Simulation with Arena

Transcription

1 Simulation with Arena Sixth Edition W. David Kelton Professor Department of Operations, Business Analytics, and Information Systems University of Cincinnati Randall P. Sadowski Retired Nancy B. Zupick Manager Arena Simulation Consulting and Support Services Rockwell Automation Mc Graw Hill Education

2 Contents Chapter 1: What Is Simulation? Modeling What's Being Modeled? How About Just Playing with the System? Sometimes You Can't (or Shouldn't) Play with the System Physical Models Logical (or Mathematical) Models What Do You Do with a Logical Model? Computer Simulation Popularity and Advantages The Bad News Different Kinds of Simulations How Simulations Get Done By Hand Programming in General-Purpose Languages Simulation Languages High-Level Simulators Where Arena Fits In When Simulations Are Used The Early Years The Formative Years The Recent Past The Present The Future 14 Chapter 2: Fundamental Simulation Concepts An Example The System Goals of the Study Analysis Options Educated Guessing Queueing Theory Mechanistic Simulation Pieces of a Simulation Model Entities Attributes (Global) Variables Resources Queues Statistical Accumulators Events Simulation Clock Starting and Stopping 24

3 viii Contents 2.4 Event-Driven Hand Simulation Outline of the Action Keeping Track of Things Carrying It Out Finishing Up Event- and Process-Oriented Simulation Randomness in Simulation Random Input, Random Output Replicating the Example Comparing Alternatives Simulating with Spreadsheets A News Vendor Problem A Single-Server Queue Extensions and Limitations Overview of a Simulation Study Exercises 48 Chapter 3: A Guided Tour Through Arena Starting Up Exploring the Arena Window Opening a Model Basic Interaction and Pieces of the Arena Window Panning, Zooming, Viewing, and Aligning in the Flowchart View Modules Internal Model Documentation Browsing Through an Existing Model: Model The Create Flowchart Module The Entity Data Module The Process Flowchart Module The Resource Data Module The Queue Data Module Animating Resources and Queues The Dispose Flowchart Module Connecting Flowchart Modules Dynamic Plots Dressing Things Up Setting the Run Conditions Running It Viewing the Reports Building Model 3-1 Yourself New Model Window and Basic Process Panel Place and Connect the Flowchart Modules The Create Flowchart Module Displays The Entity Data Module The Process Flowchart Module The Resource and Queue Data Modules Resource Animation The Dispose Flowchart Module Dynamic Plots 85

4 Specialized Generalized ^UNltNlb IX Window Dressing The Run > Setup Dialog Boxes Establishing Named Views Case Study: Specialized Serial Processing vs. Generalized Parallel Processing Model 3-2: Serial Processing Model 3-3: Parallel Processing Separated Work 90 Integrated Work Models 3-4 and 3-5: The Effect of Task-Time Variability More on Menus, Toolbars, Drawing, and Printing Menus Toolbars Drawing Printing Help! 3.8 More on Running Models Summary and Forecast Exercises Chapter 4: Modeling Basic Operations and Inputs Model 4-1: An Electronic Assembly and Test System Developing a Modeling Approach Building the Model Running the Model Viewing the Results Model 4-2: The Enhanced Electronic Assembly and Test System Expanding Resource Representation: Schedules and States Resource Schedules Resource Failures Frequencies Results of Model Model 4-3: Enhancing the Animation Changing Animation Queues Changing Entity Pictures Adding Resource Pictures Adding Variables and Plots Model 4-4: The Electronic Assembly and Test System with Part Transfers Some New Arena Concepts: Stations and Transfers Adding the Route Logic Altering the Animation Finding and Fixing Errors Input Analysis: Specifying Model Parameters and Distributions Deterministic vs. Random Inputs Collecting Data Using Data Fitting Input Distributions via the Input Analyzer No Data? Nonstationary Arrival Processes Multivariate and Correlated Input Data Summary and Forecast Exercises 194

5 x Contents Chapter 5: Modeling Detailed Operations Model 5-1: A Simple Call Center System New Modeling Issues Customer Rejections and Balking Three-Way Variables and Expressions 210 Decisions Storages Terminating or Steady State Modeling Approach Building the Mode] Create Arrivals and Direct to Service Arrival Cutoff Logic Technical Support Calls Sales Calls Order-Status Calls System Exit and Run Setup Animation Model 5-2: The Enhanced Call Center System The New Problem Description New Concepts Denning the Data Modifying the Model Model 5-3: The Enhanced Call Center with More Output Performance Measures Model 5-4: An (s, S) Inventory Simulation System Description Simulation Model Summary and Forecast Exercises 271 Chapter 6: Statistical Analysis of Output from Terminating Simulations Time Frame of Simulations Strategy for Data Collection and Analysis Confidence Intervals for Terminating Systems Comparing Two Scenarios Evaluating Many Scenarios with the Process Analyzer (PAN) Searching for an Optimal Scenario with OptQuest Periodic Statistics Summary and Forecast Exercises 303 Chapter 7: Intermediate Modeling and Steady-State Statistical Analysis Model 7-1: A Small Manufacturing System New Arena Concepts The Modeling Approach The Data Modules The Logic Modules Animation Verification 326

6 Contents xi 7.2 Statistical Analysis of Output from Steady-State Simulations Warm-up and Run Length Truncated Replications Batching in a Single Run What To Do? Other Methods and Goals for Steady-State Statistical Analysis Summary and Forecast Exercises 339 Chapter 8: Entity Transfer Types of Entity Transfers Model 8-1: The Small Manufacturing System with Resource-Constrained Transfers The Small Manufacturing System with Transporters Model 8-2: The Modified Model 8-1 for Transporters Model 8-3: Refining the Animation for Transporters Conveyors Model 8-4: The Small Manufacturing System with Nonaccumulating Convenyors Model 8-5: The Small Manufacturing System with Accumulating Conveyors Summary and Forecast Exercises 374 Chapter 9: A Sampler of Further Modeling Issues and Techniques Modeling Conveyors Using the Advanced Transfer Panel Model 9-1: Finite Buffers at Stations Model 9-2: Parts Stay on Conveyor During Processing More on Transporters Entity Reneging Entity Balking and Reneging Model 9-3: A Service Model with Balking and Reneging Holding and Batching Entities Modeling Options Model 9-4: A Batching Process Example Overlapping Resources System Description Model 9-5: A Tightly Coupled Production System Model 9-6: Adding Part-Status Statistics A Few Miscellaneous Modeling Issues Guided Transporters Parallel Queues Decision Logic Exercises 416 Chapter 10: Arena Integration and Customization Model 10-1: Reading and Writing Data Files Model 10-2: Reading Entity Arrivals from a Text File Model 10-3 and Model 10-4: Reading and Writing Access and Excel Files 429

7 xii Contents Advanced Reading and Writing Model 10-5: Reading in String Data Direct Read of Variables and Expressions VBA in Arena Overview of ActiveX Automation and VBA Built-in Arena VBA Events Arena's Object Model Arena's Macro Recorder Model 10-6: Presenting Arrival Choices to the User Modifying the Creation Logic Designing the VBA UserForm Displaying the Form and Setting Model Data Model 10-7: Recording and Charting Model Results in Microsoft Excel Setting Up Excel at the Beginning of the Run Storing Individual Call Data Using the VBA Module Charting the Results and Cleaning Up at the End of the Run Arena Template Building Capabilities Arena Visual Designer Overview of Visual Designer Dashboards D Scenes Summary and Forecast Exercises 477 Chapter 11: Continuous and Combined Discrete/Continuous Models Modeling Simple Discrete/Continuous Systems Model 11-1: A Simple Continuous System Model 11-2: Interfacing Continuous and Discrete Logic A Coal-Loading Operation System Description Modeling Approach Model 11-3: Coal Loading with Continuous Approach Model 11-4: Coal Loading with Flow Process Continuous State-Change Systems Model 11-5: A Soaking-Pit Furnace Modeling Continuously Changing Rates Arena's Approach for Solving Differential Equations Building the Model Defining the Differential Equations Using VBA Summary and Forecast Exercises 514 Chapter 12: Further Statistical Issues Random-Number Generation Generating Random Variates Discrete Continuous Nonstationary Poisson Processes 529

8 Contents xiii 12.4 Variance Reduction Common Random Numbers Other Methods Sequential Sampling Terminating Models Steady-State Models Designing and Executing Simulation Experiments Exercises 546 Chapter 13: Conducting Simulation Studies A Successful Simulation Study Problem Formulation Solution Methodology System and Simulation Specification Model Formulation and Construction Verification and Validation Experimentation and Analysis Presenting and Preserving the Results Disseminating the Model 565 Appendix A: A Functional Specification for The Washington Post 567 A.l Introduction 567 A. 1.1 Document Organization 567 A.1.2 Simulation Objectives 567 A. 1.3 Purpose of the Functional Specification 568 A. 1.4 Use of the Model 568 A. 1.5 Hardware and Software Requirements 568 A.2 System Description and Modeling Approach 569 A.2.1 Model Timeline 569 A.2.2 Presses 569 A.2.3 Product Types 571 A.2.4 Press Packaging Lines 571 A.2.5 Tray System 571 A.2.6 Truck Arrivals 572 A.2.7 Docks 573 A.2.8 Palletizers 573 A.2.9 Manual Insertion Process 574 A.3 Animation 575 A.4 Summary of Input and Output 575 A.4.1 Model Input 575 A.4.2 Model Output 576 A.5 Project Deliverables 577 A.5.1 Simulation Model Documentation 577 A.5.2 User's Manual 577 A.5.3 Model Validation 577 A.5.4 Animation 578 A.6 Acceptance 578

9 xiv Contents Appendix B: A Refresher on Probability and Statistics 579 B. 1 Probability Basics 579 B.2 Random Variables 581 B.2.1 Basics 581 B.2.2 Discrete 582 B.2.3 Continuous 584 B.2.4 Joint Distributions, Covariance, Correlation, and Independence 586 B.3 Sampling and Sampling Distributions 589 B.4 Point Estimation 591 B.5 Confidence Intervals 591 B.6 Hypothesis Tests 593 B. 7 Exercises 595 Appendix C: Arena's Probability Distributions 597 C. 1 Beta 599 C.2 Continuous 600 C.3 Discrete 602 C.4 Erlang 603 C.5 Exponential 604 C.6 Gamma 605 C.7 Johnson 606 C.8 Lognormal 607 C.9 Normal 608 CIO Poisson 609 C.ll Triangular. 610 C.12 Uniform 611 C. 13 Weibull 612 Appendix D: Academic Software Installation Instructions 613 D. 1 Authorization to Copy Software 613 D.2 Installing the Arena Software 613 D.3 System Requirements 614 References 615 Index 619