299–305 list classifications, design environment for event-driven simulation (DEEDS) approach, 102–103 LoadCoilDelayEvent, overhead crane materials-handling model, 327–330 loading time requirements, port supply chain models, 411–412 LoadPeelerDelay event, belt conveyor-plywood mill operation, 337–342 logistics management automatic warehouse operation, 421–430 cross dock model, 430–439 port operation, 411–420 supply chain models, 411 lognormal distribution, simulation modeling, 17–18 M MachineFacilityEvent, job shop scheduling model, 362–367 MaintenanceDelayEvent, maintenance models, 389–392 CRC_AU6744_Index.indd 503 ■ 503 maintenance models overview, 381 scheduling parameters, 385–396 majorizing function, discrete simulation, acceptance-rejection method, 53–55 manpower allocation, scheduling models, 372–379 MapDoors sub function, cross dock supply model, 438–439 match transactions, synchronized queues, 270–272 material allocation, facilities layout models, line balancing, 298–305 materials-handling models belt conveyor-plywood mill operation, 334–342 carrousel conveyor, 330–334 overhead car, 323–330 overview, 319 transporter car, 319–323 material summary, facilities layout models, line balancing, 297–305 mathematical computation, design environment for event-driven simulation (DEEDS) approach, 98 maximum likelihood estimates, distribution parameters, 26–27 mean, statistical analysis, simulation modeling, 74 regenerative method, 84–86 memory, simulation modeling, 15–16 MMFacilityEvent, controlled facility blockage, 248–250 model development tools design environment for event-driven simulation classes, 162–163 delays, 176–177 distribution functions, 186–187 Excel Worksheet/Function, 188–195 facility methods, 169–176 probability density function, 183–185 queue nodes and transactions, 165–169 simulator procedures, 160–162 source subs, 163–165 statistic, 181–183 summary of features, 195–196 table characteristics, 185–186 transactions, 177–181 10/29/2007 7:12:37 PM 504 ■ Index model development tools (contd.) Visual Basic functions, 187–188 Visual Basic procedures, 159–160 simulation project management, 290–291 model documentation, design environment for event-driven simulation (DEEDS), 99 model logic routines, design environment for event-driven simulation (DEEDS), 92–99 model verification, simulation output, 214–218 monitoring simulation, during execution, 207–208 multiplicative congruential formula, discrete simulation, 56–57 multi-server facility, independent facilities representation, 237–239 multivariable simulation, steady-state conditions, 79–80 MutateChromosome sub function, genetic algorithm, 463–464 Mutate sub function, genetic algorithm, 462–464 N naming protocols, Visual Basic for Applications (VBA) programming, 113 negative exponential distribution discrete simulation, inverse method, 50 simulation modeling, 15–16 network representation design environment for event-driven simulation (DEEDS), 93 reliability models, 382–385 NewNumberOfServers, model development applications, facility nodes and transactions, 176 New Replicate option, observation gathering, 206–207 NewTransaction procedure, model development applications, 177–181 NextFacility function conditional routing transactions, 260 model development applications, facility nodes and transactions, 172–176 NextMaterial Set sub function, quality control models, 400–403 CRC_AU6744_Index.indd 504 NextNode, Jackson network modeling, 253–254 NextSegment function, facilities layout models, flexible manufacturing environment, 317 node definitions design environment for event-driven simulation (DEEDS) approach, 94, 101–102 ProgramManager user interface, 145–149 select routing, 261–265 NodeIndependent function, select routing, 262–263 NodeObject function facility preemption operation, 241–242 select routing, 262–263 nonstationarity, statistical analysis, simulation modeling, 74–76 normal distribution discrete simulation, 55–56 simulation modeling, 17 normality assumption, simulation modeling, 29 statistical analysis, 76–77 NowEmpty sub function, cross dock supply model, 438–439 null hypothesis, simulation modeling, 29–32 O ObjectVariable function, select routing, 261–265 observation-based variables discrete simulation data, 57–59 statistical analysis regenerative method, 84–85 replication method, 83–84 subinterval method, 80–83 ObservationSourceEvent, quality control models, 405–406 OperationsDelayEvent, maintenance models, 389–392 Order, model development applications, transaction attributes, 179–181 OrderCompletionDelayEvent, discount store inventory control model, 346–348 OrderQueue, job shop scheduling model, 362–367 10/29/2007 7:12:37 PM Index output capabilities design environment for event-driven simulation (DEEDS), 98 facilities layout models, line balancing, 305 quality control models, 399–403, 410 overhead crane materials-handling model, characteristics, 323–330 P parallel assembly operations, ProgramManager user interface, 144–149 Pareto decision variable chart, inspection model, 450 parser subroutine design environment for event-driven simulation (DEEDS), 106–108 ProgramManager user interface code building option, 139–142 sequential operations, 152–153 viewing options, 147–149 simulation output, statistical data gathering, 233–234 PartsAvailable function, facilities layout models, line balancing, 302–305 PartsSourceEvent, quality control models, 400–403 PeelerFacilityEvent, belt conveyor-plywood mill operation, 336–342 performance evaluation lean manufacturing systems, simulation output, transient conditions, 227–232 simulation project management, 284–286 periodic review model, inventory control, 348–352 PERT project scheduling, scheduling models, 367–372 PickUpJob function, facilities layout models, flexible manufacturing environment, 312–313 piecewise continuous random variable, model development applications, 184–185 PipeSourceEvent, transporter car materialshandling model, 320–323 Poisson distribution discrete simulation, convolution method, 52–53 simulation modeling, 20–21 CRC_AU6744_Index.indd 505 ■ 505 PopulationData, quality control models, 407–408 PortFacilityEvent, port supply chain models, 415–420 port operations, logistics management, 411–420 PositionPickDelayEvent, overhead crane materials-handling model, 326–330 preliminary design, simulation project management, 290 primary events list (PEL) activity-scanning approach, 44–46 automatic warehouse operation model, 423–430 belt conveyor-plywood mill operation, 335–342 cross dock supply model, 432–439 design environment for event-driven simulation (DEEDS), 89 list classification, 103 simulation clock, 93 time and management routines, 92–99 user’s fi les management, 94–96 event-scheduling model, 38–44 facilities layout models flexible manufacturing environment, 308–317 line balancing, 300–305 inventory control continuous review model, 353–357 discount store model, 344–348 periodic review model, 348–352 job shop scheduling model, 360–367 maintenance models, 388–389 model development applications source nodes and transactions, 163–165 transactions, 177–181 model verification, collection report, 217–218 overhead crane materials-handling model, 324–330 PERT project scheduling model, 369–372 port supply chain models, 413–420 ProgramManager user interface, code building option, 139–142 reliability models, 384–385 transporter car materials-handling model, 320–323 probabilistic routing, advanced routing transactions, 265 10/29/2007 7:12:37 PM 506 ■ Index probability density function (PDF) discrete simulation discrete distribution, 50–51 histograms, 61–63 inverse method, 48–49 negative exponential distribution, 50 uniform distribution, 49–50 gamma distribution, 16 model development applications, 183–185 ProgramManager user interface, 153–155 simulation project management, data specifications, 286–288 probability theory, discrete simulation randomness, problem definition, simulation project management, 289–290 procedural languages, discrete simulation, 7–8 procedures, Visual Basic for Applications (VBA) programming, 124–128 functions, 128 sub procedure, 125–128 process-based languages, discrete simulation, ProcessChromosome subfunction, genetic algorithm, 459–464 process layout, facilities layout models, 295 process sequence, facilities layout models, flexible manufacturing environment, 306–317 process-simulation approach, discrete simulation, 46–48 ProduceOff spring sub function, genetic algorithm, 458–464 product layout, facilities layout models, 295 Program Execution, expanded version, 156–157 program execution, ProgramManager user interface, 142–144 ProgramManager user interface delay nodes, 149 facility nodes, 137–138 features summary, 157–158 Initial Model options, 138–149 Jackson network modeling, 252–254 observation gathering, 205–207 overview, 133–134 program execution, 142–144 Program Execution - expanded, 156–157 queue nodes, 136–137 source nodes, 134–136 statistical variables, 149–153 user-defined probability functions, 153–155 CRC_AU6744_Index.indd 506 user-defined tables, 155–156 VBA code building, 139–142 viewing options, 144–149 Q quality control models chart monitoring, 403–410 costing inspection plans, 397–403 overview, 397 queue nodes and transactions activity-scanning approach, 44–46 automatic warehouse operation model, 430 belt conveyor-plywood mill operation, 341–342 carrousel conveyor materials handling model, 333–334 classes and procedures, 480–481 continuous inventory review, 355–357 design environment for event-driven simulation (DEEDS) approach, 89–91 output capabilities, 98 discount store inventory control model, 347–348 discrete simulation histograms, 61–63 performance evaluation, 63–65 event-scheduling model, 38–44 Jackson network modeling, 252–254 job shop scheduling model, 362–367 manpower scheduling models, 378–379 model development applications, 162, 165–169 network logic change, 246–248 overhead crane materials-handling model, 329–330 periodic review inventory control model, 352 port supply chain models, 420 process-simulation approach, 46–48 ProgramManager user interface, 136–137 set assembly and matching, 250–252 simulation output, 209–210 statistical analysis, simulation modeling regenerative method, 84–86 subinterval method, 81–83 synchronization, 270–274 10/29/2007 7:12:38 PM Index transporter car materials-handling model, 322–323 waiting time limits, 242–243 QueueWeightStatistic variable, transporter car materials-handling model, 320–323 queuing theory, limitations of, 4–5 R RandomDestination, probabilistic routing, 265 random deviate computations, discrete simulation, 48–57 acceptance-rejection method, 53–55 convolution methods, 51–53 inverse method, 48–51 normal distribution, 55–56 random number generation, 56–57 randomness forgetfulness property, 15–16 simulation modeling, probability and statistics, 13–14 random number generation, discrete simulation, 56–57 random sample generation, design environment for event-driven simulation approach, 96 random variables, model development applications, 183–185 ReceiveArrival sub function, automatic warehouse operation model, 427–430 ReceiveSourceEvent, automatic warehouse operation model, 424–430 Recent history of nodes, select routing, 264–265 RecordARL sub function, quality control models, 407–408 regenerative method, statistical analysis, simulation modeling, 84–86 RegularSource Event, facility preemption operation, 240–242 reliability model, general principles, 381–385 RepairDelayEvent, maintenance models, 389–391 RepairFacilityEvent, reliability models, 384–385 CRC_AU6744_Index.indd 507 ■ 507 replication method design environment for event-driven simulation (DEEDS), 448 forced model termination, 208 simulation output, 205–206 statistical data gathering, 232–234 statistical analysis, simulation modeling, 83–84 RequestSourceEvent, automatic warehouse operation model, 424–430 Resource Definition segment, ProgramManager user interface, 146–149 ReturnDelayEvent, overhead crane materialshandling model, 327–330 ReviewInventoryLevel subfunction, continuous inventory review, 355–357 ReviewSourceEvent manpower scheduling models, 374–379 periodic review inventory control model, 350–352 Rotation function, select routing, 263 RouteDependent function, dependent routing, 267 routing transactions, advanced routing techniques, 259–269 always routing, 260 conditional routing, 260 dependent routing, 266–267 exclusive routing, 267 last choice routing, 267–269 select routing, 261–265 RunLength function, simulation output, 230–232 S SampleWithoutReplacement, job shop scheduling model, 366–367 sampling data design environment for event-driven simulation (DEEDS) approach, 96 without replacement, 254–255 ScheduleLineServer, facilities layout models, line balancing, 302–305 ScheduleScriptArrival sub function, cross dock supply model, 436–439 ScheduleStripDoor sub function, cross dock supply model, 437–439 10/29/2007 7:12:38 PM 508 ■ Index scheduling models daily manpower allocation, 372–379 job shop scheduling, 359–367 overview, 359 PERT project scheduling, 367–372 scripted workload specification, project management, 282–283 search algorithms, advanced analysis techniques, 450–451 SegmentMapTable, facilities layout models, flexible manufacturing environment, 308–317 select routing, advanced routing transactions, 261–265 current state of node, 264 node independent function, 262–263 recent history of node, 264–265 sensitivity, quality control models, 398–403 sequential operations, ProgramManager user interface, 149–153 ServiceBulkQueue, overhead crane materialshandling model, 327–330 Service function, model development applications, facility nodes and transactions, 171–176 service time, discrete simulation randomness, set matching, queue nodes and transactions, 250–252 shape parameters, Erlang distribution, 16 ShipOrders function, automatic warehouse operation model, 427–430 ShippingDelayEvent continuous inventory review, 354–357 periodic review inventory control model, 350–352 ShutDown sub function, simulation output, 213–214 SIMSCRIPT software, port supply chain models, 411–420 simulation algorithms, advanced analysis techniques, 450–451 simulation clock basic principles of, 5–7 design environment for event-driven simulation (DEEDS), 93 VBA interactive debugger, 218–223 simulation messages, characteristics of, 207 simulation modeling basic principles of, 4–5 batch averaging, 76–80 characteristics of, 73–74 CRC_AU6744_Index.indd 508 classification of, common distribution characterization, 14–27 beta distribution, 19 chi-square test, 23–25 gamma (Erlang) distribution, 16 goodness-of-fit tests, 23 histograms, 21–23 historical data identification, 21 Kolmogrov-Smirnov test, 26 lognormal distribution, 17–18 maximum likelihood estimates, 26–27 negative exponential distribution, 15–16 normal distribution, 17 Poisson distribution, 20 triangular distribution, 19–20 uniform distribution, 14–15 Weibull distribution, 18 construction and interpretation, 9–10 data management, 76–80 design environment, 8–9 independence in, 74, 77 normality conditions, 76–77 probability and statistics, 13–14 randomness in, regenerative method, 84–86 replication method, 83–84 stationarity conditions, 74–76 statistical output analysis, 27–32 confidence intervals, 27–29 hypothesis testing, 29–32 normality assumption, 29 subinterval methods, 80–83 transient conditions, 78–80 variance reduction, 86–87 simulation output collection report, 217–218 delay sheet, 212 design environment for event-driven simulation, 104–108 execution monitoring, 207–208 facility sheet, 211–212 forced model termination, 208 messages, 207 misuse of, 225–227 model verification, 214–218 observation gathering, 205–207 queue sheet, 209–210 source sheet, 209 standard output, 209–214 10/29/2007 7:12:38 PM Index statistics sheet, 212–213 trace report, 215–217 transient conditions, 227–232 user-defined simulator messages, 214–215 UserOutput sheet, 213–214 VBA interactive debugger, 218–223 simulation project management constants, decision variables, and constraints, 283–286 data specifications, 286–288 design/conduct experiments, 291–292 design validation, 290 model development, 290–291 overview, 281 preliminary design, 290 problem definition, 289–290 specifications, 281–283 summarize/present results, 292 verify model, 291 simulator classes and procedures, 487 SimulatorMessage function model verification, 214–215 monitoring applications, 207–208 Simulator module, model development applications, 160–162 single-server events activity-scanning approach, 44–46 process-simulation approach, 47–48 statistical analysis, simulation modeling, stationarity, 75 timescale analysis, 6–7 SLAM II operations port supply chain models, 411–420 transporter car materials-handling model, 319–323 SourceLoopDelayEvent, job shop scheduling model, 361–367 source nodes and transactions design environment for event-driven simulation (DEEDS) approach, 89–90 model development applications, 162–165 process-simulation approach, 46–48 ProgramManager user interface, 134–136 simulation output, 209 Spawn subfunction, genetic algorithm, 460–464 special effects modeling common queue match and assembly, 250–252 controlled blockage facility, 248–250 CRC_AU6744_Index.indd 509 ■ 509 facility preemption operation, 240–242 Jackson networks, 252–254 multi-server facility, 237–239 network logic change with queue nodes, 246–248 queue waiting time limits, 242–243 sampling without replacement, 254–255 time-dependent intercreation times, 244–246 special-purpose nodes, design environment for event-driven simulation (DEEDS), 90 SpliceChromosomes sub function, genetic algorithm, 461–464 spreadsheet nodes, design environment for event-driven simulation (DEEDS), 107–108 S1SourceEvent queue sheet, waiting time limits, 242–243 time-dependent intercreation times, 244–246 SSSourceEvent subfunction, controlled facility blockage, 248–250 standard deviation PERT project scheduling model, 367–372 statistical analysis, simulation modeling, 75–76 StartNextJob facilities layout models, line balancing, 303–305 maintenance models, 393–396 StartSourceEvent PERT project scheduling model, 369–372 reliability models, 382–385 stationarity, statistical analysis, simulation modeling, 74–76 statistical analysis design environment for event-driven simulation (DEEDS) approach, data gathering, 96 simulation modeling, 27–32 confidence intervals, 27–28 hypothesis testing, 29–32 independence, 74 normality assumption, 29, 76–78 observation requirements, 73–74 regenerative method, 84–86 replication method, 83–84 stationarity, 74–76 subinterval method, 80–83 10/29/2007 7:12:38 PM 510 ■ Index statistical analysis (contd.) transient conditions, 78–80 variance reduction, 86–87 simulation output data gathering, 232–234 misuse of, 225–227 statistical variables discrete simulation, 57–59 facilities layout models, line balancing, 305 ProgramManager user interface, 149–153, 154–155 statistics nodes and transactions belt conveyor-plywood mill operation, 341–342 carrousel conveyor materials handling model, 334 classes and procedures, 486 continuous inventory review, 356–357 discount store inventory control model, 348 job shop scheduling model, 367 maintenance models, 395–396 model development applications, 181–182 periodic review inventory control model, 352 simulation output, 212–213 transporter car materials-handling model, 322–323 steady-state conditions simulation output errors, 228–232 statistical analysis, simulation modeling multivariable simulation input, 79–80 stationarity, 74–76 StopIndex function, facilities layout models, flexible manufacturing environment, 313–315 StopSimulation command, characteristics of, 208 StormDelayEvent, port supply chain models, 419–420 StormSourceEvent, port supply chain models, 413–420 Sub CreateNewJob, facilities layout models, line balancing, 303–305 subinterval method forced model termination, 208 simulation modeling, statistical analysis, 80–83 simulation output, 205–206 statistical data gathering, 232–234 CRC_AU6744_Index.indd 510 sub procedures BeginService, facility preemption operation, 241–242 model development applications, queue nodes and transactions, 167–169 Visual Basic for Applications (VBA) programming, 125–128 SubTravelTime, overhead crane materialshandling model, 329–330 summarize/present results function, simulation project management, 292 supply chain models automatic warehouse operation, 421–430 cross dock model, 430–439 overview, 411 port operation, 411–420 surface plot, advanced analysis techniques, 451 synchronized queues, advanced routing transactions, 270–274 SystemFacilityEvent, reliability models, 385–386 system specifications, project management, 281–283 SystemTime function confidence intervals, 234–235 hypothesis testing, 235–236 simulation output subinterval method, 233–234 transient conditions, 229–232 T Table function, model development applications, 185–186 TankerSourceEvent, port supply chain models, 414–420 task allocation, facilities layout models, line balancing, 298–305 TaskData function, facilities layout models, line balancing, 298–305 t-distribution, confidence intervals, 27–29 terminating simulation, statistical analysis, simulation modeling, replication method, 83–84 three-factor design, inspection model, 448–450 time and list management routines, design environment for event-driven simulation, 92–99 10/29/2007 7:12:38 PM Index time-dependent variables discrete simulation data, 57–59 event-scheduling model, 43–44 source intercreation times, 244–246 time management, design environment for event-driven simulation, 93 time parameters, simulation output, statistical data gathering, 232–234 TimerDelay event controlled facility blockage, 250 cross dock supply model, 433–439 network logic change, 248 queue waiting time limits, 242–243 time-dependent intercreation times, 245–246 timescale analysis, single-server events, 6–7 ToBayDelay sub function, port supply chain models, 417–420 tolerance assessment, quality control models, 397–403 ToPortDelay function, port supply chain models, 418–420 TowMotorDelayEvent, cross dock supply model, 434–439 trace report design environment for event-driven simulation (DEEDS) approach, 96–97 model verification, 215–217 transaction attributes classes and procedures, 485 design environment for event-driven simulation (DEEDS), 89–91, 102–103 class definitions, 94 user’s fi les management, 94–96 discrete simulation, process-simulation approach, 46–48 model development applications, 177–181 quality control models, 399–403 transaction flow simulation languages, design environment for event-driven simulation, 90 Transaction Objects, advanced routing techniques, 273–274 transient conditions simulation output analysis, 227–232 statistical analysis, simulation modeling estimation techniques, 78–80 stationarity, 74–76 subinterval method, 81–83 CRC_AU6744_Index.indd 511 ■ 511 TransitTime function, model development applications statistics data, 182 transactions, 178–181 TransportDropDelayEvent, overhead crane materials-handling model, 326–330 transporter car materials-handling model, characteristics, 319–323 TransporterFacilityEvent, transporter car materials-handling model, 321–323 TransporterIdle variable, transporter car materials-handling model, 320–323 TravelDelayEvent, manpower scheduling models, 375–379 TravelTime, overhead crane materials-handling model, 328–330 triangular distribution facilities layout models, line balancing, 296–305 simulation modeling, 19–20 TugDelayEvent, port supply chain models, 416–420 U uniform distribution discrete simulation, inverse method, 49–50 simulation modeling, 14–15 UpdateChart function, quality control models, 410 UpdateInventoryPosition, periodic review inventory control model, 351–352 UpStreamCheck, facilities layout models, line balancing, 302–305 UpstreamCheck, maintenance models, 392–393 user-defined program segments project management, 282–283 time-dependent intercreation times, 245–246 user-defined simulator messages, model verification, 214–215 user-defined tables, ProgramManager user interface, 155–156 user interface, ProgramManager for DEEDS delay nodes, 149 facility nodes, 137–138 features summary, 157–158 Initial Model options, 138–149 10/29/2007 7:12:38 PM 512 ■ Index user interface (contd.) overview, 133–134 program execution, 142–144 Program Execution - expanded, 156–157 queue nodes, 136–137 source nodes, 134–136 statistical variables, 149–153 user-defined probability functions, 153–155 user-defined tables, 155–156 VBA code building, 139–142 viewing options, 144–149 UserOutput sheet, simulation output, 213–214 user’s fi les management, design environment for event-driven simulation (DEEDS), 94–96 Utilization function, simulation output, 229–232 V validation of design, simulation project management, 290 variable definitions model development applications, 162–163 Visual Basic for Applications (VBA) programming, 114–115 variance, statistical analysis, simulation modeling, 74 reduction, 86–87 regenerative method, 84–86 verification procedures, simulation project management, 291 viewing options, ProgramManager user interface, 144–149 ViewPEL function, model verification, 214 Visual Basic for Applications (VBA) software arrays, 128–131 assignment statements, 117–119 basic principles, constants, 115–116 control structures, 119–124 Case structure, 121–123 Do structure, 123–124 If structure, 119–121 logical operators, 119 For structure, 123 data types, 113–114 CRC_AU6744_Index.indd 512 design environment for event-driven simulation (DEEDS), 89–99 class definitions, 94 class subs and functions, 103–104 development and execution routines, 99 list classification, 103 mathematical computation, 98 network representation, 93 program initial conditions, 108–109 expressions, 116–117 interactive debugger, 218–223 model development applications, 187–188 model development tools, 159–160 procedures, 124–128 functions, 128 sub procedure, 125–128 ProgramManager user interface, code building option, 139–142 programming features, names, 113 search and simulation algorithms, advanced analysis techniques, 455–464 summary of features, 131–132 variable definitions, 114–115 W waiting time limits, queue nodes and transactions, 242–243 warehouse layout, automatic warehouse operation model, 421–430 Watch List, VBA interactive debugger, 219–223 Weibull distribution, simulation modeling, 18–19 WIPIndex parameter, model development applications, facility nodes and transactions, 169–176 WorkerOnJob, manpower scheduling models, 376–379 work-in-progress collection, model development applications, facility nodes and transactions, 175–176 workload specification, project management, 282–283 WorkStationsFacility, carrousel conveyor materials handling model, 331–334 10/29/2007 7:12:38 PM ... AM 10 ■ Simulation of Industrial Systems of simulation is often ignored because a user may not be well trained in the use of statistical techniques This deficiency, coupled with lack of knowledge... observations is simply monitoring the behavior of the various model components as a function of simulation time 1.2 Types of Simulation The main purpose of a simulation model is to gather observations... Industrial Systems program for this segment of the simulation model requires above-average programming skills In the absence of some software development tools to relieve the user of this burden, simulation