**Preface**

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.

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:**

- 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.