Discrete-Event Simulation: Concepts and Production in Arena

by Abdessalem Jerbi

Overview

The use of discrete-event simulation in various fields, such as in industry, logistics and public health, has really taken off over the last few decades. The implementation of discrete-event simulation does however require an understanding, and perhaps even a mastery, of precise theoretical and methodological principles.

Discrete-Event Simulation presents the key concepts involved in any discrete-event simulation project, covering the most frequently used techniques for analysing data and results, the methodological and practical aspects of implementing discrete-event simulation, along with an introduction to the use of the “Arena” discrete-event simulation tool. This book combines the elements presented with applied examples, as well as numerous examples of simulation projects in various fields.

Product Details

ISBN-13:	9781394332229
Publisher:	Wiley
Publication date:	10/30/2024
Series:	ISTE Consignment
Sold by:	JOHN WILEY & SONS
Format:	eBook
Pages:	320
File size:	17 MB
Note:	This product may take a few minutes to download.

About the Author

Abdessalem Jerbi is a doctoral engineer in mechanical engineering and has taught flow simulation at the University of Sfax in Tunisia. His research is interdisciplinary, with a particular interest in simulation-based optimization.

Table of Contents

Preface xi

Chapter 1. Simulation 1

1.1. Introduction 1

1.2. Advantages of simulation 2

1.3. Disadvantages of simulation 3

1.4. Concepts relating to simulation 4

1.5. Components of a simulation model 6

1.6. Basic principles of system representation 13

1.7. Manual simulation 16

Chapter 2. Simulation Project 23

2.1. The stages of a simulation project 23

2.2. Problem formulation 24

2.3. Setting objectives 24

2.4. Construction of the conceptual model 24

2.5. Data collection and analysis 25

2.6. Software coding 25

2.7. Verification 25

2.8. Validation 26

2.9. Design of an experimental framework 28

2.10. Running the simulation and analyzing the results 28

Chapter 3. Data Processing 31

3.1. Introduction 31

3.2. Collecting input data. 32

3.3. Fitting a probability distribution to the variable 34

Chapter 4. Results Analysis 47

4.1. Introduction 47

4.2. Determining the number of replications for a terminating system 48

4.3. Determining the number of replications for a non-terminating system 51

4.4. Statistical analysis of results 54

Chapter 5. Presentation of Arena Software 71

5.1. Introduction 71

5.2. Arena software user interface 72

5.3. The "basic process" panel 73

5.4. The "advanced process" panel 82

5.5. The "advanced transfer" panel 89

Chapter 6. Simulation Modeling 101

6.1. Introduction to using Arena software 101

6.2. Collection and analysis of results (transitional period detection) 106

6.3. Resource failure 118

6.4. Entities transfer (PickStation) 124

6.5. Queue (Hold, Batch and Match) 132

6.6. Resource group, schedule and record results (Set, Schedule, Record) 141

6.7. Supply chain (Request, Transport and Free) 148

Chapter 7. Simulation within the Manufacturing Sector 157

7.1. Study of a television assembly line 157

7.2. Simulation-based optimization of a flexible manufacturing system 184

Chapter 8. Simulation within the Health Sector: Study of a Covid-19 Mass Vaccination Center 205

8.1. Introduction 205

8.2. Objective 206

8.3. Description of the vaccination center 206

8.4. Conceptual models of the vaccination center 207

8.5. Data collection and analysis of service times 210

8.6. Arrival rate of citizens at the center 211

8.7. Coding the simulation model 212

8.8. Verification of simulation models 217

8.9. Validation of the simulation model of the real center. 217

8.10. Experimentation and analysis of results 222

8.11. Discussion and conclusion 238

Chapter 9. Simulation in Supply Chains: Optimizing CO2 Emissions Through Pooling Strategies 241

9.1. Introduction 241

9.2. Pooling strategy 242

9.3. Objective 244

9.4. Description of the channel studied 244

9.5. Formulation of the CO2 emissions indicator 245

9.6. Conceptual models. 246

9.7. Simulation models 249

9.8. Verification and validation of simulation models 263

9.9. Results and discussion 266

9.10. Conclusion 268

Appendices 269

References 281

Index 283