The folks at Grand Valley State University are quite supportive of open textbooks. This is one of several that has been written by one of their professors and used in their own classrooms. Beyond Lean: Simulation in Practice, written by Charles R. Standridge, is part of their engineering curriculum.
Standridge’s work was originally published in December of 2011. Both the first and second editions (April 2013) are available. Answers to selected problems in the text, including the Automod models are not included but are available directly from the author. His contact information is provided on his simulation text book page.
Standridge tells students that an understanding of simulation methods is a prerequisite to the case studies. However, a simulation project process, basic simulation modeling methods, and basic simulation experimental methods are presented in the first part of the text. While he doesn’t state the level of knowledge required, the analytic models require knowledge of algebra.
The goal of this simulation textbook is to make the topic accessible to as many students and professionals as possible. “Only the most basic simulation modeling methods are presented, plus extensions as needed for each particular application study.”
Table of Contents
Part I: Introduction to Methods
1. Beyond Lean: Process and Principles
1.1 Introduction
1.2 An Industrial Application of Simulation
1.3 The Process of Validating a Furture State with Models
1.4 Principles for Simulation Modeling and Experimentation
1.5 Approach
1.6 Summary
Questions for Discussion
Active Learning Exercises
2. Simulation Modeling
2.1 Introduction
2.2 Elementary Modeling Constructs
2.3 Models of System Components
2.3.1 Arrivals
2.3.2 Operations
2.3.3 Routing Entities
2.3.4 Batching
2.3.5 Inventories
2.4 Summary
Problems
3. Modeling Random Quantities
3.1 Introduction
3.2 Determining a Distribution in the Absense of Data
3.2.1 Distribution Functions Used in the Absense of Data
3.2.2 Selecting Probablility Distributions in the Absense of Data – An Illustration
3.3 Fitting a Distribution Function to Data
3.3.1 Some Common Data Problems
3.3.2 Distribution Functions Most Often Used in a Simulation Model
3.3.3 A Software Based Approach to Fitting a Data Set to a Distribution Function
3.4 Summary
Problems
Active Learning Exercises
Laboratories
Bibliography
4. Conducting Simulation Experiments
4.1 Introduction
4.2 Verification and Validation
4.2.1 Verification Procedures
4.2.2 Validation Procedures
4.3 The Problem of Correlated Observations
4.4 Common Design Elements
4.4.1 Model Parameters and Their Values
4.4.2 Performance Measures
4.4.3 Streams of Random Samples
4.5 Design Elements Specific to Terminating Simulation Experiments
4.5.1 Initial Conditions
4.5.2 Replicates
4.5.3 Ending the Simulation
4.5.4 Design Summary
4.6 Examining the Results for a Single Scenario
4.6.1 Graphs, Histograms, and Summary Statistics
4.6.2 Confidence Intervals
4.6.3 Animating Model Dynamics
4.7 Comparing Scenarios
4.7.1 Comparison by Examination
4.7.2 Comparison by Statistical Analysis
4.7.2.1 A Word of Caution about Comparing Scenarios
4.8 Summary
Problems
5. The Simulation Engine
5.1 Introduction
5.2 Events and Event Graphs
5.3 Time Advance and Event Lists
5.4 Simulating the Two Workstation Model
5.5 Organizing Entities Waiting for a Resource
5.6 Random Sampling from Distribution Functions
5.7 Pseudo-Random Number Generation
5.8 Summary
Part II: Basic Organizations for Systems
6. A Single Workstation
6.1 Introduction
6.2 Points Made in the Case Study
6.3 The Case Study
6.3.1 Define the Issues and Solution Objective
6.3.2 Build Models
6.3.3 Identify Root Causes and Assess Initial Alternatives
6.3.3.1 Analytic Model of a Single Workstation
6.3.3.2 Simulation Model of a Single Workstation
6.3.4 Review and Extend Previous Work
6.3.4.1 Detractors to Workstation Performance
6.4 The Case Study for Detractors
6.4.1 Define the Issues and Solution Objective
6.4.2 Build Models
6.4.3 Assessment of the Impact of the Detractors on Part Lead Time
6.5 Summary
Problems
Application Problems
7. Serial Systems
7.1 Introduction
7.2 Points Made in the Case Study
7.3 The Case Study
7.3.1 Define the Issues and Solution Objective
7.3.2 Build Models
7.3.3 Identify Root Causes and Assess Initial Alternatives
7.3.4 Review and Extend Previous Work
7.3.5 Implement the Selected Solution and Evaluate
7.4 Summary
Problems
Application Problems
8. Job Shops
8.1 Introduction
8.2 Points Made in the Case Study
8.3 The Case Study
8.3.1 Define the Issues and Solution Objective
8.3.2 Build Models
8.3.3 Identify Root Causes and Assess Initial Alternatives
8.3.4 Review and Extend Previous Work
8.4 The Case Study with Additional Machines
8.4.1 Identify Root Causes and Assess Initial Alternatives
8.4.2 Review and Extend Previous Work
8.4.3 Implement the Selected Solution and Evaluate
8.5 Summary
Problems
Application Problems
Part III Lean and Beyond Manufacturing
9. Inventory Organization and Control
9.1 Introduction
9.2 Traditional Inventory Models
9.2.1 Trading off Number of Setups (Orders) for Inventory
9.2.2 Trading off Customer Service Level for Inventory
9.3 Inventory Models for Lean Manufacturing
9.3.1 Random Demand – Normally Distributed
9.3.2 Random Demand – Discrete Distributed
9.3.3 Unreliable Production – Discrete Distributed
9.3.4 Unreliable Production and Random Demand – Both Discrete Distributed
9.3.5 Production Qunatities
9.3.6 Demand in a Discrete Time Period
9.3.7 Simulation Model of an Invetory Solution
9.4 Introduction to Pull Inventory Management
9.4.1 Kanban Systems: One Implementation of the Pull Philosophy
9.4.2 CONWIP Systems: A Second Implementation of the Pull Philosophy
9.4.3 POLCA: An Extension to CONWIP
Problems
10. Inventory Control Using Kanbans
10.1 Introduction
10.2 Points Made in the Case Study
10.3 The Case Study
10.3.1 Define the Issues and Solution Objective
10.3.2 Build Models
10.3.3 Identify Root Causes and Assess Initial Alternatives
10.3.4 Review and Extend Previous Work
10.3.5 Implement the Selected Solution and Evaluate
10.5 Summary
Problems
Application Problem
11. Cellular Manufacturing Operations
11.1 Introduction
11.3.1 Define the Issues and Solution Objective
11.3.2 Build Models
11.3.3 Identify Root Causes and Assess Initial Alternatives
11.3.4 Review and Extend Previous Work
11.3.5 Implement the Selected Solution and Evaluate
11.4 Summary
Problems
Application Problem
12. Flexible Manufacturing Systems
12.1 Introduction
12.2 Points Made in the Case Study
12.3 The Case Study
12.3.1 Define the Issues and Solution Objective
12.3.2 Build Models
12.3.3 Identify Root Causes and Assess Initial Alternatives
12.3.4 Review and Extend Previous Work
12.3.5 Implement the Selected Solution and Evaluate
12.4 Summary
Problems
Application Problem
Part IV Supply Chain Logistics
13. Automated Inventory Management
13.1 Introduction
13.2 Points Made in the Case Study
13.3 The Case Study
13.3.1 Define the Issues and Solution Objective
13.3.2 Build Models
13.3.3 Identify Root Causes and Assess Initial Alternatives
13.3.4 Review and Extend Previous Work
13.3.5 Implement the Selected Solution and Evaluate
13.4 Summary
Problems
Application Problem
14. Transportation and Delivery
14.1 Introduction
14.2 Points Made in the Case Study
14.3 The Case Study
14.3.1 Define the Issues and Solution Objective
14.3.2 Build Models
14.3.3 Identify Root Causes and Assess Initial Alternatives
14.3.4 Review and Extend Previous Work
14.3.5 Implement the Selected Solution and Evaluate
14.4 Summary
Problems
Application Problem
15. Integrated Supply Chains
15.1 Introduction
15.2 Points Made in the Case Study
15.3 The Case Study
15.3.1 Define the Issues and Solution Objective
15.3.2 Build Models
15.3.3 Identify Root Causes and Assess Initial Alternatives
15.3.4 Review and Extend Previous Work
15.3.5 Implement the Selected Solution and Evaluate
15.4 Summary
Problems
Application Problem
Part V Material Handling
16. Distribution Centers and Conveyors
16.1 Introduction
16.2 Points Made in the Case Study
16.3 The Case Study
16.3.1 Define the Issues and Solution Objective
16.3.2 Build Models
16.3.3 Identify Root Causes and Assess Initial Alternatives
16.3.4 Review and Extend Previous Work
16.3.5 Implement the Selected Solution and Evaluate
16.4 Alternative Worker Assignment
16.4.1 Build Models
16.4.2 Identify Root Causes and Assess Initial Alternatives
16.4.3 Implement the Selected Solution and Evaluate
16.5 Summary
Problems
Application Problem
17. Automated Guided Vehicle Systems
17.1 Introduction
17.2 Points Made in the Case Study
17.3 The Case Study
17.3.1 Define the Issues and Solution Objective
17.3.2 Build Models
17.3.3 Identify Root Causes and Assess Initial Alternatives
17.3.4 Review and Extend Previous Work
17.4 Assessment of Alternative Pickup and Dropoff Points
17.4.1 Identify Root Causes and Assess Initial Alternatives
17.4.2 Review and Extend Previous Work
17.4.3 Implement the Selected Solution and Evaluate
17.5 Summary
Problems
Application Problem
18. Automated Storage and Retrieval
18.1 Introduction
18.2 Points Made in the Case Study
18.3 The Case Study
18.3.1 Define the Issues and Solution Objective
18.3.2 Build Models
18.3.3 Identify Root Causes and Assess Initial Alternatives
18.3.4 Review and Extend Previous Work
18.3.5 Implement the Selected Solution and Evaluate
18.4 Summary
Problems
Application Problem
Appendices
AutoMod Summary and Tutorial for the Chapter 6 Case Study
Distribution Function Fitting in JMP: Tutorial
View this Free Online Material at the source:
Beyond Lean: Simulation in Practice
