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Description Module 03: Forecasting In this module, you will identify elements of demand forecasting, analyze steps in the forecasting process, and you

Description

Module 03: Forecasting

In this module, you will identify elements of demand forecasting, analyze steps in the forecasting process, and you will focus on the importance of forecasting as it relates to operations management.  Demand forecasting may be completed in a simple manner reviewing historical trends or through elaborate systems.  This will include the meaningful units in forecasting, how those meaningful units may be different in organizations providing services rather than making products, and how writing down the forecast allows multiple people in multiple roles in the organization to give input to the forecast. We will also look at the impact that a forecasting technique has on receiving the level of detail needed for a forecast. Each organization chooses its own method or methods based on the level of accuracy that may be required.

Discussion Question

Question Requirements:

Forecasting

You are in charge of creating a forecast for an organization that manufactures laptops. The industry is very competitive and supplies have to be purchased far enough ahead of time so that there is no delay in the manufacturing process should the demand increase. 

Which forecasting technique would you choose? 

What are the steps in the forecasting process? 

Why is it important to create a forecast for the correct period of time? 

What happens when a forecast is created for 3 months when an organization needs an accurate forecast for 6 months? 

Directions:

Discuss the concepts, principles, and theories from your textbook. Cite your textbooks and cite any other sources. 

Write a discussion that includes an introduction paragraph, the body, and a conclusion paragraph to address the assignment’s guide questions.

Module 03: Forecasting
In this module, you will identify elements of demand forecasting, analyze steps in the forecasting
process, and you will focus on the importance of forecasting as it relates to operations
management. Demand forecasting may be completed in a simple manner reviewing historical trends
or through elaborate systems. This will include the meaningful units in forecasting, how those
meaningful units may be different in organizations providing services rather than making products, and
how writing down the forecast allows multiple people in multiple roles in the organization to give input
to the forecast. We will also look at the impact that a forecasting technique has on receiving the level
of detail needed for a forecast. Each organization chooses its own method or methods based on the
level of accuracy that may be required.
Discussion Question
Question Requirements:
Forecasting
You are in charge of creating a forecast for an organization that manufactures laptops. The industry is
very competitive and supplies have to be purchased far enough ahead of time so that there is no
delay in the manufacturing process should the demand increase.
1.
2.
3.
4.
Which forecasting technique would you choose?
What are the steps in the forecasting process?
Why is it important to create a forecast for the correct period of time?
What happens when a forecast is created for 3 months when an organization needs an
accurate forecast for 6 months?
Directions:
• Discuss the concepts, principles, and theories from your textbook. Cite your textbooks and
cite any other sources.
• Write a discussion that includes an introduction paragraph, the body, and a conclusion
paragraph to address the assignment’s guide questions.
• Your initial post should address all components of the question with a 600-word limit.
Learning Outcomes
1. Analyze the importance of forecasting in terms of operations management.
2. Articulate the importance of developing and monitoring forecasts.
Readings
Required:
• Chapter 3 in Operations Management
• Chapter 3 PowerPoint Presentation
• Che-Jung CHANG, Guiping LI, Jianhong GUO, & Kun-Peng YU. (2020). DataDriven Forecasting Model for Small Data Sets. Economic Computation & Economic
Cybernetics Studies & Research, 54(4), 217–
229.
• Piotrowska-Woroniak, J., & Szul, T. (2022). Application of a Model Based on Rough
Set Theory (RST) to Estimate the Energy Efficiency of Public Buildings. Energies
(19961073), 15(23), 8793.
Recommended:
• Shang, Z., Li, M., Chen, Y., Li, C., Yang, Y., & Li, L. (2022). A novel model based
on multiple input factors and variance reciprocal: application on wind speed
forecasting. Soft Computing – A Fusion of Foundations, Methodologies &
Applications, 26(17), 8857–8877.
Forecasting
3-1
You should be able to:
LO 3.1
List features common to all forecasts
LO 3.2 Explain why forecasts are generally wrong
LO 3.3 List the elements of a good forecast
LO 3.4 Outline the steps in the forecasting process
LO 3.5 Summarize forecast errors and use summaries to make decisions
LO 3.6 Describe four qualitative forecasting techniques
LO 3.7 Use a naïve method to make a forecast
LO 3.8 Prepare a moving average forecast
LO 3.9 Prepare a weighted-average forecast
LO 3.10 Prepare an exponential smoothing forecast
LO 3.11 Prepare a linear trend forecast
LO 3.12 Prepare a trend-adjusted exponential smoothing forecast
LO 3.13 Compute and use seasonal relatives
LO 3.14 Compute and use regression and correlation coefficients
LO 3.15 Construct control charts and use them to monitor forecast errors
LO 3.16 Describe the key factors and trade-offs to consider when choosing a
forecasting technique
3-2
 Forecast – a statement about the future value of a
variable of interest
 We make forecasts about such things as weather,
demand, and resource availability
 Forecasts are important to making informed decisions
LO 3.1
3-3
 Expected level of demand
 The level of demand may be a function of some
structural variation such as trend or seasonal variation
 Accuracy
 Related to the potential size of forecast error
LO 3.1
3-4
• Accounting. New product/process cost estimates, profit projections,
cash management.
• Finance. Equipment/equipment replacement needs,
timing and amount of funding/borrowing needs.
• Human resources. Hiring activities, including recruitment,
interviewing, and training; layoff planning, including
outplacement counseling.
• Marketing. Pricing and promotion, e-business strategies, global
competition strategies.
• MIS. New/revised information systems, internet services.
• Operations. Schedules, capacity planning, work assignments and
workloads, inventory planning, make-or-buy decisions, outsourcing,
project management.
• Product/service design. Revision of current features, design of new
products or services.
LO 3.1
3-5
 Plan the system
 Generally involves long-range plans related to:
 Types of products and services to offer
 Facility and equipment levels
 Facility location
 Plan the use of the system
 Generally involves short- and medium-range plans related to:
 Inventory management
 Workforce levels
 Purchasing
 Production
 Budgeting
 Scheduling
LO 3.1
3-6
1.
2.
3.
4.
LO 3.1
Techniques assume some underlying causal system that
existed in the past will persist into the future
Forecasts are not perfect
Forecasts for groups of items are more accurate than
those for individual items
Forecast accuracy decreases as the forecasting horizon
increases
3-7
 Forecasts are not perfect:
 Because random variation is always present, there will
always be some residual error, even if all other factors
have been accounted for.
LO 3.2
3-8
The forecast

Should be timely

Should be accurate

Should be reliable

Should be expressed in meaningful units

Should be in writing

Technique should be simple to understand and use

Should be cost-effective
LO 3.3
3-9
1.
2.
3.
4.
5.
6.
LO 3.4
Determine the purpose of the forecast
Establish a time horizon
Obtain, clean, and analyze appropriate data
Select a forecasting technique
Make the forecast
Monitor the forecast errors
3-10
 Qualitative forecasting
 Qualitative techniques permit the inclusion of soft information
such as:
 Human factors
 Personal opinions
 Hunches
 These factors are difficult, or impossible, to quantify
 Quantitative forecasting
 These techniques rely on hard data
 Quantitative techniques involve either the projection of historical
data or the development of associative methods that attempt to use
causal variables to make a forecast
LO 3.6
3-11
 Forecasts that use subjective inputs such as opinions from consumer
surveys, sales staff, managers, executives, and experts
 Executive opinions
 A small group of upper-level managers may meet and collectively develop a
forecast
 Salesforce opinions
 Members of the sales or customer service staff can be good sources of
information due to their direct contact with customers and may be aware of
plans customers may be considering for the future
 Consumer surveys
 Since consumers ultimately determine demand, it makes sense to solicit input
from them
 Consumer surveys typically represent a sample of consumer opinions
 Other approaches
 Managers may solicit 0pinions from other managers or staff people or outside
experts to help with developing a forecast.
 The Delphi method is an iterative process intended to achieve a consensus
LO 3.6
3-12
 Forecasts that project patterns identified in recent
time-series observations
 Time-series – a time-ordered sequence of observations
taken at regular time intervals
 Assume that future values of the time-series can be
estimated from past values of the time-series
LO 3.6
3-13
 Trend
 Seasonality
 Cycles
 Irregular variations
 Random variation
LO 3.6
3-14
 Trend
 A long-term upward or downward movement in data
 Population shifts
 Changing income
 Seasonality
 Short-term, fairly regular variations related to the calendar or time
of day
 Restaurants, service call centers, and theaters all experience
seasonal demand
LO 3.6
3-15
 Cycle
 Wavelike variations lasting more than one year
 These are often related to a variety of economic, political, or even
agricultural conditions
 Irregular variation
 Due to unusual circumstances that do not reflect typical behavior
 Labor strike
 Weather event
 Random Variation
 Residual variation that remains after all other behaviors have been
accounted for
LO 3.6
3-16
 Naïve forecast
 Uses a single previous value of a time series as the basis
for a forecast
 The forecast for a time period is equal to the previous
time period’s value
 Can be used with
 A stable time series
 Seasonal variations
 Trend
LO 3.7
3-17
 These techniques work best when a series tends to vary
about an average
 Averaging techniques smooth variations in the data
 They can handle step changes or gradual changes in the
level of a series
 Techniques
1.
2.
3.
LO 3.7
Moving average
Weighted moving average
Exponential smoothing
3-18
 Technique that averages a number of the most recent
actual values in generating a forecast
n
Ft = MA n =
A
t −i
i =1
n
At − n + … + At − 2 + At −1
=
n
where
Ft = Forecast for time period t
MA n = n period moving average
At −i = Actual value in period t − i
n = Number of periods in the moving average
LO 3.8
3-19
 As new data become available, the forecast is updated
by adding the newest value and dropping the oldest
and then re-computing the average
 The number of data points included in the average
determines the model’s sensitivity
 Fewer data points used—more responsive
 More data points used—less responsive
LO 3.7
3-20
 The most recent values in a time series are given more
weight in computing a forecast
 The choice of weights, w, is somewhat arbitrary and
involves some trial and error
Ft = wt ( At ) + wt −1 ( At −1 ) + … + wt − n ( At − n )
where
wt = weight for period t , wt −1 = weight for period t − 1, etc.
At = the actual value for period t , At −1 = the actual value for period t − 1, etc.
LO 3.9
3-21
 A weighted averaging method that is based on the
previous forecast plus a percentage of the forecast
error
Ft = Ft −1 +  ( At −1 − Ft −1 )
where
Ft = Forecast for period t
Ft −1 = Forecast for the previous period
 = Smoothing constant
At −1 = Actual demand or sales from the previous period
LO 3.10
3-22
 A simple data plot can reveal the existence and nature
of a trend
 Linear trend equation
Ft = a + bt
where
Ft = Forecast for period t
a = Value of Ft at t = 0
b = Slope of the line
t = Specified number of time periods from
LO 3.11
t =0
3-23
 Slope and intercept can be estimated from historical
data
b=
n ty −  t  y
( )
n t −  t
2
2
y − b t

a=
or y − bt
n
where
n = Number of periods
y = Value of the time series
LO 
3.11
3-24
 The trend adjusted forecast consists of two
components
 Smoothed error
 Trend factor
TAFt +1 = St + Tt
where
St = Previous forecast plus smoothed error
Tt = Current trend estimate

LO 3.12
3-25
 Alpha and beta are smoothing constants
 Trend-adjusted exponential smoothing has the ability
to respond to changes in trend
TAFt +1 = St + Tt
St = TAFt +  (At − TAFt )
Tt = Tt−1 +  (TAFt − TAFt−1 − Tt−1 )

LO 3.12
3-26
 Seasonality – regularly repeating movements in
series values that can be tied to recurring events
 Expressed in terms of the amount that actual values
deviate from the average value of a series
 Models of seasonality
 Additive
 Seasonality is expressed as a quantity that gets added to or
subtracted from the time-series average in order to
incorporate seasonality
 Multiplicative
 Seasonality is expressed as a percentage of the average (or
trend) amount which is then used to multiply the value of a
series in order to incorporate seasonality
LO 3.12
3-27
 Seasonal relatives
 The seasonal percentage used in the multiplicative seasonally
adjusted forecasting model
 Using seasonal relatives
 To deseasonalize data
 Done in order to get a clearer picture of the nonseasonal (e.g.,
trend) components of the data series
 Divide each data point by its seasonal relative
 To incorporate seasonality in a forecast
1.
2.
LO 3.13
Obtain trend estimates for desired periods using a trend
equation
Add seasonality by multiplying these trend estimates by the
corresponding seasonal relative
3-28
 Associative techniques are based on the
development of an equation that summarizes the
effects of predictor variables
 Predictor variables – variables that can be used to
predict values of the variable of interest
 Home values may be related to such factors as home and
property size, location, number of bedrooms, and number of
bathrooms
LO 3.14
3-29
 Regression – a technique for fitting a line to a set of
data points
 Simple linear regression – the simplest form of
regression that involves a linear relationship between
two variables
 The object of simple linear regression is to obtain an equation
of a straight line that minimizes the sum of squared vertical
deviations from the line (i.e., the least squares criterion)
LO 3.14
3-30
yc = a + bx
where
yc = Predicted (dependent ) variable
x = Predictor (independe nt) variable
b = Slope of the line
a = Value of yc when x = 0 (i.e., the height of the line at the y intercept)
and
b=
n( xy) − ( x )( y )
(
)
n  x 2 − ( x )
2
y − b x

a=
or y − b x
n
where
n = Number of paired observatio ns
LO 3.14
3-31
 Correlation, r
 A measure of the strength and direction of relationship between
two variables
 Ranges between -1.00 and +1.00
r=
(
n( xy) − ( x )( y )
)
n  x 2 − ( x )
2
(
)
n  y 2 − ( y )
2
 r2, square of the correlation coefficient
 A measure of the percentage of variability in the values of y that is
“explained” by the independent variable
 Ranges between 0 and 1.00
LO 3.14
3-32
Variations around the line are random
2. Deviations around the average value (the line)
should be normally distributed
3. Predictions are made only within the range of
observed values
1.
LO 3.14
3-33
 Always plot the line to verify that a linear relationship
is appropriate
 The data may be time-dependent
 If they are
 use analysis of time series
 use time as an independent variable in a multiple regression
analysis
 A small correlation may indicate that other variables
are important
LO 3.14
3-34
 Allowances should be made for forecast errors
 It is important to provide an indication of the extent to
which the forecast might deviate from the value of the
variable that actually occurs
 Forecast errors should be monitored
 Error = Actual – Forecast
 If errors fall beyond acceptable bounds, corrective
action may be necessary
LO 3.5
3-35
Actual − Forecast

MAD =
t
MAD weights all errors
evenly
t
n
(Actual − Forecast )

MSE =
t
2
t
n −1
Actual t − Forecast t
100

Actual t
MAPE =
n
LO 3.5
MSE weights errors according
to their squared values
MAPE weights errors
according to relative error
3-36
Period
Actual
(A)
Forecast
(F)
(A-F)
Error
|Error|
Error2
[|Error|/Actual]x100
1
107
110
-3
3
9
2.80%
2
125
121
4
4
16
3.20%
3
115
112
3
3
9
2.61%
4
118
120
-2
2
4
1.69%
5
108
109
1
1
1
0.93%
Sum
13
39
11.23%
n=5
n-1 = 4
n=5
MAD
MSE
MAPE
= 2.6
= 9.75
= 2.25%
LO 3.5
3-37
 Tracking forecast errors and analyzing them can provide useful
insight into whether forecasts are performing satisfactorily
 Sources of forecast errors:
 The model may be inadequate due to
a.
b.
c.
omission of an important variable
a change or shift in the variable the model cannot handle
the appearance of a new variable
 Irregular variations may have occurred
 Random variation
 Control charts are useful for identifying the presence of non-
random error in forecasts
 Tracking signals can be used to detect forecast bias
LO 3.15
3-38
1. Compute the MSE.
2. Estimate of standard deviation of the distribution of errors
s = MSE
3. UCL: 0 + z MSE
4. LCL: 0 – z MSE
where z = Number of standard deviations from the mean
LO 3.15
3-39
 Factors to consider
 Cost
 Accuracy
 Availability of historical data
 Availability of forecasting software
 Time needed to gather and analyze data and prepare a
forecast
 Forecast horizon
LO 3.16
3-40
 The better forecasts are, the more able organizations will
be to take advantage of future opportunities and reduce
potential risks
 A worthwhile strategy is to work to improve short-term forecasts
 Accurate up-to-date information can have a significant effect on
forecast accuracy:
 Prices
 Demand
 Other important variables
 Reduce the time horizon forecasts have to cover
 Sharing forecasts or demand data through the supply chain can
improve forecast quality
LO 3.16
3-41
Operations Management
Operations Management
FOURTEENTH EDITION
William J. Stevenson
Saunders College of Business
Rochester Institute of Technology
OPERATIONS MANAGEMENT, FOURTEENTH EDITION
Published by McGraw-Hill Education, 2 Penn Plaza, New York, NY 10121. Copyright © 2021 by McGraw-Hill
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Library of Congress Cataloging-in-Publication Data
Library of Congress Cataloging-in-Publication Data
Names: Stevenson, William J., author.
Title: Operations management / William J. Stevenson, Saunders College of
Business, Rochester Institute of Technology.
Description: Fourteenth edition. | New York, NY : McGraw-Hill Education,
[2021] | Includes bibliographical references and index.
Identifiers: LCCN 2019044799 | ISBN 9781260238891 (bound edition ;
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ISBN 9781260718423 (loose-leaf edition ; acid-free paper) | ISBN
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Subjects: LCSH: Production management.
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v
Preface
The material in this book is intended as an introduction to the
field of operations management. The topics covered include
both strategic issues and practical applications. Among the
topics are forecasting, product and service design, capacity
planning, management of quality and quality control, inventory management, scheduling, supply chain management, and
project management.
My purpose in revising this book continues to be to provide
a clear presentation of the concepts, tools, and applications of
the field of operations management. Operations ­management
is evolving and growing, and I have found updating and
­integrating new material to be both rewarding and challenging, particularly due to the plethora of new developments in
the field, while facing the practical limits on the length of
the book.
This text offers a comprehensive and flexible amount
of content that can be selected as appropriate for different
courses and formats, including undergraduate, graduate, and
executive education.
This allows instructors to select the chapters, or portions
of chapters, that are most relevant for their purposes. That
flexibility also extends to the choice of relative weighting
of the qualitative or quantitative aspects of the material, and
the order in which chapters are covered, because chapters do
not depend on sequence. For example, some instructors cover
project management early, others cover quality or lean early,
and so on.
As in previous editions, there are major pedagogical f­ eatures
designed to help students learn and understand the material.
This section describes the key features of the book, the ­chapter
elements, the supplements that are available for teaching the
course, highlights of the fourteenth edition, and suggested
applications for classroom instruction. By providing this support, it is our hope that instructors and students will have the
tools to make this learning experience a rewarding one.
What’s New in This Edition
In many places, content has been rewritten or added to
improve clarity, shorten wording, or update information. New
material has been added on supply chains, and other topics.
Some problems are new, and others have been revised. Many
new readings and new photos have been added.
Some of the class preparation exercises have been revised.
The purpose of these exercises is to introduce students to the
subject matter before class in order to enhance classroom
learning. They have proved to be very popular with students, both as an introduction to new material and for study
purposes. These exercises are available in the Instructor’s
Resource Manual. Special thanks to Linda Brooks for her
help in developing the exercises.
Acknowledgments
I want to thank the many contributors to this edition. Reviewers and adopters of the text have provided a “continuously
improving” wealth of ideas and suggestions. It is encouraging to me as an author. I hope all reviewers and readers will
know their suggestions were valuable, were carefully considered, and are sincerely appreciated. The list includes post-­
publication reviewers.
Jenyi Chen
Eric Cosnoski
Mark Gershon
Narges Kasiri
Nancy Lambe
Anita Lee-Post
Behnam Nakhai
Rosa Oppenheim
Marilyn Preston
Avanti Sethi
John T. Simon
Lisa Spencer
Nabil Tamimi
Oya Tukel
Theresa Wells
Heath Wilken
Cleveland State University
Lehigh University
Temple University
Ithaca College
University of South Alabama
University of Kentucky
Millersville University of Pennsylvania
Rutgers Business School
Indiana University Southeast
University of Texas at Dallas
Governors State University
California State University, Fresno
University of Scranton
Cleveland State University
University of Wisconsin-Eau Claire
University of Northern Iowa
Additional thanks to the instructors who have contributed extra
material for this edition, including accuracy ­checkers: Ronny
Richardson, Kennesaw State University and Gary Black,
­University of Southern Indiana; Solutions and ­SmartBook:
Tracie Lee, Idaho State University; PowerPoint Presentations:
Avanti Sethi, University of Texas-Dallas; Test Bank: Leslie
Sukup, Ferris State University.
Special thanks goes out to Lisa Spencer, California State
University-Fresno, for her help with additional readings and
examples.
vii
viii
Preface
Finally, I would like to thank all the people at ­McGraw-Hill
for their efforts and support. It is always a pleasure to work
with such a professional and competent group of p­eople.
Special thanks go to Noelle Bathurst, Portfolio Manager;
Michele Janicek, Lead Product Developer; Fran Simon and
Katie Ward, Product Developers; Jamie Koch, Assessment
Content Project Manager; Sandy Ludovissy, Buyer; Matt Diamond, Designer; Jacob Sullivan, Content Licensing Specialist; Harper Christopher, Executive Marketing Manager; and
many others who worked behind the scenes.
I would also like to thank the many reviewers of previous
editions for their contributions: Vikas Agrawal, Fayetteville
State University; Bahram Alidaee, University of Mississippi;
Ardavan Asef-Faziri, California State University at Northridge; Prabir Bagchi, George Washington State University;
Gordon F. Bagot, California State University at Los Angeles;
Ravi Behara, Florida Atlantic University; Michael Bendixen,
Nova Southeastern; Ednilson Bernardes, Georgia Southern
University; Prashanth N. Bharadwaj, Indiana University of
Pennsylvania; Greg Bier, University of Missouri at Columbia;
Joseph Biggs, Cal Poly State University; Kimball Bullington,
Middle Tennessee State University; Alan Cannon, University
of Texas at Arlington; Injazz Chen, Cleveland State University; Alan Chow, University of Southern Alabama at Mobile;
Chrwan-Jyh, Oklahoma State University; Chen Chung, University of Kentucky; Robert Clark, Stony Brook University;
Loretta Cochran, Arkansas Tech University; Lewis Coopersmith, Rider University; Richard Crandall, Appalachian State
University; Dinesh Dave, Appalachian State University; Scott
Dellana, East Carolina University; Kathy Dhanda, DePaul
University; Xin Ding, University of Utah; Ellen Dumond,
California State University at Fullerton; Richard Ehrhardt,
University of North Carolina at Greensboro; Kurt Engemann,
Iona College; Diane Ervin, DeVry University; Farzaneh
Fazel, Illinois State University; Wanda Fennell, University of
Mississippi at Hattiesburg; Joy Field, Boston College; Warren Fisher, Stephen F. Austin State University; Lillian Fok,
University of New Orleans; Charles Foley, Columbus State
Community College; Matthew W. Ford, Northern Kentucky
University; Phillip C. Fry, Boise State University; Charles
A. Gates Jr., Aurora University; Tom Gattiker, Boise State
University; Damodar Golhar, Western Michigan University;
Robert Graham, Jacksonville State University; Angappa
Gunasekaran, University of Massachusetts at Dartmouth;
Haresh Gurnani, University of Miami; Terry Harrison, Penn
State University; Vishwanath Hegde, California State University at East Bay; Craig Hill, Georgia State University;
Jim Ho, University of Illinois at Chicago; Seong Hyun Nam,
University of North Dakota; Jonatan Jelen, Mercy College;
Prafulla Joglekar, LaSalle University; Vijay Kannan, Utah
State University; Sunder Kekre, Carnegie-Mellon University;
Jim Keyes, University of Wisconsin at Stout; Seung-Lae Kim,
Drexel University; Beate Klingenberg, Marist College; John
Kros, East Carolina University; Vinod Lall, Minnesota State
University at Moorhead; Kenneth Lawrence, New Jersey
Institute of Technology; Jooh Lee, Rowan University; Anita
Lee-Post, University of Kentucky; Karen Lewis, University of
Mississippi; Bingguang Li, Albany State University; Cheng
Li, California State University at Los Angeles; Maureen P.
Lojo, California State University at Sacramento; F. Victor
Lu, St. John’s University; Janet Lyons, Utah State University; James Maddox, Friends University; Gita Mathur, San
Jose State University; Mark McComb, Mississippi College;
George Mechling, Western Carolina University; Scott Metlen,
University of Idaho; Douglas Micklich, Illinois State University; Ajay Mishra, SUNY at Binghamton; Scott S. Morris,
Southern Nazarene University; Philip F. Musa, University of
Alabama at Birmingham; Roy Nersesian, Monmouth University; Jeffrey Ohlmann, University of Iowa at Iowa City; John
Olson, University of St. Thomas; Ozgur Ozluk, San Francisco
State University; Kenneth Paetsch, Cleveland State University; Taeho Park, San Jose State University; Allison Pearson,
Mississippi State University; Patrick Penfield, Syracuse University; Steve Peng, California State University at Hayward;
Richard Peschke, Minnesota State University at Moorhead;
Andru Peters, San Jose State University; Charles Phillips,
Mississippi State University; Frank Pianki, Anderson University; Sharma Pillutla, Towson University; Zinovy Radovilsky, California State University at Hayward; Stephen A.
Raper, University of Missouri at Rolla; Pedro Reyes, Baylor
University; Buddhadev Roychoudhury, Minnesota State University at Mankato; Narendra Rustagi, Howard University;
Herb Schiller, Stony Brook University; Dean T. Scott, DeVry
University; Scott J. Seipel, Middle Tennessee State University; Raj Selladurai, Indiana University; Kaushic Sengupta,
Hofstra University; Kenneth Shaw, Oregon State University;
Dooyoung Shin, Minnesota State University at Mankato;
Michael Shurden, Lander University; Raymond E. Simko,
Myers University; John Simon, Governors State University;
Jake Simons, Georgia Southern University; Charles Smith,
Virginia Commonwealth University; Kenneth Solheim,
DeVry University; Young Son, Bernard M. Baruch College;
Victor Sower, Sam Houston State University; Jeremy Stafford, University of North Alabama; Donna Stewart, University of Wisconsin at Stout; Dothang Truong, Fayetteville State
University; Mike Umble, Baylor University; Javad Varzandeh, California State University at San Bernardino; Timothy
Vaughan, University of Wisconsin at Eau Claire; Emre Veral,
Preface
Baruch College; Mark Vroblefski, University of Arizona;
Gustavo Vulcano, New York University; Walter Wallace,
Georgia State University; James Walters, Ball State University; John Wang, Montclair State University; Tekle Wanorie,
Northwest Missouri State University; Jerry Wei, University
of Notre Dame; Michael Whittenberg, University of Texas;
ix
Geoff Willis, University of Central Oklahoma; Pamela Zelbst,
Sam Houston State University; Jiawei Zhang, NYU; Zhenying Zhao, University of Maryland; Yong-Pin Zhou, University of Washington.
William J. Stevenson
Walkthrough
MAJOR STUDY AND LEARNING FEATURES
A number of key features in this text have been specifically
designed to help introductory students learn, understand, and
apply operations concepts and problem-solving techniques.
Examples with Solutions
Rev.Confirming Pages
Throughout the text, wherever a quantitative or
analytic technique is introduced, an example is
included to illustrate the application of that technique. These are designed to be easy to follow.
Chapter Three Forecasting
EXAMPLE
Determining a Regression Equation
Sales of new houses and three-month lagged unemployment are shown in the following
table. Determine if unemployment levels can be used to predict demand for new houses
and, if so, derive a predictive equation.
Period . . . . . . . . . . . . . 1
Units sold . . . . . . . . . . 20
Unemployment %
(three-month lag)
7.2
1.
2
41
3
17
4
35
5
25
6
31
7
38
8
50
9
15
10
19
11
14
4.0
7.3
5.5
6.8
6.0
5.4
3.6
8.4
7.0
9.0
Plot the data to see if a linear model seems reasonable. In this case, a linear model
seems appropriate for the range of the data.
50
Units sold, y
40
30
20
10
0
2
4
6
8
10
Level of unemployment (%), x
2.
Check the correlation coefficient to confirm that it is not close to zero using the website template, and then obtain the regression equation:
r = −.966
This is a fairly high negative correlation. The regression equation is
y = 71.85 − 6.91x
Note that the equation pertains only to unemployment levels in the range 3.6 to 9.0, because
sample observations covered only that range.
x
103
8
mhhe.com/stevenson14e
S O L U T I O N
Solved Problems
At the end of chapters
and chapter ­supplements,
“Solved Problems” are
­provided to illustrate
­problem solving and the
core ­concepts in the chapter.
These have been carefully
prepared to help students
understand the steps
involved in solving different
types of problems. The Excel
logo indicates that a spreadsheet is available on the
text’s website.
2.
Strategy formulation is critical because strategies provide direction for the organization, so they
can play a role in the success or failure of a business organization.
3.
Functional strategies and supply chain strategies need to be aligned with the goals and strategies
of the overall organization.
4.
The three primary business strategies are low cost, responsiveness, and differentiation.
5.
Productivity is a key factor in the cost of goods and services. Increases in productivity can
become a competitive advantage.
6.
High productivity is particularly important for organizations that have a strategy of low costs.
competitiveness, 42
core competencies, 46
environmental scanning, 48
goals, 44
mission, 44
mission statement, 44
operations strategy, 51
order qualifiers, 48
order winners, 48
productivity, 56
quality-based strategies, 52
strategies, 44
SWOT, 48
tactics, 45
time-based strategies, 53
SOLVED PROBLEMS
Computing Productivity
A company that processes fruits and vegetables is able to produce 400 cases of canned peaches in
one-half hour with four workers. What is labor productivity?
400 cases
Quantity produced
Labor productivity = ________________ = ________________________
Labor hours
4 workers × 1 / 2 hour / worker
Problem 1
mhhe.com/stevenson14e
Solution
= 200 cases per labor hour
Computing Multifactor Productivity
A wrapping-paper company produced 2,000 rolls of paper in one day. Labor cost was $160, material
cost was $50, and overhead was $320. Determine the multifactor productivity.
Quantity produced
Multifactor productivity = ______________________________
Labor cost + Material cost + Overhead
Problem 2
mhhe.com/stevenson14e
Solution
2,000 rolls
= _______________ = 3.77 rolls per dollar input
$160 + $50 + $320
A variation of the multifactor productivity calculation incorporates the standard price in the
numerator by multiplying the units by the standard price.Rev.Confirming Pages
Computing Multifactor Productivity
Compute the multifactor productivity measure for an eight-hour day in which the usable output was
300 units, produced by three workers who used 600 pounds of materials. Workers have an hourly
wage of $20, and material cost is $1 per pound. Overhead is 1.5 times labor cost.
TABLE 16.5 Excel solution for Example 2a
KEY TERMS
Chapter Sixteen Scheduling Usable output
707
Multifactor productivity = __________________________________
Labor cost + Material cost + Overhead cost
300 units
= _____________________________________________________
(3 workers × 8 hours × $20 / hour) + (600 pounds × $1 / pound) +
(3 workers × 8 hours × $20 / hour × 1.50)
300 units
= ________________
$480 + $600 + $720
= .167 units of output per dollar of input
Problem 3
mhhe.com/stevenson14e
Solution
Excel Spreadsheet
Solutions
ste3889X_ch02_040-073.indd
63
Where applicable, the
­examples and solved
­problems include screen
shots of a spreadsheet
solution.
09/04/19 09:59 AM
Source: Microsoft
c.
Using earliest due date as the selection criterion, the job sequence is C-A-E-B-D-F.
The measures of effectiveness are as follows (see table):
(1) Average flow time: 110/6 = 18.33 days
(2) Average tardiness: 38/6 = 6.33 days
(3) Average number of jobs at the work center: 110/41 = 2.68
xi
CHAPTER ELEMENTS
Within each chapter, you will find the following elements
that are designed to facilitate study and learning. All of
these have been carefully developed over many editions and
have proven to be successful.
Learning Objectives
Every chapter and supplement lists the ­learning
objectives to achieve when studying the ­chapter
material. The learning objectives are also
included next to the specific material in the
­margins of the text.
Rev.Confirming Pages
Rev.Confirming Pages
4
Product and Service
Design
C H A P T E R
LEARNING OBJECTIVES
After completing this chapter, you should be able to:
LO4.1
Explain the strategic importance of product and service design.
LO4.2
Describe what product and service design does.
LO4.3
Name the key questions of product and service design.
LO4.4
Identify some reasons for design or redesign.
LO4.5
List some of the main sources of design ideas.
LO4.6
Discuss the importance of legal, ethical, and sustainability considerations in product and service design.
LO4.7
Explain the purpose and goal of life-cycle assessment.
LO4.8
Explain the phrase “the 3 Rs.”
LO4.9
Briefly describe the phases in product design and development.
LO4.10
Discuss several key issues in product or service design.
LO4.11
Discuss the two key issues in service design.
LO4.12
List the characteristics of well-designed service systems.
LO4.13
List some guidelines for successful service design.
C H A P T E R
4.1
Mark Lennihan/AP Images
4.11 Service Design 165
Overview of Service Design 166
Differences between
Service Design and
Product Design 166
Phases in the Service Design
Process 167
Service Blueprinting 168
Characteristics of WellDesigned Service Systems 168
Challenges of Service
Design 169
Guidelines for Successful
Service Design 169
4.12 Operations Strategy 170
Operations Tour: High Acres
Landfill 174
Chapter Supplement:
Reliability 176
O U T L I N E
Introduction 140
4.7
What Does Product and Service
Design Do? 140
Objectives of Product and
Service Design 141
Key Questions 141
Reasons for Product or Service
Design or Redesign 141
4.2
Idea Generation 142
4.3
Legal and Ethical
Considerations 144
4.4
Human Factors 145
4.5
Cultural Factors 145
4.6
Global Product and Service
Design 146
4.8
Environmental Factors:
Sustainability 146
Designing for Mass
Customization 154
Reliability 156
Robust Design 157
Degree of Newness 158
Quality Function Deployment 158
The Kano Model 160
Cradle-to-Grave Assessment 146
End-of-Life Programs 147
The Three Rs: Reduce, Reuse,
and Recycle 147
Reduce: Value Analysis 147
Reuse: Remanufacturing 148
Recycle 149
4.9
Other Design
Considerations 151
4.10 Designing for Production 163
Strategies for Product or
Service Life Stages 151
Product Life Cycle
Management 153
Degree of Standardization 153
Phases in Product Design
and Development 162
Concurrent Engineering 163
Computer-Aided Design
(CAD) 164
Production Requirements 165
Component Commonality 165
The essence of a business organization is the products and services it offers, and every
LO4.1 Explain the strateaspect of the organization and its supply chain are structured around those products
gic importance of product
and services. Organizations that have well-designed products or services are more
and service design.
likely to realize their goals than those with poorly designed products or services. Hence,
organizations have a strategic interest in product and service design. Product or service design should be closely tied
to an organization’s strategy. It is a major factor in cost, quality, time-to-market, customer satisfaction, and competitive
advantage. Consequently, marketing, finance, operations, accounting, IT, and HR need to be involved. Demand forecasts and projected costs are important, as is the expected impact on the supply chain. It is significant to note that an
important cause of operations failures can be traced to faulty design. Designs that have not been well thought out, or
are incorrectly implemented, or instructions for assembly or usage that are wrong or unclear, can be the cause of product and service failures, leading to lawsuits, injuries and deaths, product recalls, and damaged reputations.
continued
138
ste3889X_ch04_138-175.indd 138
139
08/01/19 07:17 AM
ste3889X_ch04_138-175.indd
139
Chapter Outlines
Opening Vignettes
Every chapter and supplement includes an
outline of the topics covered.
Each chapter opens with an introduction to the
important operations topics covered in the ­chapter.
This enables students to see the relevance of
­operations management in order to actively engage
in learning the material.
xii
08/01/19 07:17 AM
Figures and Photos
The text includes photographs and
graphic illustrations to support
­student learning and provide interest
and motivation. Approximately 100
­carefully selected photos highlight
the 14th edition. The photos illustrate
applications of operations and supply
chain concepts in many successful
companies. More than 400 graphic
illustrations, more than any other
text in the field, are included and all
are color coded with ­pedagogical
­consistency to assist students in
understanding concepts.
56
Chapter Two
A major key to Apple’s continued
success is its ability to keep pushing
the boundaries of innovation. Apple
has demonstrated how to create
growth by dreaming up products so
new and ingenious that they have
upended one industry after another.
Rev.Confirming Pages
246
Chapter Six
Process Selection and Facility Layout
FIGURE 6.1
Process selection and
capacity planning influence
system design
Inputs
Outputs
Forecasting
Facilities and
equipment
Capacity
Planning
Product and
service design
Layout
Rev.Confirming Pages
Process
Selection
Technological
change
Work
design
Competitiveness, Strategy, and Productivity
LO6.1 Explain the
strategic importance of
process selection and the
influence it has on the
organization and its supply
chain.
6.1 INTRODUCTION
Process selection refers to deciding on the way production of goods or services will be organized. It has major implications for capacity planning, layout of facilities, equipment, and
design of work systems. Process selection occurs as a matter of course when new products or
services are being planned. However, it also occurs periodically due to technological changes
in products or equipment, as well as competitive pressures. Figure 6.1 provides an overview
of where process selection and capacity planning fit into system design. Forecasts, product
and service design, and technological considerations all influence capacity planning and process selection. Moreover, capacity and process selection are interrelated, and are often done in
concert. They, in turn, affect facility and equipment choices, layout, and work design.
How an organization approaches process selection is determined by the organization’s process strategy. Key aspects include:
• Capital intensity: The mix of equipment and labor that will be used by the organization.
• Process flexibility: The degree to which the system can be adjusted to changes in
processing requirements due to such factors as changes in product or service design,
changes in volume processed, and changes in technology.
Pieter Beens/Shutterstock
Moreover, this approach pays little attention to suppliers and government regulations, and
community, environmental, and sustainability issues are missing. These are closely linked,
theoftwo
and business organizations LO6.2
need to Name
be aware
the impact they are having in these areas and
Process
choice
demand-driven.
main factors
that influence
respond accordingly. Otherwise,
organizations
may be subject
to attack
by is
pressure
groups The two key questions in process selection are:
process selection.
and risk damage to their reputation.
6.2 PROCESS SELECTION
1.
2.
LO2.6 Define the term
productivity and explain
why it is important to companies and to countries.
Productivity A measure of
the effective use of resources,
usually expressed as the ratio
of output to input.
How much variety will the process need to be able to handle?
How much volume will the process need to be able to handle?
Answers to these questions will serve as a guide to selecting an appropriate process. Usually, volume and variety are inversely related; a higher level of one means a lower level of the
other. However, the need for flexibility of personnel and equipment is directly related to the
One of the primary responsibilities of a manager is to achieve productive use of an organizalevel
of variety the
will need to handle: The lower the variety, the less the need for
tion’s resources. The term productivity is used to describe this.
Productivity
is anprocess
index that
flexibility,
while
the higher
the variety, the greater the need for flexibility. For example, if a
measures output (goods and services) relative to the input (labor,
materials,
energy,
and other
worker’s
job to
in input:
a bakery is to make cakes, both the equipment and the worker will do the same
resources) used to produce it. It is usually expressed as the ratio
of output
thing day after day, with little need for flexibility. But if the worker has to make cakes, pies,
Output
cookies, brownies, and croissants,
both the worker and the equipment must have the flexibilProductivity = ______
(2–1)
Input
ity to be able to handle the different requirements of each type of product.
Thereitisisanother
aspect
of variety that is important. Variety means either having dedicated
Although productivity is important for all business organizations,
particularly
impordifferentthe
product or service, or if not, having to get equipment ready every
tant for organizations that use a strategy of low cost, becauseoperations
the higherfor
theeach
productivity,
time there is the need to change the product being produced or the service being provided.
lower the cost of the output.
2.7 PRODUCTIVITY
A productivity ratio can be computed for a single operation, a department, an organization, or an entire country. In business organizations, productivity ratios are used for planning
workforce requirements, scheduling equipment, financial analysis, and other important tasks.
Productivity has important implications for business organizations and for entire nations.
For nonprofit organizations, higher productivity means lower costs; for profit-based organizations, productivity is an important factor in determining how competitive a company is. For
a nation, the rate of productivity
growth is of great importance. Productivity growth is the
ste3889X_ch06_244-299.indd 246
increase in productivity from one period to the next relative to the productivity in the preceding period. Thus,
Current productivity − Previous productivity
Productivity growth = _____________________________________ × 100
Previous productivity
(2–2)
08/01/19 07:28 AM
xiii
Rev.Confirming Pages
Chapter Five
Strategic Capacity Planning for Products and Services
213
Operations Strategies
5.12 OPERATIONS STRATEGY
An Operations Strategy section
The strategic implications of capacity decisions can be enormous, impacting all areas of the
organization. From an operations management standpoint, capacity decisions establish a set
is included at the end of most
of conditions within which operations will be required to function. Hence, it is extremely
­chapters. These sections discuss
important to include input from operations management people in making capacity decisions.
how the chapters’ concepts can
Flexibility can be a key issue in capacity decisions, although flexibility is not always an
option, particularly in capital-intensive industries. However, where possible, flexibility allows
be applied and how they impact
an organization to be agile—that is, responsive to changes in the marketplace. Also, it reduces
the operations of a company.
to a certain extent the dependence on long-range forecasts to accurately predict demand. And
flexibility makes it easier for organizations to take advantage of technological and other innovations. Maintaining excess capacity (a capacity cushion) may provide a degree of flexibility,
albeit at added cost.
Some organizations use a strategy of maintaining a capacity cushion for the purpose of
blocking entry into the market by new competitors. The excess capacity enables them to produce at costs lower than what new competitors can. However, such a strategy means higherthan-necessary unit costs, and it makes it more difficult to cut back if demand slows, or to
shift to new product or service offerings.
Efficiency improvements and utilization improvements can provide capacity increases.
Such improvements can be achieved by streamlining operations and reducing waste. The
chapter on lean operations describes ways for achieving those improvements.
Bottleneck management can be a way to increase effective capacity, by scheduling nonbottleneck operations to achieve maximum utilization of bottleneck operations.
In cases where capacity expansion will be undertaken, there are two strategies for determining the timing and degree of capacity expansion. One is the expand-early strategy (i.e.,
before demand materializes). The intent might be to achieve economies of scale, to expand
Rev.Confirming Pages
market share, or to preempt competitors from expanding. The risks of this strategy include
an oversupply that would drive prices down, and underutilized equipment that would result in
higher unit costs.
The other approach is the wait-and-see strategy (i.e., to expand capacity only after demand
materializes, perhaps incrementally). Its advantages include a lower chance of oversupply due
to more accurate matching of supply and demand,
and higher capacity utilization. The key
READING
DUTCH BOY BRUSHES UP ITS PAINTS
risks are loss of market share and the inability to meet demand if expansion requires a long
lead time.
Sherwin-Williams’ Dutch Boy Group put a revolutionary spin on
In cases where capacity contraction will paint
be undertaken,
capacity
disposal Twist
strategies
cans with its innovative
square-shaped
& PourTM
become important. This can be the result of thepaint-delivery
need to replace
equipment
with
container aging
for the Dirt
Fighter interior
latexnewer
paint line.
The four-piece
square containeroperations.
could be the first
major
change
equipment. It can also be the result of outsourcing
and downsizing
The
cost
or in
how house paint is packaged in decades. Lightweight but sturdy,
benefit of asset disposal should be taken into account
when
contemplating
these
actions.
the Twist & Pour “bucket” is packed with so many conveniences, it
Readings
is next to impossible to mess up a painting project.
Winning Best of Show in an AmeriStar packaging competition sponsored by the Institute of Packaging Professionals, the
exclusive,
paint services
container stands
7½ in. time
tall and
Capacity refers to a system’s potential for producing goods orall-plastic
delivering
over aalmost
specified
holds 126isoz.,
a bit lesson
than
1 gal. Rust-resistant
moistureinterval. Capacity decisions are important because capacity
a ceiling
output
and a majorand
determiresistant, the plastic bucket gives users a new way to mix, brush,
nant of operating costs.
and store paint.
Three key inputs to capacity planning are the kind ofA capacity
thatonwill
muchtowill
hollow handle
one be
sideneeded,
makes it how
comfortable
pourbe
and
needed, and when it will be needed. Accurate forecasts
areA critical
to the
planning
process.
carry.
convenient,
snap-in
pour spout
neatly pours paint into
a trayimportant
with no dripping
but canthat
be removed
if desired,
allow
The capacity planning decision is one of the most
decisions
managers
make.toThe
a wide
brushinvolving
to be dipped
into the 5¾-in.-diameter
mouth. Capcapacity decision is strategic and long term in nature,
often
a significant
initial investment
ping
the
container
is
a
large,
twist-off
lid
that
requires
no
tools
of capital. Capacity planning is particularly difficult in cases where returns will accrue over a lengthyto
open or close. Molded with two lugs for a snug-finger-tight closperiod, and risk is a major consideration.
ing, the threaded cap provides a tight seal to extend the shelf life
A variety of factors can interfere with effective capacity,
so effective capacity is usually somewhat
of unused paint.
less than design capacity. These factors include facilities
and layout,
product/
Whiledesign
the lid requires
no tools human
to access,factors,
the snap-off
carry bail
is assembled
on theconsiderations.
container in a “locked-down position” and
service design, equipment failures, scheduling problems,
and quality
can
be
pulled
up
after
purchase
for
toting
or
hanging
on
a ladder.
Capacity planning involves long-term and short-term considerations. Long-term considerations relate
Large, nearly 4½-inch-tall label panels allow glossy front and back
to the overall level of capacity; short-term considerations relate to variations in capacity requirements
labels printed and UV-coated to wrap around the can’s rounded
due to seasonal, random, and irregular fluctuations corners,
in demand.
Ideally, display.
capacity will match demand.
for an impressive
Jim MacDonald, co-designer of the Twist & Pour and a packaging engineer at Cleveland-based Sherwin-Williams, tells Packaging
Digest that the space-efficient, square shape is easier to ship and
easier to stack in stores. It can also be nested, courtesy of a recess
Readings highlight important
real-world applications, ­provide
examples of production/­
operations issues, and offer
further elaboration of the text
material. They also provide a
basis for classroom discussion
and generate interest in the
subject matter. Many of the
end-of-chapter readings include
assignment questions.
ste3889X_ch05_190-221.indd 213
xiv
LO4.5 List some of the
main sources of design
ideas.
SUMMARY
Jerry Simon
in the bottom that mates with the lid’s top ring. “The new design
allows for one additional shelf facing on an eight-foot rack or
shelf area.”
The labels are applied automatically, quite a feat, considering
their complexity, size, and the hollow handle they likely encounter
during application. MacDonald admits, “Label application was a
challenge. We had to modify the bottle several times to accommodate the labeling machinery available.”
Source: “Dutch Boy Brushes Up Its Paints,” Packaging Digest, October 2002.
Copyright ©2002 Reed Business Information. Used with permission.
4.2 IDEA GENERATION
08/01/19 07:22 AM
Ideas for new or redesigned products or services can come from a variety of sources, including customers, the supply chain, competitors, employees, and research. Customer input can
come from surveys, focus groups, complaints, and unsolicited suggestions for improvement.
Input from suppliers, distributors, and employees can be obtained from interviews, direct or
indirect suggestions, and complaints.
One of the strongest motivators for new and improved products or services is competitors’ products and services. By studying a competitor’s products or services and how the
competitor operates (pricing policies, return policies, warranties, location strategies, etc.), an
organization can glean many ideas. Beyond that, some companies purchase a competitor’s
∑ y − b∑ t
a = ______ or ¯y − b¯t
n
Trend-adjusted
forecast
Linear regression
forecast
TAF t+1 = S t + T t
where
S t = TAF t + α( A t − TAF t)
T t = T t−1 + β( TAF t − TAF t−1 − T t−1)
t = Current period
TAF t+1 = Trend-adjusted forecast for
next period
S = Previous forecast plus
smoothed error
T = Trend component
Y c = a + bx
where
n (∑ xy ) − (∑ x) (∑ y)
b = _____________________
n(∑ x 2) − (∑ x 2)
y c = Computed value of dependent
variable
x = Predictor (independent) variable
b = Slope of the line
a = Value of y c when x = 0
∑ y − b∑ x
a = ______ or ¯y − b¯x
n
END-OF-CHAPTER RESOURCES
Standard error of
estimate

________
Se =
(y − y c) 2

_______
n−2
S e = Standard error of estimate
y = y value of each data point
n = Number of data points
For student study and review, the following items are



­provided at the end
of each chapter or chapter supplement.
t
Tracking signal
∑e
TS t = _____
MAD t
Control limits
UCL = 0 + z MSE
_____
LCL = 0 − z MSE
_____
_____
MSE = standard deviation
z = Number of standard deviations;
2 and 3 are typical values
Microsoft
1.
2.
3.
4.
Demand forecasts are essential inputs for many business decisions. They help managers decide
how much supply or capacity will be needed to match expected demand, both within the organization and in the supply chain.
Because of random variations in demand, it is likely that the forecast will not be perfect, so managers need to be prepared to deal with forecast errors.
Other, nonrandom factors might also be present, so it is necessary to monitor forecast errors to
check for nonrandom patterns in forecast errors.
It is important to choose a forecasting technique that is cost-effective and one that minimizes forecast error.
associative model, 80
judgmental forecasts, 80
regression, 98
bias, 109
least squares line, 99
seasonality, 82
centered moving average, 96
linear trend equation, 89
seasonal relative, 94
Chapter
One deviation
Introduction to Operations
Management
control chart, 107
mean absolute
seasonal variations,
93
correlation, 102
(MAD), 106
standard error of estimate, 100
cycle, 82
mean absolute percent error
time series, 82
7. What
are models
Delphi
method,and
81why are they important?
(MAPE), 106
time-series forecasts, 80
8. Why
is the
degree of customization an mean
important
consideration
in process
error,
105
squared
error (MSE),
106 planning?
tracking signal, 109
smoothing,
87consider for
moving
trend, 82
9. Listexponential
the trade-offs
you would
each average,
of these 84
decisions:
focus forecasting, 88
naive forecast, 82
trend-adjusted exponential
a. Driving your own car versus public transportation.
forecast, 76
predictor variables, 98
smoothing, 92
b. irregular
Buying a variation,
computer 82
now versus waiting
for an
improved82model.
random
variations,
weighted average, 86
c. Buying a new car versus buying a used car.
d. Speaking up in class versus waiting to get called on by the instructor.
e. A small business owner having a website versus newspaper advertising.
Taking Stock and Critical
Thinking Exercises
10. Describe each of these systems: craft production, mass production, and lean production.
11. Why might some workers prefer not to work in a lean production environment?
12. Discuss the importance of each of the following:
a. ste3889X_ch03_074-137.indd
Matching supply and demand
117
b. Managing a supply chain
These
activities encourage analytical thinking
13. List and briefly explain the four basic sources of variation, and explain why it is important for
managers to be able to effectively deal with variation.
and14.help
broaden
conceptual
understanding.
Why do people
do things that
are unethical?
15. Explain the term value-added.
A ­q16.uestion
related to ethics is included in the
Discuss the various impacts of outsourcing.
17. Discuss the term sustainability, and its relevance for business organizations.
­Critical
Thinking Exercises.
This item appears at the end of each chapter. It is intended to focus your attention on three key
issues for business organizations in general, and operations management in particular. Those issues
are trade-off decisions, collaboration among various functional areas of the organization, and the
impact of technology. You will see three or more questions relating to these issues. Here is the first
set of questions:
1. What are trade-offs? Why is careful consideration of trade-offs important in decision making?
2. Why is it important for the various functional areas of a business organization to collaborate?
3. In what general ways does technology have an impact on operations management decision
making?
This item also will appear in every chapter. It allows you to critically apply information you learned in
the chapter to a practical situation. Here is the first set of exercises:
1. Many organizations offer a combination of goods and services to their customers. As you learned
in this chapter, there are some key differences between the production of goods and the delivery of
services. What are the implications of these differences relative to managing operations?
2. Why is it important to match supply and demand? If a manager believes that supply and demand
will not be equal, what actions could the manager take to increase the probability of achieving a
match?
3. One way that organizations compete is through technological innovation. However, there can be
downsides for both the organization and the consumer. Explain.
4. What ethical considerations are important in development of technology in general, as well as AI
(artificial intelligence)?
5. a. What would cause a businessperson to make an unethical decision?
Problem Sets
b. What are the risks of doing so?
Each chapter includes a set of problems
for assignment. The problems have been
refined over many editions and are intended
to be challenging but doable for students.
Short answers to most of the problems
are included in Appendix A so students
can check their understanding and see
­immediately how they are progressing.
ste3889X_ch01_002-039.indd 37
Summaries and Key Points
KEY POINTS
Chapters contain summaries that provide an
overview of the material covered, and the
key points of the chapter are emphasized in a
­separate section.
Rev.Confirming Pages
KEY TERMS
37
Confirming Pages
Key Terms
Key
terms are highlighted in the text and then217
Strategic Capacity Planning for Products and Services
repeated
in the margin with brief definitions for
5. Give some examples of building flexibility into system design.
6. Why is it important to adopt a big-picture
approach to capacity
planning?
emphasis.
They
are listed at the end of each
7. What is meant by “capacity in chunks,” and why is that a factor in capacity planning?
8. What kinds of capacity problems do chapter
many elementary(along
and secondarywith
schools periodically
page experireferences) to aid in
ence? What are some alternatives to deal with those problems?
9. How can a systems approach to capacity
planning be useful?
reviewing.
Chapter Five
09/25/19 10:58 AM
10. How do capacity decisions influence productivity?
11. Why is it important to match process capabilities with product requirements?
12. Briefly discuss how uncertainty affects capacity decisions.
13. Discuss the importance of capacity planning in deciding on the number of police officers or fire
trucks to have on duty at a given time.
Discussion and Review Questions
14. Why is capacity planning one of the most critical decisions a manager has to make?
15. Why is capacity planning for services more challenging than it is for goods production?
16. What are some capacity measures for each of the following?
Each chapter and each supplement have a
list of discussion and review questions. These
Computer repair shop
TAKING c.STOCK
d. Farm
precede
sets and are intended
17. What is the benefit to a business organization
of havingthe
capacityproblem
measures?
to serve as a student self-review or as class
1. What are the major trade-offs in capacity planning?
TAKING STOCK
iscussion starters.
2. Who needs to be involved in capacity­d
planning?
a. University
b. Hospital
3. In what ways does technology have an impact on capacity planning?
1. A computer repair service has a design capacity of 80 repairs per day. Its effective capacity, however, is 64 repairs per day, and its actual output is 62 repairs per day. The manager would like to
increase
the number of repairs per day because demand is higher than 70 repairs per day, creating a
CRITICAL
THINKING
backlog of orders. Which factors would you recommend that the manager investigate? Explain your
EXERCISES
CRITICAL THINKING
EXERCISES
reasoning.
2. Compared to manufacturing, service requirements tend to be more time dependent, location dependent, and volatile. In addition, service quality is often directly observable by customers. Find a
recent article in a business magazine that describes how a service organization is struggling with
one or more of these issues and make recommendations on what an organization needs to do to
overcome these difficulties.
3. Identify four potential unethical actions or inactions related to capacity planning, and the ethical
principle each violates (see Chapter 1).
4. Any increase in efficiency also increases utilization. Although the upper limit on efficiency is
100 percent, what can be done to achieve still higher levels of utilization?
1. Determine the utilization and efficiency for each of the following situations.
a. A loan processing operation that processes an average of 7 loans per day. The operation has a
design capacity of 10 loans per day and an effective capacity of 8 loans per day.
PROBLEMS
b. A furnace repair team that services an average of four furnaces a day if the design capacity is
six furnaces a day and the effective capacity is five furnaces a day.
c. Would you say that systems that have higher efficiency ratios than other systems will always
have higher utilization ratios than those other systems? Explain.
2. In a job shop, effective capacity is only 50 percent of design capacity, and actual output is 80 percent
of effective output. What design capacity would be needed to achieve an actual output of eight jobs
per week?
08/01/19 06:47 AM
ste38891_ch05_190-221.indd
217
07/12/19 04:29 PM
xv
Marty designed: the Arrow and the Dart. The company hasn’t
turned a profit yet, but Marty feels that once he resolves some of
the problems he’s having with inventory and scheduling, he can
increase productivity and reduce costs.
At first, he ordered enough bike parts and subassemblies for
four months’ worth of production. Parts were stacked all over the
place, seriously reducing work space and hampering movement
of workers and materials. And no one knew exactly where anything was. In Marty’s words, “It was a solid mess!”
He and his two partners eventually managed to work off
most of the inventory. They hope to avoid similar problems in the
future by using a more orderly approach. Marty’s first priority is to
develop a materials requirement plan for upcoming periods. He
wants to assemble 15 Arrows and 10 Darts each week, to have
them ready at the start of weeks 4 through 8. The product structure trees for the two bikes follow.
Operations Tours
Arrow
Dart
These provide a simple “walkthrough” of an ­operation
Chapter Thirteen MRP and ERP
for students, describing the company, its product
M
X
K(2)
F
17. The MRP Department has a problem. Its computer
“died”
just as it spit W
out the following
inforor service, and
its Planned
process
of managing
operations.
mation:
order release
for item J27 = 640
units in week 2. The firm has been able to
F the master schedule for end item 565. The firm is
reconstruct all the information they lost except
­Companies featured
include
Wegmans
Food
Markets,
fortunate because
J27 is used
only in 565s. Given
the following
productW(2)
structure tree and assoQ
ciated inventory status record information, determine what master schedule entry for 565 was
Morton Salt, Stickley
and Boeing.
exploded intoFurniture,
the material requirements
plan that killed the computer.
Part Number
565
X43
N78
Y36
J27
On Hand
0
60
0
200
0
Lot Size
Lead Time
565
Lot-for-lot
1 week
Multiples of 120
1 week
X43
Y36 (2)
N78
Lot-for-lot
2 weeks
Lot-for-lot
1 week
OPERATIONS TOUR
J27 (4)
X43
Lot-for-lot
2 weeks
D(2)
E(2)
H(3)
2
5
Lot-for-lot
Dart
2
2
Lot-for-lot
X
1
5
Multiples of 25
W
2*
2
Multiples of 12
F
1
10
Multiples of 30
K
1
3
Lot-for-lot
Q
1
15
Multiples of 30
M
1
0
Lot-for-lot
*LT = 3 weeks for orders of 36 or more units on this item
Confirming Pages
Scheduled receipts are:
Period 1:
Period 2:
20 Arrows and 18 Ws
20 Darts and 15 Fs
As the third partner, it is your job to develop the material requirements plan.
605
STICKLEY FURNITURE
18. Develop a material requirements plan for component H. Lead times for the end item and each component except B are one week. The lead time forIntroduction
B is three weeks. Sixty units of A are needed at the start
of week 8. There are currently 15 units of B on hand and 130 of E on hand, and 50 units of H are in
production and will be completed by the start www.stickley.com
of week 2. Lot-for-lot ordering will be used for all items.
B(2)
Arrow
in New York State, two in Connecticut, one in North Carolina, and
its furniture is sold nationally by some 120 dealers.
AL. & J.G. Stickley was founded in 1900 by brothers Leopold and
Production
George Stickley. Located just outside of Syracuse, New York, the
company is a producer of fine cherry, white oak, and mahogany
furniture. In the 1980s, the company reintroduced the company’s
original line of Cmission oak furniture, which now accounts for
nearly 50 percent of the company’s sales.
Over the years, the company experienced both good and bad
times, and at one point it employed over 200 people. However,
by the
was in disarray; there were only
D(2)early 1970s, the business
E(4)
about 20 full-time employees, and the company was on the brink
of bankruptcy. The present owners bought the ailing firm in 1974,
and under their leadership, the company has prospered and grown,
and
has five retail showrooms
K now has 1,350
H(3)employees. Stickley
K
The production facility is a large, rectangular building with a
30-foot ceiling. Furniture making is labor intensive, although saws,
sanders, and other equipment are very much a part of the process. In fact, electric costs average about $60,000 a month. The
company has its own tool room where cutting tools are sharpened, and replacement parts are produced as needed.
Worker skills range from low-skilled material handlers to highly
skilled craftsmen. For example, seven master cabinet makers handle customized orders.
The process (see figure below) begins with various sawing
operations where large boards received from the lumber mills
are cut into smaller sizes. The company recently purchased a
606
CASE
PROMOTIONAL NOVELTIES
ste3889X_ch13_560-609.indd
Promotional Novelties provides a wide range of novelty items for
its corporate customers. It has just received an order for 20,000
toy tractor-trailers that will be sold by a regional filling station company as part of a holiday promotion. The order is to be shipped
at the beginning of week 8. The tree diagram shows the various
components of the trucks.
Tractor-trailer
Tractor
Wheel
assembly
Trailer
Body
Wheel
assembly
Body
606
08/08/19 09:27 AM
The company can complete final assembly of the tractortrailers at the rate of 10,000 a week. The tractor and trailer bodies
are purchased; lead time is three weeks. The wheels are the
manager’s main concern.
The company has a sufficient supply of brackets on hand.
Assembly time is one week each for tractors, trailers, and wheel
assembly. However, the wheel department can only produce
wheels at the rate of 100,000 a week. The manager plans to
use the wheel department to full capacity, starting in week 2
of the schedule, and order additional wheels from a supplier
as needed. Ordered wheels come in sets of 6,400. The lead
time for delivery from the supplier is expected to be two to
three weeks. Use lot-for-lot ordering for all items except the
purchased wheels.
Questions
Wheels (6)
Bracket
ste3889X_ch13_560-609.indd
Wheels (12)
Bracket
1. How many wheel sets should the manager order?
2. When should the wheel sets be ordered?
605
08/08/19 09:27 AM
Cases
The text includes short cases. The cases were
selected to provide a broader, more integrated
thinking opportunity for students without taking
a full case approach.
xvi
INSTRUCTOR RESOURCES
Available within Connect, instructors have access to teaching supports such as electronic files
of the ancillary materials: Solutions Manual, Instructor’s Manual, Test Bank, PowerPoint
Lecture Slides, Digital Image Library, and accompanying Excel files.
Instructor’s Manual. This manual, revised for the new edition by Tracie Lee, Idaho
State University, includes teaching notes, chapter overview, an outline for each chapter, and
­solutions to the problems in the text.
Test Bank. Updated for the new edition by Leslie Sukup, Ferris State University, and
reviewed by Nancy Lambe, University of South Alabama, the Test Bank includes over
2,000 true/false, multiple-choice, and discussion questions/problems at varying levels of
difficulty. The Test Bank is available to assign within Connect, as Word files available in
the Instructor Resource Library, and through our online test generator. Instructors can organize, edit, and customize questions and answers to rapidly generate tests for paper or online
administration.
PowerPoint Lecture Slides. Revised by Avanti Sethi, University of Texas-Dallas, the
PowerPoint slides draw on the highlights of each chapter and provide an opportunity for the
instructor to emphasize the key concepts in class discussions.
Digital Image Library. All the figures in the book are included for insertion in PowerPoint
slides or for class discussion.
xvii
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Note to Students
The material in this text is part of the core knowledge in your
education. Consequently, you will derive considerable benefit from your study of operations management, regardless
of your major. Practically speaking, operations is a course in
management.
This book describes principles and concepts of operations
management. You should be aware that many of these principles and concepts are applicable to other aspects of your
professional and personal life. You can expect the benefits of
your study of operations management to serve you in those
other areas as well.
Some students approach this course with apprehension, and
perhaps even some negative feelings. It may be that they have
heard that the course contains a certain amount of quantitative
material that they feel uncomfortable with, or that the subject
matter is dreary, or that the course is about “factory management.” This is unfortunate, because the subject matter of this
book is interesting and vital for all business students. While
it is true that some of the material is quantitative, numerous
examples, solved problems, and answers at the back of the
book help with the quantitative material. As for “factory management,” there is material on manufacturing, as well as on
services. Manufacturing is important, and something that you
should know about for a number of reasons. Look around you.
Most of the “things” you see were manufactured: cars, trucks,
planes, clothing, shoes, computers, books, pens and pencils,
desks, and cell phones. And these are just the tip of the iceberg. So it makes sense to know something about how these
things are produced. Beyond all that is the fact that manufacturing is largely responsible for the high standard of living
people have in industrialized countries.
After reading each chapter or supplement in the text,
attending related classroom lectures, and completing assigned
questions and problems, you should be able to do each of the
following:
1. Identify the key features of that material.
2. Define and use terminology.
3. Solve typical problems.
4. Recognize applications of the concepts and techniques
covered.
xx
5. Discuss the subject matter in some depth, including its
relevance, managerial considerations, and advantages
and limitations.
You will encounter a number of chapter supplements.
Check with your course syllabus to determine which ones are
included.
This book places an emphasis on problem solving. There
are many examples throughout the text illustrating solutions.
In addition, at the end of most chapters and supplements you
will find a group of solved problems. The examples within
the chapter itself serve to illustrate concepts and techniques.
Too much detail at those points would be counterproductive.
Yet, later on, when you begin to solve the end-of-chapter
problems, you will find the solved problems quite helpful.
Moreover, those solved problems usually illustrate more and
different details than the problems within the chapter.
I suggest the following approach to increase your chances
of getting a good grade in the course:
1. Do the class preparation exercises for each chapter if
they are available from your instructor.
2. Look over the chapter outline and learning objectives.
3. Read the chapter summary, and then skim the chapter.
4. Read the chapter and take notes.
5. Look over and try to answer some of the discussion and
review questions.
6. Work the assigned problems, referring to the solved
problems and chapter examples as needed.
Note that the answers to many problems are given at the
end of the book. Try to solve each problem before turning to
the answer. Remember—tests don’t come with answers.
And here is one final thought: Homework is on the
Highway to Success, whether it relates to your courses, the
workplace, or life! So do your homework, so you can have a
successful journey!
W.J.S.
Brief Contents
Preface
vii
1 Introduction to Operations Management 2
2 Competitiveness, Strategy, and Productivity 40
3 Forecasting 74
4 Product and Service Design 138
SUPPLEMENT TO CHAPTER 4: Reliability 176
5 Strategic Capacity Planning for Products and Services 190
SUPPLEMENT TO CHAPTER 5: Decision Theory 222
6 Process Selection and Facility Layout 244
7 Work Design and Measurement 300
SUPPLEMENT TO CHAPTER 7: Learning Curves 336
8 Location Planning and Analysis 348
9 Management of Quality 378
10 Quality Control 418
11 Aggregate Planning and Master Scheduling 464
12 Inventory Management 502
13 MRP and ERP 560
14 JIT and Lean Operations 610
SUPPLEMENT TO CHAPTER 14: Maintenance 646
15 Supply Chain Management 654
16 Scheduling 692
17 Project Management 732
18 Management of Waiting Lines 784
19 Linear Programming 824
Appendix A: Answers to Selected Problems 858
Appendix B: Tables 870
Appendic C: Working with the Normal Distribution 876
Appendic D: Ten Things to Remember Beyond the Final Exam
Company Index 883
Subject Index 884
882
xxi
Contents
Preface
1
2
vii
Introduction to Operations
Management 2
Introduction 42
Competitiveness 42
Mission and Strategies 44
Readings:
Amazon Ranks High in Customer Service
Introduction 4
Production of Goods Versus Providing
Services 8
Why Learn About Operations Management? 10
Career Opportunities and Professional
Societies 12
Process Management 13
The Scope of Operations Management 14
Reading:
Why Manufacturing Matters 17
Low Inventory Can Increase Agility
Key Issues for Today’s Business Operations
Readings:
Sustainable Kisses 28
Productivity Improvement 62
Summary 62
Key Points 63
Key Terms 63
Solved Problems 63
Discussion and Review Questions
Taking Stock 64
Critical Thinking Exercises 65
Problems 65
27
Cases:
Home-Style Cookies
Diet and the Environment: Vegetarian
vs. Nonvegetarian 29
64
67
68
“Your Garden Gloves”
69
Girlfriend Collective 69
Operations Tour:
The U.S. Postal Service
70
Selected Bibliography and Further Readings
36
3
Case:
Hazel 38
xxii
Hazel Revisited
33
Selected Bibliography and Further Readings
Problem-Solving Guide 39
50
Dutch Tomato Growers’ Productivity Advantage 60
The Historical Evolution of Operations
Management 21
Operations Today 24
Reading:
Agility Creates a Competitive Edge 26
Summary 36
Key Points 36
Key Terms 36
Discussion and Review Questions
Taking Stock 37
Critical Thinking Exercises 37
45
Operations Strategy 51
Implications of Organization Strategy for Operations
Management 54
Transforming Strategy into Action: The Balanced
Scorecard 54
Productivity 56
Readings:
Why Productivity Matters 59
Operations Management and Decision
Making 18
Reading:
Analytics 20
Operations Tour:
Wegmans Food Markets
Competitiveness, Strategy, and
Productivity 40
38
73
Forecasting 74
Introduction 76
Features Common to All Forecasts 78
Elements of a Good Forecast 78
Forecasting and the Supply Chain 79
Steps in the Forecasting Process 79
Approaches to Forecasting 80
Qualitative Forecasts 80
Forecasts Based on Time-Series Data 82
Associative Forecasting Techniques 98
Reading:
Lilacs 104
Legal and Ethical Considerations 144
Human Factors 145
Cultural Factors 145
Reading:
Green Tea Ice Cream? Kale Soup? 146
Global Product and Service Design 146
Environmental Factors: Sustainability 146
Readings:
Kraft Foods’ Recipe for Sustainability 148
Forecast Accuracy 104
Reading:
High Forecasts Can be Bad News 106
China Clamps Down on Recyclables
Recycle City: Maria’s Market
Monitoring Forecast Error 107
Choosing a Forecasting Technique 111
Using Forecast Information 112
Computer Software in Forecasting 113
Operations Strategy 113
Reading:
Gazing at the Crystal Ball 114
Summary 115
Key Points 117
Key Terms 117
Solved Problems 118
Discussion and Review Questions
Taking Stock 125
Critical Thinking Exercises 125
Problems 125
Fast-Food Chains Adopt Mass Customization 155
Phases in Product Design and Development 162
Designing for Production 163
Service Design 165
Reading:
The Challenges of Managing Services 169
Operations Strategy
4
137
137
Operations Tour:
High Acres Landfill
Product and Service Design 138
Reading:
Design as a Business Strategy
140
Introduction 140
Reading:
Dutch Boy Brushes Up Its Paints
142
Idea Generation 142
Reading:
Vlasic’s Big Pickle Slices
143
170
Summary 170
Key Points 171
Key Terms 171
Discussion and Review Questions
Taking Stock 172
Critical Thinking Exercises 172
Problems 172
Cases:
M&L Manufacturing 136
Highline Financial Services, Ltd.
150
Other Design Considerations 151
Readings:
Lego A/S in the Pink 152
124
Selected Bibliography and Further Readings
149
171
174
Selected Bibliography and Further Readings
174
SUPPLEMENT TO CHAPTER 4: Reliability
5
176
Strategic Capacity Planning for Products
and Services 190
Introduction 191
Reading:
Excess Capacity Can Be Bad News!
Capacity Decisions Are Strategic
192
193
xxiii
Contents
xxiv
Defining and Measuring Capacity 194
Determinants of Effective Capacity 196
Strategy Formulation 197
Forecasting Capacity Requirements 198
Additional Challenges of Planning Service Capacity 200
Do It In-House or Outsource It? 201
Reading:
My Compliments to the Chef, Er, Buyer 202
Developing Capacity Strategies
Constraint Management 207
Evaluating Alternatives 207
Operations Strategy 213
Summary 213
Key Points 214
Key Terms 214
Solved Problems 214
Discussion and Review Questions
Taking Stock 217
Critical Thinking Exercises 217
Problems 217
202
Designing Process Layouts
7
Summary 328
Key Points 328
Key Terms 329
Solved Problems 329
Discussion and Review Questions 330
Taking Stock 331
Critical Thinking Exercises 331
Problems 331
Selected Bibliography and Further Readings
221
SUPPLEMENT TO CHAPTER 5: Decision
Theory 222
Process Selection and Facility Layout 244
Introduction 246
Process Selection 246
Operations Tour:
Morton Salt 250
334
SUPPLEMENT TO CHAPTER 7: Learning
Curves 336
8
Technology 252
Readings:
Foxconn Shifts Its Focus to Automation
254
Zipline Drones Save Lives in Rwanda
258
Self-Driving Vehicles
Work Design and Measurement 300
Motion Study 315
Work Measurement 316
Operations Strategy 327
Case:
Outsourcing of Hospital Services 221
6
298
Introduction 301
Job Design 301
Quality of Work Life 305
Methods Analysis 310
Reading:
Taylor’s Techniques Help UPS 311
216
Selected Bibliography and Further Readings
281
Summary 285
Key Points 286
Key Terms 286
Solved Problems 286
Discussion and Review Questions 290
Taking Stock 291
Critical Thinking Exercises 291
Problems 291
Selected Bibliography and Further Readings
259
Process Strategy 260
Strategic Resource Organization: Facilities
Layout 260
Reading:
A Safe Hospital Room of the Future 269
Designing Product Layouts: Line Balancing
Reading:
BMW’s Strategy: Flexibility 280
272
Location Planning and Analysis 348
The Need for Location Decisions 350
The Nature of Location Decisions 350
Global Locations 352
Reading:
Coffee? 355
General Procedure for Making Location
Decisions 355
Identifying a Country, Region, Community, and
Site 356
Service and Retail Locations 363
Evaluating Location Alternatives 364
Summary 370
Key Points 370
Contents
Key Terms 371
Solved Problems 371
Discussion and Review Questions
Taking Stock 372
Critical Thinking Exercises 373
Problems 373
Case:
Hello, Walmart?
9
Process Capability 443
Readings:
RFID Chips Might Cut Drug Errors in
Hospitals 448
Operations Strategy 448
372
377
Selected Bibliography and Further Readings
377
Management of Quality 378
Introduction 379
The Evolution of Quality Management 380
The Foundations of Modern Quality Management:
The Gurus 381
Insights on Quality Management 383
Readings:
American Fast-Food Restaurants Are Having
Success in China 386
Hyundai: Exceeding Expectations
389
Quality and Performance Excellence Awards 391
Quality Certification 392
Quality and the Supply Chain 393
Total Quality Management 394
Problem Solving and Process Improvement 398
Quality Tools 401
Operations Strategy 409
Summary 409
Key Points 409
Key Terms 410
Solved Problem 410
Discussion and Review Questions
Taking Stock 412
Critical Thinking Exercises 412
Problems 412
Cases:
Chick-n-Gravy Dinner Line 414
Tip Top Markets
454
Cases:
Toys, Inc. 462
Tiger Tools 462
Selected Bibliography and Further Readings
416
10 Quality Control 418
Introduction 419
Inspection 420
Reading:
Falsified Inspection Reports Create Major Risks
and Job Losses 424
463
11 Aggregate Planning and Master
Scheduling 464
Introduction 466
Reading:
Duplicate Orders Can Lead to Excess Capacity 470
Basic Strategies for Meeting Uneven Demand
Techniques for Aggregate Planning 476
Aggregate Planning in Services 484
Disaggregating the Aggregate Plan 485
Master Scheduling 486
The Master Scheduling Process 487
473
496
Case:
Eight Glasses a Day (EGAD)
415
Statistical Process Control 425
Summary 449
Key Points 450
Key Terms 450
Solved Problems 450
Discussion and Review Questions
Taking Stock 455
Critical Thinking Exercises 455
Problems 456
Summary 491
Key Points 491
Key Terms 492
Solved Problems 493
Discussion and Review Questions
Taking Stock 496
Critical Thinking Exercises 496
Problems 496
411
Selected Bibliography and Further Readings
xxv
501
Selected Bibliography and Further Readings
501
12 Inventory Management 502
Introduction 503
Reading:
$$$ 504
The Nature and Importance of Inventories 504
Requirements for Effective Inventory
Management 507
Contents
xxvi
Readings:
Radio Frequency Identification (RFID) Tags 509
Catch Them Before They Steal! Reducing Inventory
Loss With an Assist From AI 510
Drones Can Help With Inventory Management in
Warehouses 513
Inventory Ordering Policies 513
How Much to Order: Economic Order Quantity
Models 514
Reorder Point Ordering 525
How Much to Order: Fixed-Order-Interval
Model 530
The Single-Period Model 533
Operations Strategy 538
Summary 538
Key Points 538
Key Terms 540
Solved Problems 540
Discussion and Review Questions
Taking Stock 545
Critical Thinking Exercises 545
Problems 546
Operations Strategy
589
Summary 589
Key Points 590
Key Terms 590
Solved Problems 590
Discussion and Review Questions
Taking Stock 599
Critical Thinking Exercises 600
Problems 600
599
Cases:
Promotional Novelties 605
DMD Enterprises 606
Operations Tour:
Stickley Furniture 606
Selected Bibliography and Further Readings
609
14 JIT and Lean Operations 610
Introduction 612
Reading:
Toyota Recalls 614
Supporting Goals 615
Building Blocks 616
Reading:
General Mills Studied NASCAR Pit Crew to Reduce
Changeover Time 619
545
Cases:
UPD Manufacturing 553
Grill Rite 554
Farmers Restaurant 554
Operations Tours:
Bruegger’s Bagel Bakery 556
PSC, INC.
11 Common ERP Mistakes and How to
Avoid Them 587
557
Selected Bibliography and Further Readings
559
13 MRP and ERP 560
Introduction 561
An Overview of MRP 562
MRP Inputs 563
MRP Processing 566
MRP Outputs 573
Other Considerations 574
MRP in Services 576
Benefits and Requirements of MRP 576
MRP II 577
Capacity Requirements Planning 579
ERP 581
Readings:
The ABCS of ERP 583
Lean Tools 632
Reading:
Gemba Walks 635
Transitioning to a Lean System
Lean Services 637
JIT II 638
Operations Strategy 638
Summary 639
Key Points 639
Key Terms 640
Solved Problems 640
Discussion and Review Questions
Taking Stock 642
Critical Thinking Exercises 642
Problems 642
635
641
Case:
Level Operations 643
Operations Tour:
Boeing 644
Selected Bibliography and Further Readings
645
SUPPLEMENT TO CHAPTER 14: Maintenance
646
Contents
15 Supply Chain Management 654
Scheduling Services 715
Operations Strategy 719
Introduction 656
Trends in Supply Chain Management 657
Readings:
Walmart Focuses on Its Supply Chain 660
Supply Chain Transparency
661
At 3M, a Long Road Became a Shorter Road
662
Global Supply Chains 663
ERP and Supply Chain Management 663
Ethics and the Supply Chain 664
Small Businesses 664
Management Responsibilities 665
Procurement 667
E-Business 670
Supplier Management 671
Inventory Management 674
Order Fulfillment 675
Logistics 676
Operations Tour:
Wegmans’ Shipping System 677
Readings:
UPS Sets the Pace for Deliveries and Safe
Driving 679
Springdale Farm 680
Active, Semi-Passive, and Passive RFID Tags 681
Creating an Effective Supply Chain 681
Readings:
Clicks or Bricks, or Both? 683
Easy Returns
Strategy
684
686
Summary 687
Key Points 687
Key Terms 687
Discussion and Review Questions
Taking Stock 688
Critical Thinking Exercises 688
Problems 688
Case:
Mastertag
687
689
Selected Bibliography and Further Readings
690
16 Scheduling 692
Scheduling Operations 694
Scheduling in Low-Volume Systems
xxvii
Summary 719
Key Points 719
Key Terms 720
Solved Problems 720
Discussion and Review Questions
Taking Stock 724
Critical Thinking Exercises 724
Problems 725
724
Case:
Hi-Ho, Yo-Yo, Inc. 731
Selected Bibliography and Further Readings
731
17 Project Management 732
Introduction 734
Project Life Cycle 734
Behavioral Aspects of Project Management 736
Reading:
Artificial Intelligence Will Help
Project Managers 740
Work Breakdown Structure 741
Planning and Scheduling with Gantt Charts 741
PERT and CPM 742
Deterministic Time Estimates 745
A Computing Algorithm 746
Probabilistic Time Estimates 753
Determining Path Probabilities 756
Simulation 758
Budget Control 759
Time–Cost Trade-Offs: Crashing 759
Advantages of Using PERT and Potential
Sources of Error 762
Critical Chain Project Management 763
Other Topics in Project Management 763
Project Management Software 764
Operations Strategy 764
Risk Management 765
Summary 766
Key Points 767
Key Terms 767
Solved Problems 767
Discussion and Review Questions
Taking Stock 774
Critical Thinking Exercises 774
Problems 774
774
Case:
Time, Please 781
697
Selected Bibliography and Further Readings
782
Contents
xxviii
18 Management of Waiting Lines 784
Why Is There Waiting? 786
Reading:
New Yorkers Do Not Like Waiting in Line
19 Linear Programming 824
787
Managerial Implications of Waiting Lines 787
Goal of Waiting-Line Management 788
Characteristics of Waiting Lines 789
Measures of Waiting-Line Performance 792
Queuing Models: Infinite-Source 793
Queuing Model: Finite-Source 807
Constraint Management 813
The Psychology of Waiting 813
Reading:
David H. Maister on the Psychology of Waiting 814
Operations Strategy 814
Reading:
Managing Waiting Lines at Disney World
Summary 815
Key Points 816
Key Terms 816
Solved Problems 816
Discussion and Review Questions
Taking Stock 818
Critical Thinking Exercises 818
Problems 818
Introduction 825
Linear Programming Models 826
Graphical Linear Programming 828
The Simplex Method 840
Computer Solutions 840
Sensitivity Analysis 843
Summary 846
Key Points 846
Key Terms 846
Solved Problems 846
Discussion and Review Questions
Problems 849
Cases:
Son, Ltd.
853
Custom Cabinets, Inc.
854
Selected Bibliography and Further Readings
815
856
APPENDIX A Answers to Selected Problems 858
APPENDIX B Tables 870
APPENDIX C Working with the Normal
Distribution
876
APPENDIX D Ten Things to Remember Beyond the Final
Exam 882
818
Company Index 883
Subject Index 884
Case:
Big Bank 822
Selected Bibliography and Further Readings
849
822
Operations Management
1
C H A P T E R
Introduction
to Operations
Management
LEARNING OBJECTIVES
After completing this chapter, you should be able to:
LO1.1
Define the terms operations management and supply chain.
LO1.2
Identify similarities and differences between production and service operations.
LO1.3
Explain the importance of learning about operations management.
LO1.4
Identify the three major functional areas of organizations and describe how they interrelate.
LO1.5
Summarize the two major aspects of process management.
LO1.6
Describe the operations function and the nature of the operations manager’s job.
LO1.7
Explain the key aspects of operations management decision making.
LO1.8
Briefly describe the historical evolution of operations management.
LO1.9
Describe current issues in business that impact operations management.
LO1.10
Explain the importance of ethical decision making.
LO1.11
Explain the need to manage the supply chain
C H A P T E R
1.1
O U T L I N E
Introduction 4
1.2 Production of Goods Versus
Providing Services 8
1.3 Why Learn About Operations
Management? 10
1.4 Career Opportunities and
Professional Societies 12
1.5
Process Management 13
Managing a Process to Meet
Demand 13
Process Variation 14
1.6
The Scope of Operations
Management 14
Managing the Supply Chain to
Achieve Schedule, Cost, and
Quality Goals 15
2
1.7 Operations Management and
Decision Making 18
Models 18
Quantitative Approaches 19
Performance Metrics 19
Analysis of Trade…
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