Preface

Motivation

Process simulation is one of the conceptually simplest and most often applied techniques in Operations Management and Management Science, yet it has not been widely taught to business students.  A key reason for this is that performing process simulation requires the use of software, and the software that is available tends to be complex and expensive.  Even the more graphics-based packages, although often beautifully designed, frequently have an enormous number of features that place an unnecessary burden on students (and instructors) in classes that are not devoted to simulation. 

SimQuick is a computer package for process simulation that is easy to learn (most of its features can be learned in under an hour of class time or independent reading) and inexpensive.  It is aimed primarily at business students and managers who want to understand process simulation and be able to quickly analyze and improve real-world processes.  SimQuick is flexible in its modeling capability; that is, it is not a “hardwired” set of examples; it requires true modeling.  In addition, SimQuick runs in the widely-known Microsoft Excel spreadsheet environment (it is an ordinary Excel 2000 file with some hidden macros).  Hence, users of Excel will already be familiar with much of the interface, and the results are already in the spreadsheet, ready for analysis. 

This booklet accompanies SimQuick.  It presents the basics of process simulation by having the reader construct, run, and analyze simulations of realistic processes using SimQuick.  Chapter 1 contains a brief introduction to process simulation and the concepts underlying SimQuick.  The next four chapters contain a variety of examples of process simulation.  These examples are organized as follows: waiting lines (Chapter 2), inventory in supply chains (Chapter 3), manufacturing (Chapter 4), and project management (Chapter 5).  Each example is followed by an exercise.  All of the examples and exercises have been designed with business students and managers in mind. 

In addition to presenting the basics of process simulation, this booklet introduces a number of key concepts from the analysis of processes: service level, cycle (or waiting) time, throughput, bottleneck, batch size, setup, priority rule, and so on.  The booklet also introduces some key trade-offs from the analysis of processes: number of servers vs. service level, inventory level vs. service level, working time variability vs. throughput, batch size vs. service level, and so on.  These notions are presented through computer models that the reader constructs and experiments with using SimQuick.

How to use the booklet

The booklet is self-contained; that is, all technical terms involving processes or operations are defined.  (The reader is assumed to have a rudimentary understanding of how to use Excel on the level of knowing how to save files and how to enter information into cells.)  The chapters are organized around typical topics in Operations Management and Management Science courses so that this booklet can easily be used in these types of courses. 

The reader should first read Chapter 1 (which contains a conceptual explanation of process simulation and SimQuick) and Section 1 of Chapter 2 (which contains a step-by-step explanation of how to use SimQuick by completely working through a simple example).  After this the reader has a lot of freedom: The remaining sections in Chapters 2, 4, and 5 can be read in any order (except Example 7 should be read before Example 11).  However, the sections in Chapter 3 build on one another and should be read in sequence. 

The bulk of Chapters 2 through 5 consists of examples of processes that can be modeled using SimQuick.  When needed, an example discusses how to build the SimQuick model.  Each example is followed by an exercise.

A very quick treatment of process simulation could consist of working through Example/Exercise 1, followed by Examples/Exercises 2-4 for waiting lines and Example/Exercise 18 for manufacturing.  With just this material, many real-world processes can be easily modeled and studied.  Adding Example/Exercise 7 with Decision Points would allow the modeling of many more types of processes.  Adding Examples/Exercises 12 and 13 would provide a quick introduction to the modeling of inventory in supply chains.

The booklet contains four appendices.  Appendix 1 contains a list of the basic steps in conducting a simulation project.  Appendix 2 contains tips on how to enhance SimQuick by using some of the features built into Excel.  These tips are tied to examples in the booklet. Appendix 3 describes how to use a feature of SimQuick called Custom Schedules.  Appendix 4 contains a succinct description of all the features of SimQuick and can be used for reference.  Hence, the features of SimQuick are presented in two ways: through examples and in a reference manual.

Solutions to exercises: Instructors are provided with complete solutions (in Excel) to every exercise.  These solutions may be distributed to the students at the instructor’s discretion.

Web site: Refer to www.prenhall.com/hartvigsen for additional information on SimQuick, this booklet, technical support, and process simulation in general.

Over the past four years, I have used SimQuick in the classroom with executive MBAs, full-time MBAs, and undergraduate business students.  After a one-hour introduction in class (basically, covering Section 1 of Chapter 2), the students successfully solve a variety of modeling problems with little help.  This introduction also serves as a launching pad for term projects, whereby students identify and analyze real-world processes of their choice.

New to the 2^nd edition:

The SimQuick software in the second edition has been changed in a number of ways from its first incarnation.  These changes include the following (the manual in Appendix 4 contains all the features of SimQuick):

• SimQuick runs considerably more quickly.  This allows more simulations to be performed in a reasonable amount of time, which leads to more accurate results.  As a result, more simulations are allowed.
• SimQuick accepts larger models: up to 250 elements (new tables can be added by pasting copies of the 20 tables given for each element).
• Essentially arbitrary statistical distributions can be constructed using discrete distributions (introduced in Example 5).
• A “View Model” button has been added to the Control Panel.  Clicking this button produces a copy of the tables used in the model in a format convenient for printing and logic checking.
• The initial number of objects at Buffers can be generated randomly.  This allows models to capture demand patterns that change over time (see Example 6).
• Decision Points can have up to ten outputs.
• The simulation details appearing on the Results worksheet can be suppressed, which allows SimQuick to run faster, especially when many simulations are performed.
• The method for using Custom Schedules for modeling arrivals and departures has been simplified (see Appendix 3).

The text has also been updated; these changes include the following:

• Four completely new models have been added.  Two of these models deal with services: airport security and a hospital emergency room (Examples 7 and 9); and two deal with inventory in supply chains: a base stock policy used in an appliance store (Example 16) and a periodic review policy used in a department store (Example 17).
• The key introductory section (Section 1 of Chapter 2) on how to use SimQuick has been streamlined (by removing the introduction of Decision Points).  As a result, learning the basics of SimQuick is even easier than in the first edition.  This makes possible a shorter treatment of process simulation, if the instructor wishes.
• Decision Points are now introduced in a separate section (Section 3 of Chapter 1) via an airport security example.  This example is more timely than the ATM bank example from the first edition, which has been removed.  Thus the topic of Decision Points may be skipped altogether.
• The issue of how to model observed data with a statistical distribution, particularly when it does not follow a built-in SimQuick distribution, is an important topic and is addressed as a new variation on the introductory bank example (see Example 5).
• The initial conditions of a simulation (particularly how much inventory is initially in the buffers) are of critical importance.  This topic is now explicitly dealt with as a new variation on the bank example (see Example 6).
• An important issue in manufacturing environments is that, over the long run, inventory will pile up to fill the available space.  This issue is now addressed in the exercise on linear flow processes (see Exercise 18).
• The general model for project management has been simplified.
• An appendix has been added that lists the basic steps in a simulation project.