Preface

This sixth edition explains how to use simulation to make better business decisions in application domains from healthcare to mining, heavy manufacturing to supply chains, and everything in between. It is written to help both technical and non-technical users better understand the concepts and usefulness of simulation. It can be used in a classroom environment or in support of independent study. Modern software makes simulation more useful and accessible than ever and this book illustrates simulation concepts with Simio (R), a leader in simulation software.

This edition is written for Simio Version 14 or later – the technical content, figures, and examples have been updated to adjust for 3 years of new releases. The most dramatic change is in format and distribution – we are now distributing this updated book in a free online format to make it accessible to everyone. We have incorporated many new features as well as reader suggestions. We have enhanced the Monte Carlo, input analysis, and output analysis content, and added new coverage of data-driven and data-generated modeling techniques. We added a section introducing the emerging technology of AI and Neural Networks in support of simulation. Finally, we updated the Simulation-based Scheduling in Industry 4.0 chapter, discussing how simulation is contributing to the creation and effective operation of digital twins and operational scheduling and control. End-of-chapter problems have been improved and expanded, and we have incorporated many reader suggestions. We have reorganized the material for an improved flow, and have updates throughout the book for many of the new Simio features recently added.

This book can serve as the primary text in first and second courses in simulation at both the undergraduate and beginning-graduate levels. It is written in an accessible tutorial-style writing approach centered on specific examples rather than general concepts, and covers a variety of applications including an international flavor. Our experience has shown that these characteristics make the text easier to read and absorb, as well as appealing to students from many different cultural and applications backgrounds.

A first simulation course would probably cover Chapter 1 through Chapter 8 thoroughly, and likely Chapters 9 through 11, particularly for upper class or graduate-level students. For a second simulation course, it might work to skip or quickly review Chapters 1-3 and 6, thoroughly cover all other chapters up to Chapter 12, and use Appendices A and B as reinforcing assignments or term projects.

The text or components of it could also support a simulation module of a few weeks within a larger survey course in programs without a stand-alone simulation course (e.g., MBA). For a simulation module that’s part of a larger survey course, we recommend concentrating on Chapters 1, 4, and 5, and then perhaps lightly touch on Chapters 7 and 8. Appendix B describes several real-world simulation applications that might be useful for context.

The extensibility introduced in Chapter 11 could provide some interesting project work for a graduate student with some programming background, as it could be easily linked to other research topics. Likewise Chapter 12 could be used as the lead-in to some advanced study or research in the latest techniques in simulation-based planning and scheduling and an exploration of simulation applications in support of Smart Factories and Industry 4.0. Appendix A could be used as student assignments or challenge problems in an applications-focused or independent-study course.

We assume basic familiarity with the Microsoft Windows (R) operating system and common applications like Microsoft Excel (R) and Microsoft Word (R). This book also assumes prior coursework in, and comfort with, probability and statistics. Readers don’t need to be experts, but do need command of the basics of probability and statistics; more specific topics are outlined at the beginning of Chapters 2 and 6.