ISE Simulation with Arena

✍ Scribed by Randall P. Sadowski Nancy B. Zupick W. David Kelton

• Publisher: McGraw Hill Education
• Year: 2023
• Tongue: English
• Leaves: 689
• Edition: 7
• Category: Library

✦ Synopsis

9781266275722 International edition of Simulation with Arena 7th Edition by W. David Kelton, Randall P. Sadowski, Nancy B. Zupick.*Student textbook only, No Access Code included****Simulation with Arena provides a comprehensive treatment of simulation using industry-standard Arena software. The textbook begins by having the reader develop simple high-level models, and then progresses to advanced modeling and analysis. Statistical design and analysis of simulation experiments is integrated with the modeling chapters, reflecting the importance of mathematical modeling of these activities. An informal, tutorial writing style is used to aid the beginner in fully understanding the ideas and topics presented. The new edition now reflects Arena version 16.2 (from version 14.5 in the prior edition), which contains many new and useful features. The new edition of Simulation with Arena is also available in McGraw Hill Connect, featuring Adaptive Learning Assignments, the MHeBook, Instructor Resources, and more!

✦ Table of Contents

Cover
Title Page
Copyright Page
About the Authors
Contents
Preface
Chapter 1: What Is Simulation?
1.1 Modeling
1.1.1 What’s Being Modeled?
1.1.2 How About Just Playing with the System?
1.1.3 Sometimes You Can’t (or Shouldn’t) Play with the System
1.1.4 Physical Models
1.1.5 Logical (or Mathematical) Models
1.1.6 What Do You Do with a Logical Model?
1.2 Computer Simulation
1.2.1 Popularity and Advantages
1.2.2 The Bad News
1.2.3 Different Kinds of Simulations
1.3 How Simulations Get Done
1.3.1 By Hand
1.3.2 Programming in General-Purpose Languages
1.3.3 Simulation Languages
1.3.4 High-Level Simulators
1.3.5 Where Arena Fits In
1.4 Applications of Simulation in Industry
1.4.1 Capital Investment Studies
1.4.2 Operational Models
1.4.3 The Future of Simulation
Chapter 2: Fundamental Simulation Concepts
2.1 An Example
2.1.1 The System
2.1.2 Goals of the Study
2.2 Analysis Options
2.2.1 Educated Guessing
2.2.2 Queueing Theory
2.2.3 Mechanistic Simulation
2.3 Pieces of a Simulation Model
2.3.1 Entities
2.3.2 Attributes
2.3.3 (Global) Variables
2.3.4 Resources
2.3.5 Queues
2.3.6 Statistical Accumulators
2.3.7 Events
2.3.8 Simulation Clock
2.3.9 Starting and Stopping
2.4 Event-Driven Hand Simulation
2.4.1 Outline of the Action
2.4.2 Keeping Track of Things
2.4.3 Carrying It Out
2.4.4 Finishing Up
2.5 Event- and Process-Oriented Simulation
2.6 Randomness in Simulation
2.6.1 Random Input, Random Output
2.6.2 Replicating the Example
2.6.3 Comparing Alternatives
2.7 Simulating with Spreadsheets
2.7.1 A News Vendor Problem
2.7.2 A Single-Server Queue
2.7.3 Extensions and Limitations
2.8 Overview of a Simulation Study
2.9 Exercises
Chapter 3: A Guided Tour Through Arena
3.1 Starting Up
3.2 Exploring the Arena Window
3.2.1 Opening a Model
3.2.2 A Tour of the Arena Window
3.2.3 Modules
3.2.4 Basic Interactions
3.2.5 Panning, Zooming, and View
3.3 Browsing Through an Existing Model: Model 3-1
3.3.1 The Create Flowchart Module
3.3.2 The Entity Data Module
3.3.3 The Process Flowchart Module
3.3.4 The Resource Data Module
3.3.5 The Queue Data Module
3.3.6 Animating Resources and Queues
3.3.7 The Dispose Flowchart Module
3.3.8 Connecting Flowchart Modules
3.3.9 Dynamic Plots
3.3.10 Dressing Things Up
3.3.11 Setting the Run Conditions
3.3.12 Running It
3.3.13 Viewing the Reports
3.4 Building Model 3-1 Yourself
3.4.1 New Model Window and Required Panels
3.4.2 Place and Connect the Flowchart Modules
3.4.3 The Create Flowchart Module
3.4.4 Displays
3.4.5 The Entity Data Module
3.4.6 The Process Flowchart Module
3.4.7 The Resource and Queue Data Modules
3.4.8 Resource Animation
3.4.9 The Dispose Flowchart Module
3.4.10 Dynamic Plots
3.4.11 Window Dressing
3.4.12 The Run > Setup Dialog Boxes
3.4.13 Establishing Named Views
3.5 Case Study: Specialized Serial Processing vs Generalized Parallel Processing
3.5.1 Model 3-2: Serial Processing – Specialized Separated Work
3.5.2 Model 3-3: Parallel Processing – Generalized Integrated Work
3.5.3 Models 3-4 and 3-5: The Effect of Task-Time Variability
3.6 General Overview of Arena’s Ribbons
3.6.1 Animate Bar
3.6.2 Printing, Media and Extras
3.7 Help!
3.8 Summary and Forecast
3.9 Exercises
Chapter 4: Modeling Basic Operations and Inputs
4.1 Model 4-1: An Electronic Assembly and Test System
4.1.1 Developing a Modeling Approach
4.1.2 Building the Model
4.1.3 Running the Model
4.1.4 Viewing the Results
4.2 Model 4-2: The Enhanced Electronic Assembly and Test System
4.2.1 Expanding Resource Representation: Schedules and States
4.2.2 Resource Schedules
4.2.3 Resource Failures
4.2.4 Frequencies
4.2.5 Results of Model 4-2
4.3 Model 4-3: Enhancing the Animation
4.3.1 Changing Animation Queues
4.3.2 Changing Entity Pictures
4.3.3 Adding Resource Pictures
4.3.4 Adding Variables and Plots
4.4 Model 4-4: The Electronic Assembly and Test System with Part Transfers
4.4.1 Some New Arena Concepts: Stations and Transfers
4.4.2 Adding the Route Logic
4.4.3 Altering the Animation
4.5 Finding and Fixing Errors
4.6 Input Analysis: Specifying Model Parameters and Distributions
4.6.1 Deterministic vs Random Inputs
4.6.2 Collecting Data
4.6.3 Using Data
4.6.4 Fitting Input Distributions via the Input Analyzer
4.6.5 No Data?
4.6.6 Nonstationary Arrival Processes
4.6.7 Multivariate and Correlated Input Data
4.7 Summary and Forecast
4.8 Exercises
Chapter 5: Modeling Detailed Operations
5.1 Model 5-1: A Simple Call Center System
5.2 New Modeling Issues
5.2.1 Customer Rejections and Balking
5.2.2 Three-Way Decisions
5.2.3 Variables and Expressions
5.2.4 Storages
5.2.5 Terminating or Steady State
5.3 Modeling Approach
5.4 Building the Model
5.4.1 Create Arrivals and Direct to Service
5.4.2 Arrival Cutoff Logic
5.4.3 Technical Support Calls
5.4.4 Sales Calls
5.4.5 Order-Status Calls
5.4.6 System Exit and Run Setup
5.4.7 Animation
5.5 Model 5-2: The Enhanced Call Center System
5.5.1 The New Problem Description
5.5.2 New Concepts
5.5.3 Defining the Data
5.5.4 Modifying the Model
5.6 Model 5-3: The Enhanced Call Center with More Output Performance Measures
5.7 Model 5-4: An (s, S) Inventory Simulation
5.7.1 System Description
5.7.2 Simulation Model
5.8 Summary and Forecast
5.9 Exercises
Chapter 6: Statistical Analysis of Output from Terminating Simulations
6.1 Time Frame of Simulations
6.2 Strategy for Data Collection and Analysis
6.3 Confidence Intervals for Terminating Systems
6.4 Comparing Two Scenarios
6.5 Evaluating Many Scenarios with the Process Analyzer (PAN)
6.6 Searching for an Optimal Scenario with OptQuest
6.7 Periodic Statistics
6.8 Summary and Forecast
6.9 Exercises
Chapter 7: Intermediate Modeling and Steady-State Statistical Analysis
7.1 Model 7-1: A Small Manufacturing System
7.1.1 New Arena Concepts
7.1.2 The Modeling Approach
7.1.3 The Data Modules
7.1.4 The Logic Modules
7.1.5 Animation
7.1.6 Verification
7.2 Statistical Analysis of Output from Steady-State Simulations
7.2.1 Warm-up and Run Length
7.2.2 Truncated Replications
7.2.3 Batching in a Single Run
7.2.4 What To Do?
7.2.5 Other Methods and Goals for Steady-State Statistical Analysis
7.3 Summary and Forecast
7.4 Exercises
Chapter 8: Entity Transfer
8.1 Types of Entity Transfers
8.2 Model 8-1: The Small Manufacturing System with Resource-Constrained Transfers
8.3 The Small Manufacturing System with Transporters
8.3.1 Model 8-2: The Modified Model 8-1 for Transporters
8.3.2 Model 8-3: Refining the Animation for Transporters
8.4 Conveyors
8.4.1 Model 8-4: The Small Manufacturing System with Nonaccumulating Conveyors
8.4.2 Model 8-5: The Small Manufacturing System with Accumulating Conveyors
8.5 Summary and Forecast
8.6 Exercises
Chapter 9: A Sampler of Further Modeling Issues and Techniques
9.1 Modeling Conveyors Using the Material Handling Panel
9.1.1 Model 9-1: Finite Buffers at Stations
9.1.2 Model 9-2: Parts Stay on Conveyor During Processing
9.2 More on Transporters
9.3 Entity Reneging
9.3.1 Entity Balking and Reneging
9.3.2 Model 9-3: A Service Model with Balking and Reneging
9.4 Holding and Batching Entities
9.4.1 Modeling Options
9.4.2 Model 9-4: A Batching Process Example
9.5 Overlapping Resources
9.5.1 System Description
9.5.2 Model 9-5: A Tightly Coupled Production System
9.5.3 Model 9-6: Adding Part-Status Statistics
9.6 A Few Miscellaneous Modeling Issues
9.6.1 Guided Transporters
9.6.2 Parallel Queues
9.6.3 Decision Logic
9.7 Exercises
Chapter 10: Arena Integration and Customization
10.1 Model 10-1: Reading and Writing Data Files
10.1.1 Model 10-2: Reading Entity Arrivals from a Text File
10.1.2 Reading in data from Excel using the Direct Read/Write
10.1.3 Writing Data to Excel
10.1.4 Additional Methods of Reading and Writing Information from Arena
10.2 VBA in Arena
10.2.1 Overview of ActiveX Automation and VBA
10.2.2 Built-In Arena VBA Events
10.2.3 Arena’s Object Model
10.2.4 Arena’s Macro Recorder
10.3 Model 10-5: Presenting Arrival Choices to the User
10.3.1 Modifying the Creation Logic
10.3.2 Designing the VBA UserForm
10.3.3 Displaying the Form and Setting Model Data
10.4 Arena Template Building Capabilities
10.5 Arena Visual Designer
10.5.1 Overview of Visual Designer
10.5.2 Dashboards
10.5.3 3D Scenes
10.6 Summary and Forecast
10.7 Exercises
Chapter 11: Continuous and Combined Discrete/Continuous Models
11.1 Modeling Simple Discrete/Continuous Systems
11.1.1 Model 11-1: A Simple Continuous System
11.1.2 Model 11-2: Interfacing Continuous and Discrete Logic
11.2 A Coal-Loading Operation
11.2.1 System Description
11.2.2 Modeling Approach
11.2.3 Model 11-3: Coal Loading with Continuous Approach
11.2.4 Model 11-4: Coal Loading with Tank Flow
11.3 Continuous State-Change Systems
11.3.1 Model 11-5: A Soaking-Pit Furnace
11.3.2 Modeling Continuously Changing Rates
11.3.3 Arena’s Approach for Solving Differential Equations
11.3.4 Building the Model
11.3.5 Defining the Differential Equations Using VBA
11.4 Summary and Forecast
11.5 Exercises
Chapter 12: Further Statistical Issues
12.1 Random-Number Generation
12.2 Generating Random Variates
12.2.1 Discrete
12.2.2 Continuous
12.3 Nonstationary Poisson Processes
12.4 Variance Reduction
12.4.1 Common Random Numbers
12.4.2 Other Methods
12.5 Sequential Sampling
12.5.1 Terminating Models
12.5.2 Steady-State Models
12.6 Designing and Executing Simulation Experiments
12.7 Exercises
Chapter 13: Conducting Simulation Studies
13.1 A Successful Simulation Study
13.2 Problem Formulation
13.3 Solution Methodology
13.4 System and Simulation Specification
13.5 Model Formulation and Construction
13.6 Verification and Validation
13.7 Experimentation and Analysis
13.8 Presenting and Preserving the Results
13.9 Disseminating the Model
Appendix A: A Functional Specification for The Washington Post
A.1 Introduction
A.1.1 Document Organization
A.1.2 Simulation Objectives
A.1.3 Purpose of the Functional Specification
A.1.4 Use of the Model
A.1.5 Hardware and Software Requirements
A.2 System Description and Modeling Approach
A.2.1 Model Timeline
A.2.2 Presses
A.2.3 Product Types
A.2.4 Press Packaging Lines
A.2.5 Tray System
A.2.6 Truck Arrivals
A.2.7 Docks
A.2.8 Palletizers
A.2.9 Manual Insertion Process
A.3 Animation
A.4 Summary of Input and Output
A.4.1 Model Input
A.4.2 Model Output
A.5 Project Deliverables
A.5.1 Simulation Model Documentation
A.5.2 User’s Manual
A.5.3 Model Validation
A.5.4 Animation
A.6 Acceptance
Appendix B: A Refresher on Probability and Statistics
B.1 Probability Basics
B.2 Random Variables
B.2.1 Basics
B.2.2 Discrete
B.2.3 Continuous
B.2.4 Joint Distributions, Covariance, Correlation, and Independence
B.3 Sampling and Sampling Distributions
B.4 Point Estimation
B.5 Confidence Intervals
B.6 Hypothesis Tests
B.7 Exercises
Appendix C: Arena’s Probability Distributions
C.1 Beta
C.2 Continuous
C.3 Discrete
C.4 Erlang
C.5 Exponential
C.6 Gamma
C.7 Johnson
C.8 Lognormal
C.9 Normal
C.10 Poisson
C.11 Triangular
C.12 Uniform
C.13 Weibull
Appendix D: Academic Software Installation Instructions
D.1 Authorization to Copy Software
D.2 Installing the Arena Software
D.3 System Requirements
References
Index