Must read and follow all instructions and use scholarly sources.  No plagiarism!!  

Required Resources

Text

Vonderembse, M. A., & White, G. P. (

2

0

1

3

). 

Operations management

 [Electronic version]. Retrieved from https://content.ashford.edu/

/ (Links to an external site.)

· Chapter 7: Facility Location and Process Selection

· Chapter 8: Capacity Decisions

Recommended Resources

Multimedia

July, E. (Producer) & Rodrigo, J. M. (Director). (

200

3). 

Business is blooming: The international floral industry (Links to an external site.)

 [Video file]. Retrieved from the Films On Demand database.

· Watch the following segments:

· Anticipating Flower Market Demand

· Ecuador: King in the Flower World

· Ecuador’s Flower Production

· Exporting Flowers from Ecuador

Websites

American Society for Quality. (n.d). 

Pareto chart (Links to an external site.)

. Retrieved from http://asq.org/learn-about-quality/cause-analysis-tools/overview/pareto.html

American Society for Quality. (n.d). 

Six sigma (Links to an external site.)

. Retrieved from http://asq.org/sixsigma/

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Discussion 1

Process Selection: Product Design and Capacity

How is process selection related to product design and capacity determination? Your initial post should be 200-2

5

0 words.

Discussion 2

Monique Food Processing Company and Capacity

Read Problem 6: The “Monique Food Processing Company” in Chapter 8 of your text.

Monique Food Processing Company produces light snacks that can be heated in a microwave. The following steps are included in the process:

200

200

Steps	Description	Capacity (Units/Hour)
1	Prepare food			200
2	Measure and place in plastic pouch	175
3	Prepare cardboard box
4	Insert pouch into box	300
5	Shrink-wrap box

a. What is the system capacity, and which is the bottleneck department?

b. How much slack (unused capacity) is available in other departments?

c. How much system capacity can be gained by adding capacity to the bottleneck?

d. What are the key factors that determine when to add capacity?

e. Why would an organization want to reduce its capacity?

Make and include calculations. Answer questions “a” through “e.” Your response should be 200-250 words.

Week 4 – Assignment

Beck Manufacturing and Plant Capacity

Read the “Beck Manufacturing” case study in Chapter 8 of your text. In a three- to four-page paper, address the following:

· Calculate the capacity of each machine center and the capacity of the system.

· Analyze where the focus of the company’s efforts should be if Beck wants to expand capacity. Determine how much extra capacity he can get without causing another operation to become the bottleneck.

· Suggest ways Beck can expand capacity without purchasing new equipment.

Your paper should be in paragraph form (avoid the use of bullet points) and supported with the concepts outlined in your text and additional scholarly sources.

Submit your three- to four-page paper (not including the title and reference pages). Your paper must be formatted according to APA style as outlined in the Ashford Writing Center and must cite at least three scholarly sources in addition to the textbook.

Carefully review the 

Grading Rubric (Links to an external site.)

 for the criteria that will be used to evaluate your assignment

7

©

iStockphoto/Thinkstock

Facility Location and Process Selection

Learning Objec�ves
A�er comple�ng this chapter, you should be able to:

Discuss loca�on as a strategic decision.
Discuss the quan�ta�ve and qualita�ve factors influencing loca�on decisions.
Integrate qualita�ve and quan�ta�ve factors to make effec�ve loca�on decisions.
Describe how loca�on influences other opera�ng decisions.
Describe the process selec�on decision and how it is influenced by the volume of product demanded.
Define the different process types: line flow, batch flow, flexible manufacturing system, manufacturing cell, job
shop, and project.
Construct a cost-volume-profit model of a firm, and understand how to use the model to manage the firm.
Calculate the break-even point for cases involving both single- and mul�ple-product breakeven.

Processing math: 0%

Fast-food restaurants, hotels, hospitals, and gas sta�ons are o�en located on heavily traveled
roadways in order to provide customer convenience and accessibility.

©age fotostock / SuperStock

7.1 Facility Location

The previous chapters in this book have provided an understanding of what opera�ons are, why they are important, how they can be used to create compe��ve advantage, how
they impact key business elements such as cost and quality, and how they relate to suppliers. This chapter provides some organiza�onal context for the study of opera�ons.

The purpose of an organiza�on is to manufacture a good or provide a service, and opera�ons play a key role. This begins with designing the produc�on system, which includes:

1. Designing a product, which was discussed in an earlier chapter
2. Determining where and how the product will be created (loca�on and process)
3. Se�ng the capacity of the organiza�on

There are other decisions involved in designing the system that produces these goods and services, such as how to lay out and organize the facility and design the individual jobs
that employees must perform. However, these topics are beyond the scope of this text.

Facility loca�on is the placement of a facility with regard to a company’s customers, suppliers, and other facili�es with which the company interacts. The loca�on decision usually
commits substan�al resources and cannot be easily changed. Many of the principles and techniques used in loca�ng a facility are the same whether an organiza�on is selling fried
chicken or groceries, provides fire protec�on or health services, stores electronic parts or food, or makes computer chips or paper. Managers making the decision should consider
the costs of opera�ng at a par�cular loca�on, including costs to acquire the land and build the facility, as well as costs for labor, taxes, and u�li�es. They should consider the
convenience of a par�cular loca�on for customers as well as the cost to transport materials to the facility and move finished product from the facility. Managers should also
consider access to banking, educa�onal, and other ac�vi�es that are important to the success of their organiza�on. Thus, many factors, both quan�ta�ve and qualita�ve, influence
the loca�on decision. Quan�ta�ve factors are easily measurable, while qualita�ve factors are more subjec�ve.

What o�en differs from one industry to another are the weights assigned to these various factors. The size of the weight assigned to a factor indicates its importance. For example,
a primary factor in loca�ng a fire sta�on is its response �me to the buildings within that fire district. Thus, response �me should be assigned a large weight. When loca�ng a
restaurant, easy customer accessibility may be more important than the cost to transport raw material (food and beverages) to the facility. An organiza�on producing solar cells may
feel that it is very important to locate in an area close to a university or research park that specializes in key technology. Organiza�ons that produce plywood, dimensional lumber,
or paper need a readily available supply of wood, so they usually locate near �mber resources. Managers of labor-intensive opera�ons may feel that low labor cost is the cri�cal
factor that determines the loca�on of their facility.

Location as a Strategic Decision

The loca�on decision usually involves commitment of a large capital investment that cannot be moved. As a result, loca�on should be viewed as a long-term, strategic decision
because it will have a major impact on the organiza�on’s ability to compete. The loca�on decision should not be based solely on marke�ng issues, produc�on factors, or
transporta�on costs. Successful managers integrate the relevant factors and weigh them appropriately in order to make the best long-term decision for the organiza�on.

This long-term commitment should fit with the organiza�on’s overall strategy. In
some cases, organiza�ons develop marke�ng and opera�ng strategies that have an
impact on the loca�on decision. A regional facility strategy requires that each
produc�on facility has a defined marke�ng area and each facility produces a
complete line of products for that area. This is o�en done when customer
convenience and access are important, or when outbound transporta�on costs are
very high. Fast-food restaurants, instant oil change opera�ons, hospitals, and branch
banks are examples of opera�ons located to provide maximum customer
convenience and access. Many customer-oriented service opera�ons are located in
this way. Bo�le making, corrugated box produc�on, and aluminum can making
opera�ons are examples of facili�es that are located by region to keep outbound
transporta�on costs low. These finished products have high shipping costs because
they occupy a lot of space—shipping a can to the beverage company means
shipping a lot of empty space. When these low-value finished products are shipped
long distances, transporta�on costs increase the cost of the product, making the
company less price compe��ve.

A product facility strategy means that one facility is responsible for producing one
product or product line and shipping that product throughout the country and the
world. This approach is appropriate when the produc�on process is complex and
hard to control, such as making ceramic heat shields for spacecra�. It can be used
when a firm does not want to duplicate expensive equipment, facili�es, and highly

trained personnel. This approach is also popular when there are advantages to specializa�on and economies of scale, and when transporta�on costs are not prohibi�ve. The
produc�on of igniters for jet aircra� engines, for example, would benefit from a product facility strategy. This item is small, so shipping costs are low. An igniter is high in value, so
shipping cost, as a percent of purchase price, is also small.

Manufacturing Location Factors

There are differences in the loca�on decision for manufacturers and service providers. Manufacturing firms consider a variety of factors.

Quan�ta�ve factors for manufacturers include:

Labor costsProcessing math: 0%

Material costs
Transporta�on
U�li�es, taxes, real estate costs, and construc�on costs
Government incen�ves

Qualita�ve factors include:

Labor climate
Quality of life
Proximity to customers and markets
Proximity to suppliers and resources

Service Location Factors

In service opera�ons, many of the factors iden�fied with manufacturing are s�ll relevant. In most service opera�ons, service providers would consider labor cost, taxes, real estate
costs, construc�on costs, and government incen�ves as important elements in a loca�on decision. On the other hand, material cost and transporta�on costs would be relevant for
only some service providers, such as restaurants and retail opera�ons that purchase, transport, and resell goods. U�lity costs are not a significant factor for most service opera�ons
because consump�on is generally low compared to manufacturing. The qualita�ve factors listed for manufacturers are likely to be relevant for service providers, with the excep�on
of proximity to suppliers and resources. This is because materials and component parts are not always shipped from suppliers.

If a business has customers that u�lize a service facility in person, being close to customers is very important. For example, retail opera�ons require this proximity to the customer,
but a call center can be located anywhere in the world. Customers o�en place a high value on their �me, therefore, convenience is essen�al. Transporta�on costs are important for
warehousing and distribu�on, but response �me—the �me elapsed between a request for service to the delivery of that service—may be even more important. If travel distance
and �me are short, total inventory in the system can be kept very low. In some cases, the trip from producers to the distribu�on center to the retail store can be one day or less.

Loca�on of compe�tors may also be an important factor for service opera�ons. In some services, such as newspaper publishing, having compe�tors in the immediate area o�en has
a significant nega�ve impact on sales. In others, service providers tend to cluster together. In many cases, they adver�se together. Nearly every medium-size town and large city has
an “auto mile” or “auto strip” where one of every car dealer is located. The idea of such a loca�on is to create a cri�cal mass, so customers can quickly and easily compare products
from different dealers. Fast-food restaurants will o�en locate in similar clusters. These clusters are caused to some extent by the need to deal with customer choice. For example, in
a large group of poten�al customers, some will want pizza, some will want burgers, and others will want chicken. Fast-food chains locate their restaurants near high-volume
ac�vi�es, such as large shopping malls, sport centers, and expressway exits in large urban areas.

The loca�on of emergency units, such as fire protec�on and ambulance service, is determined by minimizing response �me, providing minimum coverage, and opera�ng from a
mobile loca�on. Response is important when �me is a cri�cal factor. The objec�ve is to locate a facility so that the maximum response �me to any point served by the emergency
unit is minimized.

Minimum coverage implies that all customers have a minimum level of coverage. For example, no house in the city will be more than one mile from a fire sta�on or an ambulance
service. The number and placement of facili�es required to provide minimum coverage can be determined by grouping customers into appropriate popula�on centers and examining
candidate facility loca�ons to see if the minimum coverage is provided. This can be accomplished by lis�ng the popula�on centers in the columns of a table and lis�ng the poten�al
facility loca�ons in the rows of the same table. Then, each poten�al facility can be judged to determine if the minimum coverage is achieved. In many cases, more than one
candidate facility may be required to provide that coverage.

Government Incentives

Many states and local governments have been very aggressive in their efforts to a�ract new businesses. One incen�ve offered by state and local governments is a significant
reduc�on in property taxes. They have also offered low-interest loans, provided free training to workers, and subsidized wages for a specified period of �me. In addi�on, many states
and ci�es have established agencies that can help private industry slice through governmental red tape. In some cases, state and local governments have put together parcels of
land by using their powers of eminent domain. Simply stated, eminent domain means that an owner can be forced to sell property to the government at fair market value if it will
be used for the good of all. Once obtained, proper�es are sold to private industry for development. Governments can acquire property more quickly and less expensively than
private industry can. As soon as word gets out that private industry is interested in developing an area, the land prices are sure to increase significantly. With the power of eminent
domain, the government can avoid being delayed by owners of key parcels.

In some cases, businesses that have been in a state for years are grumbling about the preferred treatment given to newcomers, and some states are beginning to wonder if the jobs
created are worth the costs of the incen�ves. Despite this, bidding wars among states for the jobs these new developments bring are likely to con�nue. The pressure on elected
officials to create jobs in the short term seems to mask the long-term impact that this treatment may have on future revenues and expenses of the state.

Highlight: Changing Loca�ons for Automo�ve Assembly

For many years, automobile assembly plants were located in the Midwest, and new facili�es were built in this region in order to provide good, low-cost access to a large
percentage of the North American popula�on. As the popula�on has increased in the South and Southwest, many automobile companies—especially foreign producers—have
located new assembly facili�es in the South to take advantage of lower labor costs, lower construc�on costs, cheaper land, and government incen�ves. Alabama persuaded
Mercedes-Benz to build an assembly facility for making sport u�lity vehicles. Honda opened a facility in Lincoln, Alabama, that employs more than 2,000 people to make its
Odyssey minivan. Toyota has constructed an engine assembly facility in Huntsville, Alabama. Hyundai Motor Company of South Korea has built a final assembly facility in the
South.

These efforts have cost Alabama nearly $700 million in incen�ves. Cri�cs argue that the state has not received sufficient return on its investment. Also, these investments have
taken money away from schools and services, and made it difficult for the state to provide tax relief for its low-income residents. Proponents argue that these efforts are
“Alabama’s new day.” Other companies are inves�ga�ng the poten�al that Alabama has to offer.Processing math: 0%

Processing math: 0%

State and local governments offer incen�ves such as tax breaks, low-
interest loans, and help cu�ng through red tape to a�ract and retain
businesses and jobs.

©Photodisc/Thinkstock

7.2 Evaluating Locations

The factors that must be weighed when evalua�ng loca�ons are grouped into three subsec�ons: (1) managing the
quan�ta�ve factors, including the impact of loca�on on cost and the increasing importance of government
incen�ves; (2) describing the qualita�ve factors and illustra�ng how these can be analyzed as well as integrated
with the quan�ta�ve factors; and (3) discussing the effects of the loca�on decision on other opera�ng factors.

Managing Quantitative Factors

Quan�ta�ve factors include the costs associated with facility construc�on, produc�on, overhead, and
transporta�on to and from the facility. State and local governments offer incen�ves to a�ract and retain businesses
and jobs. Such incen�ves include tax abatement, low-interest loans, help in cu�ng through red tape, low business
taxes, and low rates for unemployment insurance and worker’s compensa�on. Finally, the loca�on can affect sales
volume and selling price. The announcement of a new facility may ini�ate price-cu�ng or other costly product
promo�on ac�vi�es by exis�ng compe�tors in the area.

Loca�on decision plays an important role in shaping the cost func�on. The total-cost equa�on is:

TC = (VC)X + FC

where

TC = total cost

VC = variable cost per unit

X = the number of units produced

FC = fixed costs

Variable costs are affected by prevailing wage rates, material costs, u�lity rates, and transporta�on costs for incoming materials and outgoing finished products. Fixed costs are
affected by construc�on and land costs and the cost of administra�on, all of which are likely to be lower in rural areas. There also may be tax incen�ves or other special
considera�ons for a par�cular site.

To prepare cost es�mates for a site, data are collected and analyzed. To illustrate, Table 7.1 contains data for a site in Indianapolis, Indiana, for a facility to build computer control
panels. These data can be used to prepare a pro forma opera�ng budget.

Table 7.1: Data for site in Indianapolis, Indiana

Produc�on Costs

Type Rate Projected Usage

Labor Welding
Electrical
General assembly

$10.00/hr.
$12.00/hr.
$9.00/hr.

0.5 hrs./unit
0.3 hrs./unit
1.1 hrs./unit

Material Sheet metal
Threaded fasteners
Electrical wire

$.40/lb.
$2.00/100
$.06/lineal �.

100 lbs./unit
20/unit
70 lineal �./unit

U�li�es

Natural gas

Electricity

$4.00/1,000 cu. �.
$.06/kilowa� hr.

500 cu. �./unit
200 kilowa� hrs./unit

Processing math: 0%

Transporta�on* In rail
In motor carrier
In motor carrier
Out motor carrier

$.03/lb. (sheet metal)
$.04/lb. (fasteners)
$.04/lb. (wire)
$20/unit (finished)

100 lbs./unit
5 lbs./unit
4 lbs./unit
1

Facility Overhead Ini�al Investment
Land acquisi�on costs
Building construc�on
Plan start-up costs
Ini�al employee training

$2,100,000
$175,000,000

Special Considera�ons Tax abatement
Low-interest loans
Supplementary training expenses

$25,000,000

*Rates are given from specific origin to a specific des�na�on, so distance has been accounted for.

Table 7.1 contains projected labor, material, and u�lity usage in addi�on to the rates. U�li�es may have both fixed and variable components. Some u�lity costs are variable and
directly linked to producing a product, such as the power required to run a drill press. In other cases, u�lity costs cannot be linked to a product. An example is the energy needed to
heat a building. The amount of heat required is not related to the number of units produced. Table 7.1 shows variable u�lity costs. The fixed component of u�li�es is included in
overhead expenses. Transporta�on costs are a func�on of the quan�ty of materials shipped, the distance traveled, and the type of carrier used.

Table 7.1 also lists as a lump sum an es�mate of facility overhead expenses, such as supervisors, material handling, and plant management staff. The value of the investments in the
facility and the value of any special considera�ons are also listed as lump sums. The special considera�ons figure is shown as a savings that should be deducted from the ini�al
investment.

Table 7.2 shows a pro forma opera�ng budget based on producing 45,000 units per year at the site described in Table 7.1. An opera�ng budget usually does not include capital costs
for facili�es. The costs of making products at this facility can now be es�mated. Considering only the variable costs, the unit variable cost is calculated as follows:

Unit variable cost
= $100.46/unit

The cost including a share of the annual facility overhead is:

Cost with overhead
= $147.13/unit

*Throughout this text, to enlarge the size of the math equa�ons, please right click on the equa�on and choose “se�ngs” then “scale all math” to increase the viewing percentage.

Table 7.2: Pro forma opera�ng budget for one year based on es�mated sales of 45,000 units

Labor
Welding
Electric
Assembly
Total Labor costs

($10.00/hr.)(0.5 hrs./unit)(45,000 units)
($12.00/hr.)(0.3 hrs./unit)(45,000 units)
($9.00/hr.)(1.1 hrs./unit)(45,000 units)

$ 225,000
162,000
445,500
$ 832,500

Material
Sheet metal
Fasteners
Wire
Total material costs

($.40/lb.)(100 lbs./unit)(45,000 units)
($2.00/100)(20/unit)(45,000 units)
($.06/lin. �.)(70 lin. �./unit)(45,000 units)

$ 1,800,000
18,000
189,000
$ 2,007,000

U�li�es
Natural gas
Electricity
Total u�lity costs

($4.00/1,000 cu. �.)(500 cu. �./unit)(45,000 units)
($.06/kwh)(200 kwh/unit)(45,000 units)

$ 90,000
540,000
$ 630,000

Transporta�on
Sheet metal
Fasteners
Wire
Finished product
Total transporta�on costs

($.03/lb.)(100 lb./unit)(45,000 units)
($.04/lb.)(5 lb./unit)(45,000 units)
($.04/lb.)(4 lb./unit)(45,000 units)
($20.00/unit)(45,000)

$ 135,000
9,000
7,200
900,000
$ 1,051,200

Variable costs
Facility overhead*
Grand total

$ 4,520,700
2,100,000
$ 6,620,700

*Some overhead costs can be variable, but to simplify the discussion in this case, we will assume all overhead costs are fixed.

Comparing Quantitative Factors

To make effec�ve loca�on decisions, management must organize the poten�al costs and revenues for each site in a way that allows them to be easily compared. Begin by examining
the cost data for the Indianapolis site (detailed in Tables 7.1 and 7.2), and for an alterna�ve site in Lexington, Kentucky. The new facility is scheduled to produce 45,000 units per
year. The costs for both sites are summarized here. (The incen�ves are to be subtracted from the ini�al investment.)

Indianapolis Lexington
Processing math: 0%

Variable Costs $100.46/unit $95.77/unit

Annual Overhead Cost $2,100,000/year $1,900,000/year

Ini�al Investment $175,000,000 $168,000,000

Incen�ves $25,000,000 $10,500,000

Several assump�ons are made including: (1) revenue is not affected by either choice; (2) sales volume per year, selling price, unit variable costs, and fixed costs do not change over
the period in ques�on; and (3) the �me value of money is ignored. The �me value of money is the no�on that one dollar received today is worth more than one dollar received at
some future point. One dollar received today can be invested and earn a posi�ve return, thereby making its value greater than one dollar.

Problem

Compare the costs of the Indianapolis and Lexington sites over a five-year period, using the total-cost equa�on. (The subscript I stands for Indianapolis and the subscript L for
Lexington.)

TC = (VC)X + FC

TCI = ($100.46/unit)(45,000 units/year)(5 years) + ($2,100,000/year)(5 years) + $175,000,000 – $25,000,000

= $22,603,500 + $10,500,000 + $150,000,000

= $183,103,500

TCL = ($95.77/unit)(45,000 units/year)(5 years) + ($1,900,000/year)(5 years) + $168,000,000 – $10,500,000

= $21,548,250 + $9,500,000 + $157,500,000

= $188,548,250

Over a 5-year period, Indianapolis has a lower total cost.

At what point in �me will the costs of these two sites be equal? In this case, X will represent the number of years un�l costs are equal. This informa�on may be very useful for
managers when choosing between the alterna�ve sites.

TCI = TCL

(100.46)(45,000)X + 2,100,000X + 175,000,000 – 25,000,000 = (95.77)(45,000)X + 1,900,000X + 168,000,000 – 10,500,000

$4,520,700X + $2,100,000X + $150,000,000 = $4,309,650X + $1,900,000X + $157,500,000

$6,620,700X – $6,209,650X = $157,500,000 – $150,000,000

$411,050X = $7,500,000

X = 18.25 years

Check the answer by subs�tu�ng the �me X into the cost equa�ons for Indianapolis and Lexington and seeing if the costs are equal.

If the amount sold per year is allowed to vary, the point of equal costs could be viewed in a different way. In the model, the number of years could be a constant, and the
number of units sold per year could become a variable. If the �me period is set at five years, how many units must be sold each year if costs are equal? Here, the variable

X

represents the number of units sold each year.

TCI = TCL

(100.46)(X)5 + (2,100,000)5 + 175,000,000 – 25,000,000 = (95.77)(X)5 + (1,900,000)5 + 168,000,000 – 10,500,000

X = 277,186 units/year

Including Qualitative Factors

Qualita�ve factors do not usually have measurable, direct effects, but they do need to be carefully considered and integrated into the decision by management. The chapter 7
appendix contains a sample list of some of the qualita�ve factors that could be considered such as labor climate, cultural ac�vi�es, and weather.

To integrate qualita�ve factors into the loca�on decision, managers should:

1. Decide which factors are relevantProcessing math: 0%

2. Weigh each of the factors—some may be more important than others
3. Evaluate each site so that ra�onal comparisons can be made

Unless a manager makes a judgment about the importance of each factor, all the factors are assumed to have equal weight. These weights are usually selected prior to determining
the rankings or raw scores so that the scores do not bias the weights. The weights are mul�plied by the scores to determine the weighted scores. Then, the weighted scores are
added together to determine total scores.

Problem

A commi�ee has determined that the following factors are relevant to the decision. Indianapolis and Lexington are ranked on a scale of 1 to 10, with 10 being most desirable.
The rankings are subjec�ve es�mates.

Factor Weight Indianapolis Raw Score Lexington Raw Score

Recrea�onal ac�vi�es 20 8 7

University research facili�es 40 8 8

Union ac�vity 40 4 7

Banking services 80 7 6

Available labor pool 60 7 5

The rankings can eventually be added; 10 is considered “good” in all cases, but a ten may not indicate more of that factor. For example, a 10 in university research ac�vi�es is
desirable and indicates high levels of research; a 10 in union ac�vity is also desirable, but may indicate low levels of union ac�vity.

Mul�ply the weight by the raw score for both Indianapolis and Lexington.

          Indianapolis           Lexington

Weight Raw Score Weighted Score Raw Score Weighted Score

Recrea�onal ac�vi�es 20 8 160 7 140

University research facili�es 40 8 320 8 320

Union ac�vi�es 40 4 160 7 280

Banking services 80 7 560 6 480

Available labor pool 60 7 420 5 300

Total 1,620 1,520

As long as the same weights are applied to each loca�on, the weighted scores are comparable. The absolute value of each score does not have meaning, but comparing total
scores is useful.

If Indianapolis is superior in profit and investment, then the choice between the two loca�ons is easy because Indianapolis also has a slight qualita�ve edge. If Indianapolis is
not superior in profit and investment, then management should judge the impact of these qualita�ve factors on the long-term success of the organiza�on. Even though a
mathema�cal model can be used to analyze the data, the results must s�ll be interpreted and a decision made.

On-Site Versus Off-Site Expansion

Loca�on can have a significant impact on an organiza�on’s ability to compete. It can influence costs, selling price, demand, educa�onal opportuni�es for employees and their
families, and access to financial services. How can the loca�on decision affect other factors in produc�on?

Assume that demand for an organiza�on’s product exceeds present capacity. An organiza�on can consider two op�ons to increase capacity: build addi�ons to the exis�ng plant on-
site, or design and build a new plant in another loca�on. On-site expansion is more popular because it usually involves less capital investment. Many services, such as shipping,
receiving, and administra�on, may not need to be expanded. Only the cri�cal opera�ons— that is, the bo�lenecks—require capacity increases.

However, on-site expansion can create many problems, especially if it is a repeated prac�ce. As more produc�on space is added, material handling and storage become more
difficult because inventory space is o�en converted to produc�on. As new product varia�ons are added, the once simple product flow becomes complicated or stymied because
plant addi�ons o�en occur over many years and no long-term planning for future addi�ons is made. When on-site expansion is used to increase capacity, intra-plant transporta�on
and communica�on can become strained.

Staying at the same site o�en postpones the introduc�on of new product and process technologies. Old equipment and old produc�on methods are used longer than they should
be. Future product innova�on, produc�vity increases, quality improvements, and cost reduc�ons can be nega�vely affected. On-site expansion can mean a growing number of
workers, products, and processes that must be managed. Such layering of expanded responsibili�es creates complexi�es for managers at all levels.

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Leverage means making the workforce more produc�ve through the use of be�er tools and
equipment. One worker with a few simple tools may be able to assemble an automobile, but not at a
compe��ve cost.

©Monty Rakusen/Cultura/Ge�y Images

7.3 Foundations of Process Selection

Process selec�on is determining the most appropriate method of comple�ng a task. It is a series of decisions that include technical or engineering issues and volume or scale issues.
The technical or engineering issues include the basic methods used to produce a service or good. For example, deciding to remove a gall bladder using laparoscopic surgery versus
tradi�onal methods is a technical decision made by physicians. The decision depends on the pa�ent’s condi�on and is o�en made at the �me of surgery. On the other hand,
determining the number of surgery rooms and the number of surgeries to perform each day at the regional medical center is a volume or scale decision that is related to demand.
In general, the technical aspects of process selec�on are beyond the scope of this course, so the focus will remain on volume or scale issues.

There is a strong rela�onship among process selec�on and three cri�cal elements in
business: volume, cost, and profit. The volume or scale decision involves applying the
appropriate mix of technology to leverage the organiza�on’s workforce. Leverage means
making a workforce more produc�ve through the use of be�er tools. For example, one
person working alone with a few simple tools may be able to assemble an automobile,
but he or she cannot build it at a cost that competes with organiza�ons providing their
employees with sophis�cated tools and technology. The person working alone, or even
with many others like him or her, cannot build enough cars to sa�sfy demand without
significant automa�on and an organiza�on to leverage their �me and talent. More
sophis�cated tools allow a workforce to produce more with the same commitment of
�me and effort. This produc�vity improvement lowers the unit cost of the product and
raises the capacity of the workforce. Similarly, a surgeon performing a surgery without
the proper equipment and an effec�ve suppor�ng staff will not only be less produc�ve
but could also be dangerous to the pa�ent.

This presents an interes�ng trade-off between efficiency and costs in the process
selec�on decision. As more sophis�cated tools are applied to the produc�on process,
produc�vity and capacity increase and labor cost per unit declines. As tools become
more sophis�cated, the cost of acquiring them o�en increases, which translates into
increased fixed costs.

Process Selection Relates to Product Design and Capacity

Product design, capacity, and process selec�on are decisions that should be considered
simultaneously. The way the product is designed affects how many people will buy it,
and that affects the producer’s capacity planning decision. This, in turn, affects the process and the costs to produce the product, which affects how many people can afford to buy
it. This logic can be represented as a circle with customers at the center, as illustrated in Figure 7.1.

Figure 7.1: Product design, process selec�on, and capacity
decisions are closely related

Rela�ng Process Selec�on to Product Design

Decisions made when designing a product have an impact on the process for making it. For example, if a bed is made of brass, there is no need for woodworking equipment in the
manufacturing process. Process selec�on and process technology, in turn, influence the product design. Electronic funds transfers, music downloads, and streaming video are
examples of products that are now feasible because of improvements in informa�on and communica�on technology.

Rela�ng the design of the product to process selec�on goes beyond the examples listed in the preceding paragraph. The teamwork concept is changing how organiza�ons approach
product design and process selec�on. In service organiza�ons, such as fire departments, teams of managers from various disciplines design the services, which may include fire

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preven�on programs for homes and businesses, fire safety for school-age children, and firefigh�ng. While developing a product design, the team examines various process selec�on
decisions, including the types of equipment and facili�es needed, the techniques used in figh�ng fires, the methods used to develop educa�on programs, and the type and level of
training needed by employees who deliver these services.

Manufacturing firms combine design engineers with process engineers (some�mes called manufacturing engineers) to create a design team. This team, like the team at the fire
department, is responsible for providing what is best for the customer. Because the design engineers and the process engineers work together, the lead �me required to bring a new
product from an idea to a reality is reduced. This effort, called concurrent engineering, enables the organiza�on to par�cipate in �me-based compe��on. By doing what is best for
the customer, the organiza�on hopes to be rewarded with increased demand for its products and high profit margins. These teams also improve communica�on, which decreases
the number of engineering change orders, avoids unnecessary delays, and gets the product to market more quickly, preven�ng mistakes that could increase costs.

Process Selec�on and Capacity

Process selec�on is also related to the volume demanded in the marketplace. If the market for the product is es�mated at only 1,000 units per year, it may be difficult to jus�fy
expensive, specialized equipment that produces 100 units per hour. Such equipment would be required to operate only 10 hours each year. It is unlikely that the cost of this
specialized equipment could be supported by the 1,000 units demanded unless a very high price is charged for each unit.

Problem

Quick-as-a-Blink Prin�ng Center is growing rapidly, and many of its customers are demanding that their documents be professionally bound. Management has made a decision
to purchase a binding machine. The op�ons are to purchase a manual binding machine that requires con�nuous operator a�en�on or an automa�c machine that requires only
periodic operator a�en�on. The following data are available for analysis. Note that the costs of materials can be ignored because we are assuming that the cost of the printed
documents and the binding material are the same regardless of the machine used.

Machine Annual Fixed Costs Variable Labor Costs Produc�on Rate

Manual $1,000 $18/hour 10 units/hour

Automa�c $9,000 $2/hour 100 units/hour

The total-cost equa�on is as follows:

TC =FC + (VC)(Xp)

where
TC = total cost
FC = fixed costs
VC = variable cost per unit

Xp = number of units produced

Comparing Costs: What is the cost to produce 1,000 units per year on each machine? From the following calcula�ons, it is clear that the manual machine has lower costs.
Dividing the total cost by the volume produced gives a unit cost that includes the variable cost and a share of the fixed costs.

Manual:

TC =
= $2,800

Unit Cost =
= $2.80 per unit at a volume of 1,000

Automa�c:

TC =
= $9,020

Unit Cost =
= $9.02 per unit at a volume of 1,000

What happens if 10,000 books need to be bound? The marginal labor cost of binding each addi�onal book on the automa�c machine is only $.02 because the labor cost is
$2.00 per hour and the output is 100 units per hour. On the manual machine, the marginal cost of binding a book is $1.80.

Manual:

TC =
= $19,000

Unit Cost =
= $1.90 per unit at a volume of 10,000

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Automa�c:

TC =
= $9,200

Unit Cost =
= $0.92 per unit at a volume of 10,000

The unit cost for binding 10,000 books with the automa�c opera�on is significantly lower. As demand increases, the automa�c process becomes more and more appealing.

The Indifference Point: At what produc�on volume are the costs of the manual and automa�c machines equal? The variable X represents the volume produced. To check the
accuracy of the following calcula�ons, subs�tute the computed value of X into the total-cost equa�on for each machine to determine if the two total costs are equal. Except for
differences caused by rounding, they should be:

Total cost manual = Total cost automa�c

(1,000) + (1.80)(X) = (9,000) + (0.02)(X)

Solve for X:

(1.80 – 0.02)(X) = 9,000 – 1,000

X

X = 4,494 units

The Power of Volume to Reduce Costs: This problem illustrates how unit costs can be decreased by purchasing high-speed equipment and producing large numbers of parts.
The following table lists the unit costs for various volumes. Verify the unit cost for binding 100,000 books.

Volume Manual Automa�c

1,000 $2.80 $9.02

10,000 1.90 0.92

100,000 1.81 0.11

This example makes many simplifying assump�ons, such as unlimited capacity, no increase in maintenance costs, and no increase in the failure rate of the machine as volume
increases. These and other relevant factors could be es�mated and considered in the analysis. The impact of volume on unit cost is very clear based on this example.

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The economies of scale principle states that there is a most efficient
size for a facility and a most efficient size for the firm.

©Stockbyte/Thinkstock

Shipping Goods by Container Ships: Economy of
Scale; Addicted to Cheap Shopping? Why the Real

Cost of Goods Keeps Going Down

7.4 Understanding Effects of Scale

Business leaders have long recognized the advantages that can be gained by having high-volume opera�ons. The
tremendous increase in prosperity in the United States and other developed countries was driven by making
large quan��es of the same or similar products on the same equipment, that is, the same fixed-cost base. This
approach, o�en called mass produc�on, is based on the concept of economies of scale. Recall from Chapter 3
that the economies of scale principle states that there is a most efficient size for a facility, and a most efficient
size for a firm. In prac�ce, the principle has been used to jus�fy both building larger facili�es for the produc�on
of goods and services and purchasing more automated equipment to speed produc�on and lower costs.

An organiza�on can use both or either of these approaches to leverage the �me and talents of the people who
create the large volume of services and goods that customers demand. If organiza�ons and society are to
progress, investments in equipment and facili�es (fixed costs) must be made to increase the produc�vity of labor
and management.

The cri�cal challenge when achieving
economies of scale is pu�ng a large
volume of product across the same
equipment or fixed-cost base. In the past, it
was necessary that different products
produced on a machine where very similar
because equipment was not flexible enough
to cope with design differences. With
technological advances, it is possible to
achieve economies of scale by making

different products on the same equipment, and this can be done without the extra costs that are incurred
when equipment is stopped and changed over to make the new product. Economies of scope is the term that
describes this situa�on. Economies of scope are economies of scale across products. For example, Allen-Bradley
has a facility that can produce a wide variety (100 different designs) of computer motherboards in produc�on
lot sizes as small as one unit. The facility can produce them at a rate and cost that rivals mass produc�on.

Cost-Volume-Profit Modeling

To understand scale, it is helpful to construct a simple model. A model is an abstrac�on of the key variables and
rela�onships in a real problem, and is used to simplify the problem and increase understanding. The cost-
volume-profit (C-V-P) model uses es�mates of costs, revenues, volume sold, and volume produced in order to
es�mate profit.

C-V-P Model Formula�on

The C-V-P model is formulated by determining total revenue and costs, as shown in the following equa�ons:

TR = (SP)(Xs)

where

TR = total revenue

SP = selling price per unit

Xs = number of units sold

TC = FC + (VC)(Xp)

where
TC = total cost

FC = fixed cost

VC = variable cost per unit
Xp = number of units produced

Shipping Goods by
Container Ships:
Economy of Scale
From Title:

Addicted to Cheap Shopping? Why the Real Cost …
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wID=100753&xtid=39028)

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The profit (P) equa�on is total revenue minus total cost: P = TR – TC

By subs�tu�ng the TR and TC equa�ons into the equa�on for profit, the following mathema�cal model can be used to calculate profits, given sales and produc�on volumes. This is
the cost-volume-profit model.

P = SP(Xs) – [FC + VC(Xp)]

This model can also be manipulated to determine the volume required to earn targeted value for profit. In order to do this, assume that the number of units sold is equal to the
number of units produced.

If X = Xs = Xp, then

P = SP(X) – [FC + VC(X)]

P = SP(X) – FC – VC(X)

P + FC = (S – VC) (X)

Solve for X as follows:

If C is defined as contribu�on per unit, then C = (SP – VC). Thus, the equa�on becomes

The profit point is the number of units (X) that must be produced and sold at the contribu�on per unit (C) in order to cover the fixed costs (FC) and profit (P). Figure 7.2 represents
this model graphically and illustrates the profit point. If the profit is set to zero, equa�on 7.1 is recognizable as the break-even formula. The break-even point (BEP) is the volume
that must be produced and sold so that profit is zero.

Figure 7.2: Cost-volume-profit model

Problem

The mechanics of applying the C-V-P model are rela�vely simple. To calculate the profit point, you must know the selling price, variable costs, and fixed costs. Management can
determine the projected level of profit to be used in the model. In this example, the fixed cost and profit are for a one-month period.

SP = $8.00/unit

VC = $4.50/unit

C = $3.50/unit

FC = $25,000/month

P = $8,000/month

In this case, the number of units that must be produced and sold to make $8,000 profit in one month is 9,429 units; that is the profit point.

X

 = 9,429 units/month

Managers can use this number in many ways. Here are two examples. First, if the organiza�on has a capacity of only 5,600 units per month, then achieving an $8,000 profit is
not possible. Second, if the sales forecast is for 9,000 units, then that profit level will not be achieved because not enough units will be sold. Changes can be made to the

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model for the purpose of sensi�vity analysis and to answer what-if ques�ons. For example, what if the variable costs increased from $4.50 to $5.00 per unit? Under these
circumstances, the profit point becomes 11,000 units per month.

C-V-P Assump�ons

The C-V-P model, like any model, makes several assump�ons. The assump�on that sales volume equals produc�on volume has already been men�oned. The model also assumes
that total cost and total revenue are linear func�ons of volume. The model is based on historical data for costs and revenue. Any changes in these rela�onships caused by changes
in technology, demand, or strategy may invalidate the use of this or any other model. Users of models should understand these assump�ons, or they may apply the model
ineffec�vely and thus obtain misleading results.

The Mul�ple-Product Case of the C-V-P Mode

The discussion of the C-V-P model has considered only single-product firms. Many organiza�ons produce more than one product, using the same set of fixed costs. How can this
firm be modeled? In this case, another set of variables, product mix, is added to the revenue and cost rela�onships. To solve the problem, a weighted contribu�on based on the mix
of each product is calculated. Consider the following problem.

Problem

A company repairs small appliances. The table that follows provides the average selling price, variable cost, and contribu�on for each service. The product mix and profit target
are also listed. The fixed costs are shared by all three products.

Coffeepot Mixer Blender

Product mix 45% 20% 35%

Selling price/unit $12 $16 $9

Variable cost/unit $6 $7 $4

Contribu�on/unit $6 $9 $5

Profit target = $20,000/yr.

Fixed costs = $30,000/yr.

The mix is the number of each product repaired divided by the total number repaired. The weighted contribu�on is calculated as:

where

WC = weighted contribu�on per unit

Mi = product mix as a percentage of total sales for product i, where i = 1,. . ., n for n different products or product lines

SPi = selling price for product i

VCi = variable cost for product i

Thus, the weighted contribu�on for the product mix shown above is:

WC = 0.45($12/unit – $6/unit) + 0.2($16/unit – $7/unit) + 0.35($9/unit – $4/unit)

= $6.25/unit

In the mul�ple-product case, the weighted contribu�on per unit subs�tutes for the contribu�on per unit in equa�on 7.1.

X =
=
=

8,000 units

Interpre�ng the Results: The variable X is measured as a composite unit—a unit consis�ng of 45% coffeepot, 20% mixer, and 35% blender.

One composite unit with a weighted contribu�on = $6.25

45% Coffeepot

20% Mixer

35% Blender

Product Mix No. Required

Coffeepot 0.45 3,600 units
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Mixer 0.20 1,600

Blender 0.35 2,800

8,000 units

The number of units, 8,000, represents the total number of coffeepots, mixers, and blenders that must be repaired to make a $20,000 profit. The number of coffeepots
required is (0.45)(8,000 units), or 3,600 units.

What Happens to the Profit Point if the Mix Changes?: In this model, the mix affects the profit point. If the es�mated mix is different from the actual mix, then the profit point
will change. Assume the mix changes to 50% coffeepots, 10% mixers, and 40% blenders, and the total number of units repaired remains 8,000. How is profit affected?

Coffeepot Mixer Blender

Product Mix 50% 10% 40%

Selling price/unit $12 $16 $9
Variable cost/unit $6 $7 $4
Contribu�on/unit $6 $9 $5

Profit target (P) = unknown.

Fixed costs = $30,000/yr.

Equa�on 7.2 can be restated and used to calculate profit.

X

WC(X) = P + FC

P = WC(X) – FC

The fixed costs are $30,000, and the volume is given as 8,000 units. First, the weighted contribu�on is calculated based on the new mix.

WC =
= 0.5($12/unit – $6/unit) + 0.1($16/unit – $7/unit) + 0.4($9/unit – $4/unit)

  = $5.90/unit

Now profit can be calculated.

P = $5.90(8,000 units) – $30,000 = $17,200

The profit is only $17,200 dollars because demand shi�ed away from mixers, which have a higher contribu�on per unit, to the lower-contribu�on coffeepots and blenders.
Profit is not only a func�on of the volume produced and sold, but also a func�on of the product mix.

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An assembly line allows a company to make a fast-food pizza quickly and with low labor costs.

Newscast/ASSOCIATED PRESS/AP Images

7.5 Process Selection and Economies of Scale and Scope

From the perspec�ve of economies of scale or economies of scope, process selec�on focuses on the volume of product demanded in the market. Organiza�ons can influence that
volume by increasing adver�sing, providing be�er service, and producing higher quality products. Regardless of how that volume is generated, an organiza�on needs to respond to
higher demand with an appropriate process.

When does an organiza�on have sufficient volume to jus�fy specialized, high-speed equipment? Is a demand of 50,000 units per year sufficient? It is not possible to give specific
answers to these ques�ons because the answers depend on what the organiza�on produces. For example, if it produces space shu�les, then an annual demand of 50,000 would
certainly be large enough to support specialized facili�es, and even 5,000 would be considered a large volume. If, however, the organiza�on is processing checks for a bank, 50,000 a
year is a very small number, and even 1 million per year is not large.

In process selec�on, Hayes and Wheelwright (1979, p.133) have suggested that product and process can be viewed through two sides of a matrix. Figure 7.3 displays a series of
process alterna�ves that can be matched with iden�fiable product characteris�cs so that efficient opera�ons can be achieved. High-volume opera�ons are usually referred to as line
flow processes. One type of line flow is the con�nuous flow process. A con�nuous flow does not usually iden�fy individual units; rather, the product is mixed and flows together in
a con�nuous stream. Oil refining is a good example of a con�nuous flow process. Processing checks in a bank is another example. The term assembly line is used to describe the
high-volume assembly of discrete products. A washing machine is a good example of an assembly-line product and making a fast-food pizza on a busy night is another. Con�nuous
flow and assembly lines are usually dedicated facili�es that produce large volumes with li�le, if any, difference in the products. Because the items produced within such a facility are
the same or very similar, the process involves economies of scale. To increase volume, cut costs, and achieve economies of scale, organiza�ons tradi�onally move up the shaded
diagonal in Figure 7.3 (see next page).

Batch is a term used to describe a produc�on process that does not have sufficient
volume from a single product to fully use a facility. In this case, the facility produces
several products to build sufficient volume. When this resource sharing exists, a
transi�on �me, or changeover �me, is usually required to change the facility from being
able to make one product to being able to make the next. For example, Merck, which
produces medica�ons, uses batch produc�on. Merck has equipment that is designed to
mix ingredients and form pills or capsules. O�en this equipment can produce in a few
weeks all the capsules of a par�cular medica�on needed for an en�re year. Because of
shelf life considera�ons and inventory costs, making even a one-year supply in a single
batch creates too much inventory. So, companies like Merck produce different medicines
in smaller batches using the same equipment. In between batches, the equipment must
be thoroughly cleaned so the next batch is not contaminated. These changes take �me
and cost money, but are necessary to maintain enough volume to support the large
investment in equipment.

As product volume declines, batching opera�ons may no longer be possible. Here, only a
few units of a product are required, and there may be no assurance that the order will
be repeated. The differences between products can be significant. In this situa�on,
usually called job shop produc�on, the facility is general and flexible enough to meet a
variety of needs. To achieve this flexibility, job shops generally have a much higher unit
cost than line flow or batch processes for the same product. Fancy restaurants and
hospital emergency rooms are examples of job shops. Both types of organiza�ons offer great product variety and cater to individual customer demands.

At the bo�om of the volume scale in Figure 7.3 are projects, which are usually one-of-a-kind opera�ons. Each job is different from the rest. Most large construc�on jobs are
projects, and many service opera�ons can be categorized as projects. Installing new computer hardware, adding new computer so�ware, and implemen�ng a new management
planning and control system could all qualify as projects. The rela�onship between product and process, illustrated in Figure 7.3, indicates that there is a one-to-one rela�onship
between product volume and the type of process. For example, Figure 7.3 indicates that one-of-a-kind products cannot be produced on an assembly line or in a con�nuous flow
shop. Figure 7.3, therefore, implies that an organiza�on’s op�ons are limited to product and process matches on the diagonal. The diagram implies that if an organiza�on wants to
achieve the low cost obtained in con�nuous flow or assembly-line opera�ons, it must significantly limit product variety. An organiza�on that wants to achieve the product variety
obtained in a job shop or projects must incur high unit costs.

Figure 7.3: Matching process alterna�ves with product characteris�cs

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However, with the advances in informa�on and manufacturing technologies, organiza�ons have new process alterna�ves that are flexible, allowing changes from one product to
another to be made quickly and with few costs. With these technologies, the products produced within a facility can be different, yet low in costs. This is economies of scope, and it
implies moving off the shaded diagonal in Figure 7.3 toward the lower le� corner of the diagram. This segment of the diagram implies both low cost and high variety, which is called
mass customiza�on and is discussed in a later sec�on.

The following sec�ons describe the tradi�onal process alterna�ves: con�nuous flow, assembly line, batch, job shop, and project, as well as manufacturing cells and flexible
manufacturing systems.

Line Flow Processes

Con�nuous flow opera�ons and assembly lines have some differences; yet both are high-volume, mass-produc�on opera�ons characterized by a standardized product with
interchangeable parts. Because of this, the process is the same for each unit, and the product has a dominant product flow through the facility. With li�le or no product varia�on,
there is no reason to have more than one path through the facility. Furthermore, the equipment that processes the products should be arranged “around” the product so that
material-handling and transporta�on costs are not excessive. This approach is called a product layout.

In terms of the cost structure, a con�nuous flow process or an assembly line has rela�vely high fixed costs and rela�vely low variable costs. The high fixed costs are, in part, a result
of the substan�al investment in specialized equipment.

There are some differences between a con�nuous flow process and an assembly line. In a con�nuous flow process, the product is o�en a commodity in which one unit is not
dis�nguishable from another. In this case, the producer makes no a�empt to track each unit separately. For example, in refining gasoline from crude oil, one gallon of unleaded
regular gasoline is like another. Banks process checks one a�er another without changing methods. The produc�on of fiberglass insula�on is high-volume and fast-paced. It is not
feasible to track and iden�fy each piece produced. The emphasis is on measuring inputs and comparing them to outputs.

The tradi�onal assembly-line process allows some varia�ons among units. Op�ons are usually selected from a list of possibili�es, and the minor adjustments needed to cope with
this varia�on can be made by workers on the produc�on line. Adding green peppers to the standard pizza is easy to do. Adding custom floor mats to a car or a temperature probe
to a microwave oven is also easy to do. As technology improves, assembly lines are becoming more flexible. The con�nuous flow and assembly-line characteris�cs are summarized in
Table 7.3, along with the other process types.

Table 7.3: Characteris�cs of the process alterna�ves

Characteris�cs

Process Volume Product variety Product flow Facility layout Fixed costs Variable costs Equipment

Con�nuous flow High Standard Dominant Product High Low Special purpose

Assembly line High Standard with minor modifica�on Dominant Product High Low Special purpose

Batch High Some varia�on Dominant Product High Low Some flexibility

Flexible manufacturing system High Moderate variety Dominant Product High Low Flexible
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A woodcarving business that makes carvings to order is one example of a job shop because it handles
a large number of different products produced in small volumes, rather than producing large
quan��es of the same product.

iStockphoto/Thinkstock

Manufacturing cell High Moderate variety Dominant Product Moderate Low to moderate Flexible

Job shop Low Major differences Random Process Low High Flexible

Project One One-of-a-kind Not applicable Fixed posi�on Low to moderate High Flexible

Batch Flow

When quan��es are not sufficient to support dedicated produc�on facili�es, several groups or batches are produced using the same facility. These products are usually similar in
design and have similar processing requirements. For example, glass containers come in a variety of sizes but are designed and built similarly. A key to understanding whether or not
differences among products are meaningful can be found when the equipment is shut down to change from one product to another. If the �me for these changes is not significant
and the sequence of opera�ons is similar, then it is like a line flow process. However, if the changeover �me is significant, then these products are usually built in batches.

Because of the similar processing requirements in batch opera�ons, one or a few product flows dominate. For example, appliance manufacturers may produce several different
models of refrigerators on the same assembly line. In cases where changeover �me is significant, manufacturers may produce a batch—for example, one week’s produc�on of a
par�cular model—and then switch to another model. Although the models show some differences from batch to batch, these differences are not significant enough to change the
product-oriented layout of the facility. If a producer is able to design the product and the process so that different models can be produced one a�er the other with zero or near
zero changeover �me, then the process is similar to an assembly line that is producing a standard product. The disadvantages of batch produc�on are that (1) changeover �me is
nonproduc�ve, and (2) extra inventory must be maintained to sa�sfy demand for the products that are not being produced.

Job Shops

With limited product volume, batching opera�ons may not be possible. Here, only a
few units of a product are required, and there may be no assurance that the order
will be repeated. The differences between products can be significant. In this
situa�on, usually called job shop produc�on, the facility is general and flexible
enough to meet a variety of needs. To achieve this flexibility, job shops generally
have a much higher unit cost than line flow or batch processes for the same
product. Fancy restaurants and hospital emergency rooms are examples of job
shops. Both types of organiza�ons offer great product variety, and cater to
individual customer demands.

A job shop does not produce large quan��es of the same or even similar products,
but is dominated by a large number of different products produced in small
volumes. Because the products are different, they do not follow the same path
through the facility. In fact, the movement of products between work centers is
best characterized as random. As a result, it is not possible to organize machines by
product flow as in the line flow processes or in batch opera�ons. It is necessary to
group machines by process or type of opera�on because a job is as likely to require
work at one work center as at any of the other centers. When similar equipment is
grouped together it is called a process layout. The job shop is one of the process
alterna�ves shown in Table 7.3.

Because the products are very different, specialized equipment cannot be jus�fied.
Job shops use flexible equipment to meet the needs of the diverse product group.

A job shop produces different products on general-purpose machines using skilled labor. The cost structure has low fixed costs and high unit-variable costs.

Projects

In a project, cost structure is not the same as in other processes because there is only a single unit. In one sense, the cost for the project is all variable. Fixed costs in the form of
overhead begin to make sense when a firm is engaged in more than one project and can spread certain major equipment costs and overhead costs across several different projects.

Product flow is not meaningful in projects because the end product of most construc�on projects is designed to remain sta�onary. The usual term that describes the layout is fixed
posi�on. A project-oriented opera�on is very flexible, allowing extensive customizing of the finished products. Projects are common in service opera�ons, for example, Seibel
Systems develops and installs so�ware systems that control banking opera�ons. These so�ware systems can monitor each transac�on, keep a history on it, and assist in reconciling
the transac�on to the account. To design these systems, so�ware companies draw the needed talent from a pool of experts and form a project team. Because each system is
different, different groups may be used to develop each system. These companies provide a service and use project management to successfully complete the work.

Manufacturing Cells and Flexible Manufacturing Systems

Manufacturing cells and flexible manufacturing systems (FMS) are process op�ons that offer the poten�al to produce low-cost products that meet varying customer requirements.
Manufacturing cells rely on group technology to build a family of parts with similar design and processing characteris�cs. Group technology is a set of methods that enables firms to
classify parts based on size, shape, use, type of material, and method of produc�on. A family of parts is a collec�on of parts with similari�es in these characteris�cs. In this way, a
product-oriented layout (cell) can be designed that will reduce material-handling costs, increase machine u�liza�on, and shorten produc�on lead �mes. Because the processing is
similar, less �me is required to change from one product within the family to another (see Table 7.3).

An FMS is similar to a manufacturing cell because it relies on group technology to build families of parts. Also, like a manufacturing cell, an FMS produces low-cost products with
high variety. The major differences are that an FMS o�en has more automa�on, robots, and computer control than a manufacturing cell does, and it usually operates without
people tending the machines.Processing math: 0%

Direct Sales in Computers; Your Computer, Your
Way: Dell and the Direct Sales Model

Flexible manufacturing systems grew from the need to cope with demand for increasing product varia�ons. With an FMS, an organiza�on can capture new markets by accumula�ng
produc�on requirements from several low-volume products. Higher-volume opera�ons allow the arrangement of a set of machines in one layout to produce all the different
products. The products, however, must be similar enough to have the same or a similar sequence of opera�ons, and the machines must be flexible enough to handle the
differences. This system is feasible with computer technology and robo�cs that can quickly be adapted to new products. A manufacturing cell and an FMS enable organiza�ons to
increase the volume of product moving across a group of machines and, thereby, reduce opera�ng costs.

Mass Customization

Mass customiza�on offers an alterna�ve to addressing product variety. Firms that seek mass customiza�on are
able to design, produce, and quickly deliver products that meet specific customer needs at close to mass-
produc�on prices. These firms develop close rela�onships with their customers, which depend on frequent
informa�on exchange.

From an opera�ons perspec�ve, mass customiza�on is the low-cost, high-quality, large-volume delivery of
individually customized goods and services. Put simply, mass customiza�on combines the pursuit of economies
of scale and scope, quality improvement, and flexibility. Economies of scale and scope imply achieving high-
volume opera�ons and low costs. When pursuing flexibility, there are three a�ributes to consider:

1. Range/variety—The number of viable states for the produc�on system and the degree of difference in those
states. From the perspec�ve of range, the greatest variety is when a large number of very different products
can be produced

2. Mobility/responsiveness—The ability to change quickly from producing one product to producing another.
High mobility minimizes the need for long produc�on runs. How long does it take for the service center to
shi� from doing brake work on a Ford to doing exhaust work on a Chrysler?

3. Uniformity—The ability to a�ain similar performance across the en�re range of outputs. Will the quality on
the brake job for the Ford be at the same high level as the quality of the exhaust system for the Chrysler?

Flexibility is the greatest when all three elements of flexibility are at the highest level. That is, the firm can
produce a large number of products that are very different, can change between them quickly, and can
maintain a high level of performance.

Flexibility is an important factor for the service industry. Following are some examples of the product variety that services face.

1. Hospitals and medical clinics a�empt to treat pa�ents with a wide variety of needs.
2. With the deregula�on of financial markets, the differences between banks and brokerage houses have blurred. Banks are doing much more than taking deposits and making loans.
3. Universi�es are a�emp�ng to cope with an expanding number of majors, specialized degree programs, and individualized study programs. When this expansion occurs, universi�es

must have faculty who have the capabili�es to teach and conduct research across disciplines, else the capabili�es of the faculty may not match the changing needs of the
organiza�ons that hire the graduates.

Direct Sales
in Computers
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Chapter Summary

Facility loca�on should not be based en�rely on produc�on factors and transporta�on. Loca�on is a long-term strategic decision that can have a major impact on the
organiza�on’s ability to compete.
Loca�ng a facility can have strategic implica�ons. Some organiza�ons employ a regional facility approach where one facility is responsible for producing all the products for that
area of the country. Others employ the product facility strategy where one plant produces one product or product line and ships it throughout the country.
Both quan�ta�ve and qualita�ve factors influence the loca�on decision. These factors should be integrated if the decision-making process is to work effec�vely.
Loca�on influences costs, selling price, demand, and access to financial services.
Process defines the way that the products should be produced.
Process selec�on is closely related to the product design and capacity decisions.
A cost-volume-profit model is one way of reviewing processing op�ons. This model allows the organiza�on to examine the risks associated with selec�ng a processing op�on.
Mass-produc�on alterna�ves involve greater risk, but have the poten�al for greater return.
Process selec�on is a func�on of volume demanded. The different process types include line flow, which includes con�nuous flow and assembly line, batch, job shop, and project
as well as manufacturing cells and flexible manufacturing systems. Each of these process types is summarized in Table 7.3.
Mass customiza�on allows firms to achieve greater product variety while keeping costs low and produc�on volumes high.

Case Studies

Tilley Video Disc, Inc.

William (“Call Me Billy”) Tilley, founder, president, and chairman of the board of Tilley Video Disc, Inc., has a very pleasant problem. The market for digital video discs (DVD) is
expanding rapidly, and he has accepted an a�rac�ve offer for his controlling interest in Tilley Video Disc, Inc., while retaining his current management responsibili�es. The deal is
con�ngent on Billy’s development of a plan to expand produc�on from 10,000 to 50,000 units, and to lower produc�on costs. Evers, Inc., the company that has made the offer, feels
the growth in sales will be drama�c if costs can be significantly reduced.

Presently, produc�on of the video discs takes place in one plant in Rimer, Oregon. The plant was formerly a slaughterhouse and meatpacking facility. Billy has quickly come to the
conclusion that produc�on could be maintained at this facility, but that significant on-site expansion is not sound. The equipment in the facility was purchased from a bankrupt
company and has been used for several years. It can best be characterized as slow, general-purpose equipment. The following data has been compiled from the exis�ng plant for the
last 12 months:

Selling Price $6.50/unit
Variable costs $3.25/unit
Total Produc�on 9,824/year
Rejects 644/year
Sales 9,180/year
Es�mated capacity 10,000/year
Annual fixed costs $20,000

Evers’ vice president of marke�ng thinks that the selling price should be reduced to about $5.00 in order to achieve the needed sales growth and to grab market share in the highly
compe��ve consumer market. As a consultant to Billy Tilley, you are charged with developing a plan that will allow the company to increase capacity by 400% and reduce variable
costs by 20%. You should use the cost-volume-profit model in building your plan. Use an annual profit of $80,000 as a target profit. Provide a wri�en report that addresses the
following ques�ons:

1. Is it a good idea to keep the exis�ng facility?
2. What benefits may be derived from the new technology?
3. Should one facility be built, or should the plan have several small facili�es similar to the present facility?
4. Why and how will the cost structure of the new facility differ from that of the exis�ng one? Be specific. Use the C-V-P model to help describe the differences.

Dailey Computer Service

Kathy Dailey, president of Dailey Computer Service, has called you into her office to help plan the company’s future. Profits have been declining even though sales have increased.
During this �me, selling price and costs have not changed. The company sells three services: a payroll package; data entry services; and computer forms. The following table shows
the revenue and costs of these services:

Payroll
Package

Data entry
(per 1,000)

Computer forms
(per 100)

Selling price $3,500 $25 $35
Variable cost $800 $16 $30

Fixed costs average $40,000 per month.

Sales data for the last two months are listed here.

Two Months Ago Last Month

Units Sales Units Sales
Payroll (packages) 7 $24,500 5 $17,500
Data entry (1,000) 2,500 62,500 2,200 55,000
Forms (100) 1,400 49,000 2,000 70,000
Total sales $136,000 $142,500

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1. How did the firm manage to increase sales, hold the line on price and costs, and make less money? Be specific; Dailey wants numbers to back up your answer.
2. If Dailey Computer Service maintains the same sales mix as last month, how can it achieve a profit of $10,000 next month? Be specific.
3. From what you have discovered in this analysis, answer the following ques�ons:

a. How should Dailey Computer Service approach marke�ng?
b. Should price changes be considered?

Discussion Ques�ons

Click on each ques�on to reveal the answer.

1. Why is facility loca�on important to an organiza�on?
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Facility loca�on is the placement of a facility with respect to customers, suppliers, and other facili�es with which it interacts. The facility loca�on decision is cri�cal to an
organiza�on’s success because (1) the result of the decision is to commit a significant amount of an organiza�on’s resources, (2) the costs of reloca�on are high, (3) the loca�on
can greatly influence produc�on and transporta�on costs, (4) the loca�on affects an organiza�on’s ability to serve its customers, and (5) the loca�on can be a key ingredient in
an organiza�on’s strategy. The facility loca�on decision is a long term, strategic decision, which can have a major impact on the organiza�on’s ability to compete.

2. What factors are affected by the choice of loca�ons? Which of these factors can be measured in dollars, and which cannot?
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Facility loca�on decisions depend on marke�ng issues, produc�on factors and environmental decisions. Many organiza�ons require easy access to customers. Some choose to
locate near universi�es to take advantage of research facili�es. Some need easy access to raw materials. Some locate to take advantage of low labor rates, material and/or
transporta�on costs. The quality of schools, cultural advantages and banking services, along with others, can also play an important role in the loca�on decision.

Many of these factors can be measured in dollars while others cannot. Quan�ta�ve factors include costs associated with building the facility, producing the product, overhead,
and transporta�on to and from the facility. State and local governments offer incen�ves to a�ract and retain businesses and jobs, and these are quan�ta�ve, as well.
Qualita�ve factors include recrea�onal and cultural ac�vi�es, availability of labor, educa�onal and research facili�es, and many others listed in the appendix to this chapter.

3. How can qualita�ve and quan�ta�ve factors be integrated to make a sound and logical loca�on decision?
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Qualita�ve factors, whose direct impact on profits is not measurable, need to be carefully considered and integrated with quan�ta�ve factors. To integrate these factors,
managers should decide which qualita�ve factors are relevant to the decision, weight each relevant factor, and evaluate each site so that ra�onal comparisons can be made.
These scores can be summed for each site and compared with the results from the analysis of the quan�ta�ve factors. If one site is the best in both qualita�ve and quan�ta�ve
factors, then it would seem to be the correct choice. If not, then trade-offs need to be made among the sites.

4. What hidden factors are influenced by on-site loca�on, and how are they influenced?
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On-site expansion can create many problems, especially if it is a repeated prac�ce. As more produc�on space is added, material handling and storage become more difficult
because storage space is converted to produc�on. As new product varia�ons are added, the once simple product flow becomes complicated by twists, turns, and back-tracking.
On-site expansion can strain intra-plant transporta�on and communica�on.

Staying at the same site o�en postpones the introduc�on of new products and process technologies. Old equipment and old produc�on methods are used longer than they
should be. Future product innova�on, produc�vity increases, quality improvements, and cost reduc�ons can be nega�vely affected. On-site expansion can mean a growing
number of workers, products, and processes that need to be managed. Such layering of expanded responsibili�es creates real complexi�es for management at all levels.

5. Why are spa�al rela�onships important in the loca�on decision?
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In addi�on to factors like local labor costs and u�lity costs, the loca�on decision should consider spa�al rela�onships. Spa�al rela�onships are important because convenient
access by customers and/or the ability to transport large quan��es of material easily and quickly may be very important. In loca�ng a health care facility, the distance which
customers travel should be considered because it is important to the customer. When outbound transporta�on costs are high, manufacturing and warehousing tend to locate
close to customers. A good example of this is aluminum can producers. The cost to ship a can is very high because the organiza�on is shipping a lot of air and very li�le
product. On the other hand, when inbound transporta�on costs are high, facili�es tend to be located close to suppliers.

6. What is process selec�on, and how can the organiza�on use it to gain compe��ve advantage?
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Process describes the way in which the product is made. Process selec�on is a series of decisions that include technical or engineering issues and volume or scale issues. The
technical issues include the basic technology used to produce the good or service such as con�nuous cas�ng to make slabs in the steel industry. It includes the sequence of
steps, the equipment, and the facili�es needed to perform the services or produce the goods. Volume or scale decisions involve using the proper amount of mechaniza�on to
leverage the organiza�on’s workforce. Leverage means to make the workforce more produc�ve through the use of be�er tools. The purpose of leveraging is to achieve the
desired level of produc�on at an acceptable level of cost. Process is strategically important because it helps to define the product’s costs and quality.

7. How is process selec�on related to product design and capacity determina�on?
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644

Product design, capacity, and process selec�on decisions should be considered simultaneously rather than independently. The market research that helps to shape the product
design also provides an es�mate of the demand for the product at a price that customers are willing to pay. The demand for that product should be used to determine the
capacity the organiza�on will select. The amount of demand will help to determine how the product will be produced. Large volume products (and low product variety) tend to
be produced by line flow processes while low volume products (and high product variety) are produced in job shops.

The following example illustrates the rela�onships between product and process design. If a fast food sandwich is described as flame broiled, the process should not include
grills for frying. In turn, process selec�on influences product design. A wrist watch powered by light is an example where improvements in technology ul�mately led to new
product designs.

Process selec�on is constrained by the volume of the product required. For example, if the market for a product is es�mated at only 1,000 units per year, it would be very
difficult to jus�fy spending a great deal of money on a machine that will produce 100 units per hour. The machine will only need to operate ten hours per year to meet
demand.Processing math: 0%

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8. Explain how the cost-volume-profit model of a firm is derived. How is it useful to opera�ons managers in making the process selec�on decision?
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644

The cost-volume-profit (C-V-P) model uses es�mates of costs, revenues, volume sold, and volume produced in order to es�mate profit. The C-V-P model is formulated by
determining total revenue and costs. The difference between revenue and costs is profit. The model allows managers to calculate profit for any sales or produc�on volume. It
also can be used to determine the volume required to be produced and sold to achieve a given level of profit. It is useful for opera�ons managers in making the process
selec�on decision because the cost structure (the amount of fixed and variable costs) can be changed to represent the different processes. Line flow processes have high fixed
and low unit variable costs while job shops have low fixed and high unit variable costs. By trying different alterna�ves, the impact of process selec�on on profit can be
determined.

9. What are line flow processes, and what characteris�cs help to define them? Give examples.
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644

High volume opera�ons are generally referred to as line flow processes. Line flow processes are characterized by standard products, a dominant product flow, high fixed costs,
low unit variable costs, and special purpose equipment. One type of line flow is the con�nuous flow process. A good example of a con�nuous flow opera�on is an oil refinery.
Another good example is a paper mill. Assembly lines refer to opera�ons that assemble a high volume of discrete products. Automobiles are made on assembly lines.

10. What is batch flow, and what characteris�cs help to define it? Provide examples.
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644

Batch flow describes a produc�on process that does not have sufficient volume from a single product to fully use the facility. Several products are made on the same
equipment to provide sufficient volume. Changeover �me is generally required to change the facility from one product to the next. Thus, products are made in batches. Batch
opera�ons are characterized by limited product variety, small differences between product flows, high fixed costs but not as high as a line flow process, moderate unit variable
costs, and special purpose machines which have some flexibility in order to deal with product variety. The auto parts manufacturer referred to in the text is a good example of
batch flow.

11. What is a job shop, and what characteris�cs help to define it? Provide examples.
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Job shops are characterized by the need to produce only a few units of a given product with no guarantees that the product will ever be made again. Differences between
products can be significant. A job shop is characterized by product flows that vary significantly, low fixed costs, and high unit variable costs. The facility for such an opera�on
must be general and flexible. Hospital emergency rooms and five-star restaurants are examples of job shops.

12. What is a project, and what characteris�cs help to define it? Provide examples.
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644

Projects are generally one-of-a-kind opera�ons in which each job is different. Projects are characterized by low to moderate fixed costs, high variable costs, and tremendous
flexibility. Construc�on work and installa�ons of large computer hardware and so�ware systems are good examples of projects.

13. How will flexibility help an organiza�on achieve a compe��ve advantage?
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644

In the future, flexibility in the produc�on process will play an increasingly important role. Changing customer demand and specialized design will give producers that have
flexibility a compe��ve edge because they can provide a variety of products in a �mely fashion and at low costs.

Problems

1. Darwal Developers specializes in analyzing facility loca�on decisions. Presently, the company is looking at two loca�ons: Orlando, Florida, and Olympia, Washington, for which it has
determined the following cost informa�on:

Orlando Olympia
Variable costs $14.70/unit $16.45/unit
Annual fixed costs $12,000,000 $11,000,000
Ini�al investment $166,000,000 $145,000,000

a. At a volume of 800,000 units per year for a 10-year period, which facility has the lower cost?
b. At what annual volume do these facili�es have equal costs? Once again, assume a 10-year period.
c. Graph the results of Part b.

2. Marvin Manufacturing is considering three loca�ons for its new plant: Tucson, Arizona; San Diego, California; and Newark, New Jersey.

Tucson San Diego Newark
Variable costs $1.60/unit $1.45/unit $1.50/unit
Annual fixed costs $1,800,000 $2,000,000 $1,900,000
Ini�al investment $14,000,000 $16,000,000 $15,000,000

a. At a volume of 2 million units per year for a 5-year period, which facility has the lowest cost?
b. At what annual volume(s) do these facili�es have equal costs? Assume a 5-year period. (Hint: It is helpful to graph each of the cost equa�ons before solving for the point where

the costs are equal.)

3. Intensive Technologies consults for clients in the aerospace industry. Their corporate headquarters is located in Washington, D.C., but the organiza�on is planning to relocate to the
West Coast. It is considering three sites: Sea�le, Washington; Portland, Oregon; and Oakland, California. The full costs of opera�ng at each site, which include ini�al investment,
annual fixed costs, and variable costs, are approximately equal. A management team from Intensive Technologies has visited each city, and has evaluated each site using the
following criteria. The evalua�on uses a 1-to-10 scale, with 1 being the best score. Top management selected the criteria and the weight assigned to each factor.

Weight Oakland
Score

Portland
Score

Sea�le
Score

University research specializing in aerospace 50 4 2 2
Processing math: 0%

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Available pool of skilled engineers 50 4 3 2
Opportunity for advanced management educa�on 40 2 3 3
Cultural ac�vi�es 20 1 2 3
Recrea�onal ac�vi�es 20 2 4 3

a. What is the weighted score for each city?
b. Which city has the advantage in terms of the qualita�ve factors? Is this advantage significant?
c. What is your recommenda�on to top management?

4. Barrel City Health Care System is looking for a new loca�on for its corporate headquarters. It is considering Atlanta, Georgia, and Danville, Illinois. The ci�es are rated from 1 to 10 on
each of the following factors, with 10 as the best score.

Weight Atlanta Score Danville Score
Cultural ac�vi�es 40 8 6
University research facili�es 80 8 8
Union ac�vi�es 60 8 4
Banking services 60 6 8
Available labor 20 6 8

a. Determine the weighted scores for both ci�es.
b. How can these scores be integrated with cost differences?
c. Suppose the following costs apply:

Atlanta Danville
Opera�ng costs $1,400,000/year $1,300,000/year
Ini�al investment $22,000,000 $20,000,000

Over a 10-year period, Danville has a $3,000,000 advantage. To determine that, take the difference in opera�ng costs per year, and mul�ply it by 10 years. Then add
the difference in ini�al investment. Under what circumstances might the company s�ll choose Atlanta? How much would Barrel need to value each point of Atlanta’s
qualita�ve advantage to make it the new headquarters?

5. Nelson, Neddel, and Nickersen (NNN) Stockbrokers are planning to invest in automated equipment that will process stock transac�ons. The equipment requires a $12 million annual
investment. The opera�ng costs are $120 per hour. The equipment can generate 5,000 transac�ons per hour.

a. What is the unit cost of a transac�on if 1 million are required?
b. What is the unit cost if 10 million are required?
c. What is the unit cost if 100 million are required?
d. Why would NNN want to keep the level of transac�ons high?

6. George’s Mold Shop is planning to bid on a plas�c part for automakers. If George’s gets the bid, the manager is planning to buy a new semi-automa�c machine to speed up the
produc�on process. The annual fixed cost of the machine is $45,000. The machine requires only part-�me supervision, and the labor cost is es�mated at $1.50 per hour. This has
been calculated as 0.08 hour of labor at $18.75 per hour. On average, the machine can produce 140 pieces per hour and is expected to operate for 2,000 hours per year.

a. What is the unit cost of a plas�c part if 10,000 are required?
b. What is the unit cost if 100,000 are required?
c. What is the unit cost if 200,000 are required?
d. What is the unit cost if the machine operates at capacity for the en�re year?

7. Slimline Manufacturing makes briefcases. It is considering the purchase of new s�tching machines for its final assembly. Following are the data for analysis:

System Annualized Fixed Costs Variable Costs
Spurance $3,500 $1.25/unit
Yamamoto $8,000 $0.85/unit

a. If Slimline’s demand is for 8,300 briefcases per year, which system should the company use?
b. If Slimline needs to s�tch 19,800 cases per year, which system has the lower cost?
c. At what volume do the two alterna�ves have equal costs?

8. Finn Bank and Trust is comparing a manual system for processing checks with a highly automated system. Presently, the bank processes about 10,000 checks each workday, and it
operates 250 days per year. In the near future, it is planning to sell check-processing services to other small rural banks in the area. The bank’s management has collected the
following data:

System Annualized Fixed Costs Variable Costs
Manual $50,000 $0.045/check
Automa�c $350,000 $0.005/check

a. At its present volume of checks, which system should Finn use?
b. If Finn can process checks for other banks and boost its volume to 100,000 checks per day, which system has the lower cost?
c. At what volume do the two alterna�ves have equal costs?

9. The X-ray machine at Marchal Medical Center was purchased and installed nearly four decades ago. Medically, the machine func�ons very effec�vely, but requires excessive �me to
adjust for each pa�ent. A new X-ray machine is available that will reduce the �me required to serve a pa�ent.

System Annualized Fixed Costs Variable Labor Costs
Processing math: 0%

Old X-ray $40,000 $4.00/X-ray
New X-ray $120,000 $1.00/X-ray

a. Which system would provide lower costs if the annual pa�ent demand is 15,000?
b. If volume could be boosted to 20,000 pa�ents per year, which system would provide the lower costs?
c. At what pa�ent volume do these alterna�ves have equal costs?

10. Quill Pen Company sells pens that are o�en purchased as gradua�on presents. The pens sell for $5.50 each and cost $1.50 per unit to produce. Fixed costs total $40,000 per year.
a. How many pens must Quill sell to cover fixed costs?
b. How many units must Quill sell to make $50,000 profit per year?
c. If fixed costs increase by $10,000 per year, what are the answers to Parts a and b?

11. Brockman Visi�ng Nurse Service has determined that it will cost approximately $20 each �me one of its nurses visits a sick person at home. The charge is $30, part of which is paid
by the pa�ent and part by insurance. Overhead expenses are $7,000 per month.

a. How many calls must the service make to cover overhead expenses?
b. How many calls must it make to ensure a $3,000 profit per month?

12. A.J. Electronics produces monitors for microcomputers. It has a one-shi� opera�on with fixed costs of $25,000 per month. The cost of purchased parts is $20 per unit, and the
standard labor cost is $15 per unit. The company sells the monitors for $55 each to customers who sell them under their own brand names.

a. How many monitors does A.J. have to produce and sell each month to cover costs?
b. How many monitors must be produced and sold to meet a $5,000 target profit?

13. Presently A.J. has the capacity to produce 1,600 monitors each month if it maintains a one-shi� opera�on. The A.J. sales staff is nego�a�ng a deal with a major seller of
microcomputers that will increase units sold per month from approximately 1,400 to 3,000. If the deal is successful the opera�ons manager plans to add a second shi�. Adding a
second shi� will increase fixed costs by $10,000 per month and increase produc�on labor costs to $16 per unit for those units produced on the second shi�. This increase is due
en�rely to paying a premium (shi� differen�al) for second-shi� labor. The unit price for purchased parts will drop by $0.50 for units produced on both shi�s because of discounts for
buying larger quan��es. The addi�on of a second shi� will add 1,600 units per month to capacity.

a. Graph A. J.’s cost-volume-profit rela�onship for one shi� only.
b. Graph A.J.’s cost-volume-profit rela�onship for two shi�s.
c. How many units must A.J. produce and sell to cover its costs when the second shi� is in place?
d. At what volume does A. J. make a $24,000 profit per month?
e. What happens to the company’s profit if the selling price of monitors drops by $5 per unit? Be specific, using calcula�ons to support your answers.

14. Carder Kitchen Utensil Produc�on makes steak knives and salad forks in the same facility.

Steak Knives Salad Forks
Product mix 0.7 0.3
Selling price $0.80 $0.40
Variable cost/unit $0.50 $0.25

Annual fixed costs are es�mated at $250,000

a. At what volume will Carder cover its costs, given the present mix?
b. At what volume will Carder report a $150,000 annual profit, given the present mix?
c. If the mix changes to 0.6 for steak knives and 0.4 for salad forks, recalculate the answers to Parts a and b.
d. If the price of a steak knife is raised by $.05, what is the impact of this new mix on the volume required to make a $150,000 profit?

15. Junge Hardware Products makes nuts, bolts, and washers in the same facility.

Nuts Bolts Washers
Product mix 0.4 0.4 0.2
Selling price $0.07 $0.09 $0.03
Variable cost/unit $0.03 $0.06 $0.001

Annual fixed costs are es�mated at $2,500,000.

a. At what volume will Junge cover its costs, given the present mix?
b. At what volume will it report a $1,500,000 annual profit, given the present mix?
c. If the price of a bolt is raised by $.01, what happens to the volume required to make a $1,500,000 profit?

16. Winken, Blinken, and Knod, Inc., is considering three different machines to grind contact lenses. The annual costs and opera�ng costs are listed below.

Annualized Fixed Costs Variable Opera�ng Costs
Manual grinder $9,000 $5.00/lens
Automa�c grinder $30,000 $2.50/lens
Computer controlled automa�c grinder $50,000 $0.75/lens

a. If 10,000 lenses are needed, which op�on has the lowest cost?
b. If 20,000 lenses are needed, which op�on has the lowest cost?
c. At what volume(s) of lens produc�on do the alterna�ves have equal costs?
d. How would you explain these op�ons to management?Processing math: 0%

Click here to see solu�ons to the odd-numbered problems.
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Key Terms

Click on each key term to see the defini�on.

assembly line
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A process through which discrete parts are put together to make a finished product. It is a high volume opera�on that produces products that are very similar in features and
performance.

batch
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A term used to describe a produc�on process that does not have sufficient volume from a single product to fully use the facility. The facility must produce several products to have
sufficient volume to achieve economies of scale. There is an equipment changeover prior to making each product.

break-even point (BEP)
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The volume of a good or service that must be produced and sold so that profit is zero. This is the zero profit point in the cost-volume profit model.

changeover �me
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The �me required to change the facility or equipment from making one product to making the next product.

concurrent engineering
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Occurs when design and process engineers work together to make be�er decisions and reduce the �me it takes to bring products to market.

con�nuous flow process
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A process for mass producing products that does not iden�fy individual units. The products are mixed and flow together in a con�nuous stream. Oil refining is a good example of a
con�nuous flow process.

contribu�on per unit
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The selling price of a unit minus the variable cost of producing the unit. It is the amount that each unit of sale contributes toward covering overhead costs and mee�ng profit
objec�ves.

cost-volume-profit (C-V-P) model
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A simple model of an organiza�on that uses es�mates of costs, revenues, volume sold, and volume produced in order to es�mate profit.

economies of scope
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

Economies of scale across products. Implies building the volume necessary to cover fixed costs by producing a variety of products on the same equipment. This requires flexibility
within the organiza�on.

family of parts
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A group of parts that require similar machining opera�ons.

group technology
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A set of methods that enables firms to classify parts based on size, shape, use, type of material, and method of produc�on.

job shop
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A facility capable of producing a wide variety of products in very small volumes. The produc�on facility is general purpose and flexible enough to meet a variety of needs.

leverage
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

When referring to opera�ons and produc�vity, leverage makes the work force more produc�ve through the use of be�er tools.

Processing math: 0%

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line flow processes
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

High volume opera�ons. Two examples of line flow processes are con�nuous flow processes and assembly lines.

mass customiza�on
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The ability to quickly design, produce, and deliver products that meet specific customer needs at close to mass-produc�on prices. This is the low-cost, high-quality, large volume
delivery of customized products.

process layout
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The grouping or arrangement of equipment by the type of process that the machine performs, such as all drilling equipment in one loca�on.

process selec�on
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A series of decisions that include technical or engineering factors and volume or scale factors. The result determines how the services or goods will be produced.

product facility strategy
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A strategy wherein one facility is responsible for both producing a product or product line and shipping that product all over the country and around the world.

product layout
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The physical arrangement of facili�es so that products move along one path. Resources are arranged around this path to minimize material movement, reduce material handling
costs, and eliminate delays in produc�on.

profit point
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

The number of units that must be produced and sold at a given contribu�on per unit in order to cover fixed costs plus profit. The break-even point is a special case of the profit
point where target profit is zero.

project
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A process for making one-of-a-kind products.

regional facility strategy
(h�p://content.thuzelearning.com/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/sec�ons/cover/books/AUBUS644.13.2/

A loca�on strategy in which each facility is assigned a market area and each facility produces a complete line of products for that area.

Chapter 7 Appendix

EXAMPLE OF THE FACTORS IN LOCATION ANALYSIS

Many factors that cannot be measured in dollars should be considered in the loca�on decision. The factors in the following list are o�en important.

UTILITIES

Water

Water supplied by: ________________________________Municipal __________Private ______

Name of supplier: ________________________________________________________________

Address: ________________________________________________________________________

For rate informa�on, contact: _______________________________________________________

Source of city water: River(s) _________ Wells ________ Lake(s) or reservoir(s) ____________

Supply of river water available: ____________________ cu. �./sec.

Supply of lake or reservoir water: __________________ gals.

Water supply approved by State Board of Health: Yes _________ No ____________

Capacity of water plant: __________________________ gals./min.

Average consump�on: ___________________________ gals./day
Processing math: 0%

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Peak consump�on: ______________________________ gals./day

Sanita�on

Type of sewage treatment plant: ________________________________________________

Treatment plant cer�fied by the State Board of Water Pollu�on: Yes _______ No _________

Characteris�cs of waste treatment plant:

Measurement          Capacity             Present Load

Gallons per day       _________________ _________________

Popula�on equivalent _________________ ________________

Natural gas

Natural gas service available:                  Yes __________ No _______

Name: ____________________________________________________________________

Address: __________________________________________________________________

For rate informa�on, contact: _________________________________________________

Electricity

Suppliers:         Municipal _______ Private _______ Co-op ______

Name(s): ________________________________________________________

Address(es): _____________________________________________________

For rate informa�on, contact: _______________________________________

LOCAL MANUFACTURING CHARACTERISTICS

Number of manufacturing plants in community: _________________________________________

Number of manufacturing plants with unions: ___________________________________________

Number of manufacturing employees in community: _____________________________________

Strikes within last 5 years affec�ng 5% or more of the labor force: __________________________

Major manufacturers or other large employers in community: _____________________________

Name of firm: _______________________________________________________________________

Employment: ______________________________________________________________________

Product(s) manufactured: ____________________________________________________________

LABOR MARKET ANALYSIS

Date of last labor market survey: ___________________________________________________

Results of survey: _______________________________________________________________

Es�mated labor force available: ___________________________________________________

This es�mate can be documented:           Yes ____________ No _____________

County labor data:

Civilian work force (annual average): ______

Unemployed: ______________________________________

Unemployed as a percentage of workforce: ______________

Total employment: __________________________________

Agricultural employment: _________________________

Nonagricultural employment: ______________________

Manufacturing employment: _____________________
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Nonmanufacturing employment: ___________________

HEALTH FACILITIES

Number of hospitals in community: __________

Number of beds: ____________

If no hospitals, distance to nearest facility: ___________________________________________

Clinic in community:       Yes ____________ No _____________

Medical personnel:        MD(s) _________ DO(s) ___________

Nurses:                  Registered ______ Prac�cal

RECREATIONAL FACILITIES

Type of recrea�onal facili�es available in city or within 10 miles:

Public golf course(s) ________________ Public park(s) __________________

Public tennis court(s) _______________ Public swimming pool(s) __________

Country clubs available:                     Yes ___________ No _____________

Nearest public access to lake or river:           _____________________miles

Ac�vi�es allowed:

Swimming ________________________ Fishing ________________________

Water skiing ______________________ Motor boa�ng _________________

LOCAL INDUSTRIAL DEVELOPMENT ORGANIZATION

Name of group: _________________________________________________________________

Person to contact: _______________________________________________________________

Address: _______________________________________________________________________

Phone number: _________________________________________________________________

Home: ________________________________________

Business: ______________________________________

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12.4 Dispatching in MRP

The rules men�oned above are limited because they only consider the condi�ons that exist for a given point in �me and a given work center. By and large, they ignore that a given
part may be part of a subassembly that must be complete before the final product can be assembled.

MRP takes into account lead �mes. As long as the planning lead �mes used in MRP are valid, then the priority of each item should be based on the MRP lead �mes. Therefore, in
an MRP system, priori�es are determined by referring to the planned order releases and lead �mes. Thus, the dispatching rules are irrelevant to MRP systems. Instead, MRP works
from the order due dates, scheduling order releases far enough ahead of �me that the due dates should be met. Unfortunately, there s�ll may be conflicts at machines and work
centers that need to be addressed.

Machine Loading

The dispatching rules previously described a�empt to determine a schedule based on the a�ributes, such as due date or processing �me, of each job. However, the �me it takes for
a job to be processed consists of the following five components:

1. Wait �me
2. Move �me
3. Queue �me
4. Set-up �me
5. Run �me

Wait �me is the �me a job spends wai�ng before it is moved to the next work center. Move �me is the material-handling �me between work centers. Queue �me is the �me a job
spends wai�ng to be processed at a work center. Set-up �me is the �me to prepare a machine to process that job, and run �me is actual processing �me.

In general, all of these components—except queue �me—will be nearly fixed. Queue �me really depends to a large extent on the workload that has been scheduled for each work
center. If a machine’s capacity is being used extensively, then it is more likely that many jobs will be wai�ng for processing at that machine. When the capacity of a work center is
exceeded, lines of work (queues) will build up in front of that work center.

Loading is an approach to scheduling that a�empts to take capacity u�liza�on into account. There are several different approaches to loading, but loading begins with scheduling.

Forward Scheduling

Suppose scheduling begins immediately so that each job starts at the earliest possible moment. This is called forward scheduling. As jobs progress through a produc�on facility, each
work center will have a certain workload placed on it from the jobs assigned to that work center. Figure 12.6 illustrates the schedule that could be generated by forward scheduling
four jobs (A, B, C, and D) through three work centers (lathe, mill, and drill). This schedule assumes six hours for wait and move �me between machines. Note that the jobs use the
same three work centers, but use them in different orders, so Opera�on l for Job A uses the lathe, but Opera�on l for Job D uses is the drill. Also note that Job B and Job D do not
use the lathe and the mill, respec�vely.

Figure 12.6: Forward schedule for four jobs with finite loading

Work Center Sequence and Processing Time

(Number Is Sum of Set-up and Run Times in Hours)

Job Opera�on I Opera�on II Opera�on III

A Lathe 3 Drill 2 Mill 4

B Mill 4 Drill 3

C Lathe 2 Mill 3 Drill 4

D Drill 5 Lathe 4

In a forward schedule shown in Figure 12.6, each job begins as close to �me zero as possible, and each job is scheduled similarly through the successive opera�on, allowing six
hours for wait and move �me between machines. Some jobs have been delayed (queue �me) at certain work centers because another job had already started at that work center.Processing math: 0%

For example, Job C had to wait three hours before it could start on the lathe because Job A was s�ll being processed on that machine. This approach of making one job wait if
another has been scheduled on the same machine is called finite loading because it takes into considera�on the limited capacity on each machine. Another approach uses infinite
loading, which does not take capacity considera�ons into account. Infinite loading assumes that there is unlimited or infinite capacity.

Backward Scheduling

Backward scheduling starts from a desired due date and works backward. The informa�on for the four jobs and three work centers previously presented is used again, but the
following due dates are added:

Job Due Date

A Hour 24

B Hour 16

C Hour 24

D Hour 16

In this case, infinite loading will be used, elimina�ng the problem of more than one job at the same work center at the same �me. The resul�ng schedule is shown in Figure 12.7.
Backward scheduling begins by scheduling the last opera�on for each job so that it would end at the �me due, and then works backward through each opera�on. As a result of
infinite loading, some work centers have been scheduled to do more than one job at one �me. This may not be a problem if more than one machine is available. Actually, either
finite or infinite loading can be used with either forward or backward scheduling.

Figure 12.7: Backward schedule for four jobs with infinite
loading

Either of the preceding schedules can also be used to generate a load profile for each work center. A load profile indicates the workload being placed on that work center. Figure
12.8 shows the load profiles for the backward schedule of Figure 12.7 at an hourly rate. These load profiles were obtained by adding up the number of jobs scheduled during each
hour for each machine. No�ce that any hour in which more than one hour of machine �me is scheduled could present a problem if only one of each machine is available.

Figure 12.8: Load profiles for backward schedule

Forward and backward scheduling are both widely used—and many companies use both. Forward scheduling is useful for jobs that need to start immediately. Backward scheduling
works well when a desired due date is specified. Both finite and infinite loading can be used with forward and backward scheduling. Finite loading requires much more effort for
companies to keep track of which jobs are scheduled for which machines and at what �me. Unforeseen problems, varia�ons in processing �me, and other factors can combine to
make this a wasted effort. Therefore, most companies use infinite loading and then address over-loaded work centers a�er examining the load profile.

This approach to scheduling helps to point out the importance of capacity requirements planning and its �e-in with both the medium-range produc�on plan and the master
schedule. While capacity requirements planning is only a rough es�ma�on, it s�ll helps to ensure that sufficient capacity will be available. If the master schedule indicates a realis�c
capacity, then infinite loading does not o�en produce too many problems.

Sequencing

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When using a forward schedule with finite loading, two jobs are not allowed to be in the same work center at the same �me. Thus, if Job 1 had been started at work center A, Job
3 had to wait. But, would it have been be�er to start Job 3 on work center A first and make Job 1 wait? To answer that ques�on, it is possible to use a tool to schedule each work
center— the Gan� load chart.

Each work center can be indicated by one bar on the Gan� load chart. The job being processed at each work center and its processing �me can also be indicated. Figure 12.9 shows
the Gan� load chart that corresponds to the forward finite load schedule of Figure 12.6. The primary difference between the forward schedule shown in Figure 12.6 and the Gan�
load chart in Figure 12.9 is that the former is organized by job and �me, and the la�er is organized by opera�on and �me. The Gan� load chart is very useful for finite scheduling
because it allows only one job to be run on each machine or work center at one �me. Any conflicts will immediately become apparent.

Figure 12.9: Gan� load chart for forward schedule

Input/Output Control

Input/output control is a simple method for managing work flow and queue lengths. If work is put into a work center faster than it comes out, a queue will build up. If work is put
in at a slower rate than it comes out, the work center may run out of work.

Figure 12.10 shows the input/output report for a work center. The cumula�ve devia�on of actual input from planned input, and cumula�ve devia�on of actual output from planned
output are recorded each week. Further, the cumula�ve change in backlog is determined each week by comparing actual input to actual output. For example, in week 43, actual
output exceeds actual input by 30 hours. Therefore, the cumula�ve backlog decreases by that amount. In week 45, actual input exceeds actual output by 20 hours, therefore,
backlog increases by 20 hours.

Figure 12.10: Input/output report in standard hours

Simulation in Developing Schedules

Scheduling and sequencing can be rather difficult in some situa�ons. This is especially true in job shops where many different end products require different opera�ons.
Unfortunately, manually developing schedules in such situa�ons can be extremely �me consuming and difficult because there are too many combina�ons to consider.

Computers help to address this difficulty. Using simula�on techniques, it is possible to develop a trial schedule on the computer and then test that schedule without actually
processing the jobs. Through this simula�on, poten�al problems can be iden�fied and an improved schedule can be developed. Today, more companies are developing computer
simula�on programs to help solve their scheduling problems.

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8

©Fotosearch/SuperStock

Capacity Decisions

Learning Objec�ves
A�er comple�ng this chapter, you should be able to:

Define capacity as a measure of an organiza�on’s ability to provide customers with the requested service or
good.
Explain that capacity es�ma�on is difficult because many management decisions affect capacity.
Describe how overall capacity of the system is dependent on the capaci�es of the departments and machines
that form the produc�on system.
Determine the bo�leneck in a system and demonstrate how that informa�on can be used.
Describe key capacity decisions, such as how much capacity to add; when, where, and what type (process) of
capacity to add; when to reduce capacity and by how much.

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To es�mate capacity, managers must first select a way to measure it. Hospitals o�en use beds as a
measure of capacity.

©Hemera/Thinkstock

8.1 Capacity Defined

Capacity is a measure of an organiza�on’s ability to provide customers with the demanded services or goods in the amount requested and in a �mely manner. Capacity is also the
maximum rate of produc�on. An organiza�on marke�ng and selling ro�sserie chicken should be able to produce and deliver chicken in sufficient quan��es to sa�sfy consumer
demand during lunch and dinner �mes when demand peaks. Mee�ng customer demand requires the acquisi�on of physical facili�es, the hiring and training of qualified people, and
the acquisi�on of materials to achieve the desired produc�on level. The following important ques�ons about capacity planning are addressed in this chapter:

How can management es�mate capacity?
What is system capacity, and why is it important?
How can capacity decisions be made to gain a compe��ve advantage for the
organiza�on?

Role of Capacity Planning

Capacity planning is very important because significant capital is usually required to
build the facili�es and purchase the equipment to build capacity. Crea�ng a series of
large server farms to support the Internet and data communica�ons requires substan�al
investment. Millions of dollars are required to build a brewery, a hospital, or a kni�ng
produc�on line to make sweaters. These expenditures are for fixed assets that are
expensive to maintain and even more expensive to change. Capacity decisions require
careful considera�on of an organiza�on’s long-term objec�ves and the market demand.
Capacity decisions must be consistent with current and an�cipated demand.

Organiza�ons should be flexible in order to meet future as well as present capacity
requirements. Flexibility can allow managers to:

Adjust produc�on volume to respond to changes in customer demand.
Produce different products on the same equipment (product mix) to respond to
changing customer needs.
Alter product technology and process technology to maintain or improve an
organiza�on’s compe��ve posi�on.

Real World Scenarios: Meijer Superstores

Meijer superstores provide consumers with a full range of food products as well as a diverse range of other products, such as spor�ng goods, automo�ve supplies, clothes, and
lawn care equipment. Meijer’s concept is twofold: 1) build big stores that have high sales; and 2) aggressively expand the number of stores. In addi�on to the advantage of
one-stop shopping, Meijer’s large capacity stores offer other advantages.

The average purchase made by each customer should be higher because of the wide product variety. Although most tradi�onal grocery items such as bread, rice, and milk have
very low profit margins, products like microwaveable hamburgers, organic products, free-range chicken, and in-store bakery goods have higher margins and these boost profits.

Larger capacity allows Meijer to spread the fixed cost of a store over a greater sales volume, thereby reducing costs and increasing profits. For example, when more customers
shop at Meijer, the cost of floor space, food display racks, and checkout facili�es remain unchanged. These are simply u�lized at a higher level. Hea�ng and ligh�ng costs are
also unaffected by these addi�onal shoppers, for the most part. Meijer is crea�ng economies of scale by serving more customers with the same facili�es and equipment.
Examples of variable costs for Meijer include staffing levels for checkout counters and spending for items such as eggs and milk when customers buy more. Meijer also has
installed self-checkout facili�es that take less space and reduce labor costs at checkout to increase facility u�liza�on and to enhance produc�vity.

Meijer is also spreading the fixed costs of corporate opera�ons over more stores by rapidly expanding the number of new stores. In addi�on to cu�ng the per-store share of
these corporate-level fixed costs, expansion gives Meijer more buying power, which enables it to nego�ate be�er prices and delivery schedules from suppliers.

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An organiza�on’s product mix is the percentage of total output devoted to each product. Johnson &
Johnson is a large corpora�on with an expansive product mix including consumer and pharmaceu�cal
products such as Tylenol and BAND-AIDs.

©Mike Derer/ Associated Press/AP Images

8.2 Estimating and Altering Capacity

Before es�ma�ng capacity, it is necessary to recognize the difference between theore�cal or ideal capacity and achievable capacity. Theore�cal capacity is what a service firm or a
manufacturer can produce under ideal condi�ons for a short period of �me. Under ideal condi�ons there are no equipment breakdowns, maintenance requirements, material
problems, or worker errors. While organiza�ons strive to eliminate these unproduc�ve delays, allowances for these elements must be made in order to develop realis�c es�mates of
capacity.

To es�mate capacity, managers must first select a way to measure it. In some cases, the choice is obvious, for example, tons per hour of steel or kilowa�-hours of electricity. A
hospital can use beds as a measure of capacity. Thus, a hospital with 100 beds that are available 365 days per year has a capacity of 36,500 pa�ent-days each year. Hospitals
measure the number of pa�ents admi�ed and how long each stays so they can calculate pa�ent-days consumed. A comparison of pa�ent-days consumed and pa�ent-days available
gives the opera�ng ra�o shown below.

*Throughout this text, to enlarge the size of the math equa�ons, please right click on the equa�on and choose “se�ngs” then “scale all math” to increase the viewing percentage.

In general, the opera�ng ra�o is calculated according to the following equa�on:

Finding a yards�ck to es�mate capacity is more difficult in a restaurant than in a hospital because there is no uniform product on which the measurement can be based. Capacity
could be measured in terms of people served, meals prepared, or the ability to generate sales dollars. It is management’s responsibility to select the appropriate measure and apply
it.

Once the measure has been selected, es�ma�ng capacity involves the following steps:

1. Determine the maximum rate per hour of the produc�on equipment.
2. Determine the number of hours worked in a given �me period.
3. Mul�ply those two numbers.

Capacity can be changed by changing the number of hours worked in a �me period, or by changing the produc�on rate. The number of hours worked per �me period is affected by
several factors, including over�me, mul�ple shi�s, down�me for preven�ve maintenance, and allowances for unplanned equipment failure.

Problem

Given the following informa�on on maximum produc�on rate and hours worked for an oven that cooks pizzas, determine the capacity per week.

Maximum produc�on rate = 40 pizzas/hour
Number of hours = 84 hours/week

Over�me = 0 hours/week
Preven�ve maintenance = 0 (because it is performed a�er closing)

Equipment failure = 2% of planned hours
(Unplanned down�me)

Capacity/week = (40 pizzas/hour)(84 + 0 – 0 hours/week)(1 – 0.02)
= 3,292.8 pizzas/week

The hours worked per week is reduced from 100% to 98% of the available hours because of the 2% down�me an�cipated for equipment failure.

Several management decisions affect capacity. For example, increases in the amount and
quality of preven�ve maintenance could increase capacity by reducing unexpected
equipment failure. Other decisions affect capacity by changing the produc�on rate. The
following decisions are examined in this sec�on:

Changing the mix of products produced by the facility.
Adding people to the produc�on process.
Increasing the mo�va�on of produc�on employees.
Increasing the machine produc�on rate.
Improving the quality of the raw materials and the work in process.
Increasing product yield.

Product Mix

An organiza�on’s product mix is the percentage of total output devoted to each
product. For example, an agency may sell life, house, and automobile insurance. How
does product mix effect capacity? It may take more of an agent’s �me to sell life
insurance than automobile insurance. Consequently, a shi� in demand toward life
insurance policies reduces an agent’s selling capacity. In theory, the agent should earn
more money selling life insurance to compensate for the extra �me. Otherwise, the
agent will favor house and auto insurance.

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Problem

Assume that each contact for life insurance takes three hours, house insurance takes two hours, and automobile insurance requires one hour. What are the capaci�es of an
agent who works 40 hours per week under Mix 1 and Mix 2?

Type Mix 1 Mix 2

Life insurance 0.20 0.40

House insurance 0.30 0.40

Automobile insurance 0.50 0.20

Begin by calcula�ng the produc�on rate for each type of insurance. These produc�on rates represent what an agent could do if he or she sold only that type of insurance.

Produc�on Rate = (hours worked per week)/(hour required per unit)

Produc�on RateLife = (40 hrs./wk.)/(3 hrs./unit) = 13.33 contacts per week

Produc�on RateHouse = (40 hrs./wk.)/(2 hrs./unit) = 20 contacts per week

Produc�on RateAuto = (40 hrs./wk.)/(1 hr./unit) = 40 contacts per week

Now calculate the capacity for one week if Mix 1 is assumed. Now, the agent’s �me is divided among the various types according to the mix.

PR = (13.3 contacts/wk.)(0.2) + (20 contact/wk.)(0.3) + (40 contacts/wk.)(0.5)

= 28.67 contacts/wk.

As an exercise, calculate the capacity if Mix 2 is assumed. (The answer should be 21.33 contacts per week.) Thus, as the mix shi�s away from automobile insurance to life and
house insurance, which require more �me per contact, the capacity of an agent as measured by the number of contacts declines. If an average selling price for each type of
contract can be determined, it would be possible to calculate the capacity of a sales person when genera�ng revenue on a daily, weekly, or monthly basis.

Product mix issues are also relevant in manufacturing. A steel company produces steel of many alloys, shapes, and sizes, and these differences require different produc�on processes
and �mes. For example, the sheet steel that forms the body of an automobile or an appliance is produced in many widths. A 60-inch piece may be needed for the hood, and a 40-
inch piece may be needed for a door panel. The mill that rolls these widths takes about the same amount of �me per foot regardless of width. Therefore, a mill with a heavy mix of
40-inch pieces will be able to produce fewer tons per hour than a mill with many 60-inch pieces. What is the capacity of the processing equipment, and what are the units of
capacity? Steel is measured in tons per hour, but those who es�mate capacity realize that capacity changes as the mix of steel changes because different products have different
produc�on rates. Therefore, product mix must be es�mated before capacity can be es�mated.

Problem

Assume that a company uses steel that is 1/8-inch thick and has a density of 0.2833 pounds per cubic inch. The machines roll steel for 80 hours per week at an average speed
of 30 inches per second. The company produces both 40- and 60-inch widths of steel and wants to determine the capacity of each of the following product mixes.

Size Mix 1 Mix 2

40 inches 80% 50%

60 inches 20% 50%

The company’s produc�on rate can be calculated as follows:

Produc�on rate (PR) = (produc�on rate for 40-inch)(mix for 40-inch) + (produc�on rate for 60-inch) (mix for 60-inch)

The produc�on rate for the 40-inch size (PR40) can be determined as follows:

PR40 = (width)(thickness)(processing rate inches/hour)(density)
     = (40 in)(1/8 in)(30 in/sec)(3,600 sec/hr)(0.2833 Ibs/cubic in)

     = 152,982 Ibs/hr

This would be the produc�on rate if only the 40-inch size were produced. Calculate the produc�on rate for the 60-inch size, which is 229,473 pounds per hour.

Now calculate the overall produc�on rate if Mix 1 is assumed.

PR = (152,982 Ibs/hr)(0.8) + (229,473 lbs/hr)(0.2)

   = 122,385.6 lbs/hr + 45,894.6 lbs/hr

   = 168,280.2 Ibs/hr

Convert this figure to tons per hour.
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Labor Rela�ons; CNBC Titans: Procter and Gamble

Next, convert the produc�on rate into an es�mate of capacity for a week.

Capacity for Mix 1 = (PR of mix 1)(hours worked)

= (84.14 tons/hr)(80 hrs/week)

= 6,731.2 tons/week

Calculate the capacity if Mix 2 is assumed, which is 7,649.1 tons per week. Thus, as the mix shi�s from 40-inch to 60-inch steel, the capacity increases. Capacity is influenced by
product mix.

Adding People

Adding people to an opera�on may increase the maximum produc�on rate. This increase occurs when the opera�on is constrained by the amount of labor assigned to the job. The
capacity of both service opera�ons and manufacturing opera�ons is affected by adding or elimina�ng people. Organiza�ons that are successful need to be willing and able to adapt
to change. Part of being able to adapt is having flexibility to meet changes in demand. The following example illustrates the flexibility available to an organiza�on in mee�ng varying
levels of demand.

Problem

To assemble the frames for 25 rocker/recliner chairs, each assembler takes his or her work order to the inventory clerk to pick the parts required to make the chairs. This takes
about 30 minutes. A�er returning to the work area, each assembler completes 25 chair frames in 3 1/2 hours. To increase the capacity to assemble chair frames, a separate
stock picker could be hired to gather inventory for all the assemblers. Then each assembler would be able to increase produc�on by 1/7 because the 30 minutes consumed in
stock picking could now be used to assemble chairs. Therefore, each assembler could assemble for 4 hours rather than 3 1/2 hours. One stock picker could serve eight
assemblers. The capacity improvement is calculated here.

Increasing Motivation

Another way to increase the produc�on rate for an opera�on with labor constraints is to increase mo�va�on.
Substan�al increases in produc�on rates can be achieved when workers feel they are an important part of the
opera�on. These produc�vity increases do not require addi�onal labor costs or extra investment in equipment.
The people work harder to accomplish more when they have an emo�onal or financial stake in the
organiza�on.

There has been a growing awareness among both management and labor that communica�on and coopera�on
offer be�er opportuni�es for success than sharp-tongued rhetoric, lockouts, and strikes. Evidence of this
willingness to cooperate exists in almost every industry as organiza�ons fight for market share and workers fight
for jobs in the increasingly global environment. In the automo�ve industry, labor has agreed to liberalize work
rules so that produc�vity can be increased. For example, some facili�es have reduced the number of job
classifica�ons from 100 to only a few, making it possible to perform simple maintenance tasks with one or two
employees rather than five or six. Management has agreed to profit sharing, which allows the workforce to
share in the benefits of these simplified work rules. Management has also begun to recognize the talents of its
labor force and has encouraged employee involvement in what used to be exclusively management domain:
decision making.

Labor is learning to accept efforts to improve automa�on because workers see that cu�ng costs and enhancing
quality can lead to the best kind of job security, that is, increasing sales. Shared decision-making has not only
caused increased coopera�on, but it has created more mo�vated employees, thus providing the following
benefits to organiza�ons:

Organiza�ons can tap into talent that already exists in their workforce.
Workforces are more recep�ve to training and new ideas.
People work harder and smarter.

Increasing Machine Production Rate

In an opera�on that is machine constrained, adding people will not increase capacity. Machine constrained means that the equipment is opera�ng for all the available �me at its
best speed, while the operators have some idle �me. For example, if a pizza oven can bake 40 pies per hour, and the staff can assemble 60 pies per hour, then the process is
machine constrained. To increase capacity, either new machines should be purchased or exis�ng machines should be operated more efficiently.

One possibility that was men�oned earlier is to increase preven�ve maintenance so that down�me due to machine failure will be reduced or eliminated. Another approach is to
develop procedures that more efficiently u�lize exis�ng machines. With con�nuing process improvements there is usually a way to improve a machine’s produc�on rate. A
procedure could be as simple as finding a faster and be�er way to load pizzas into the oven or increasing the heat in the oven to cook pizzas faster.

Improving Quality

Labor
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A pizza oven is an example of a machine constraint. To increase capacity, new machines must be
purchased or exis�ng machines must be operated more efficiently.

©iStockphoto/Thinkstock

When filming a movie, a director o�en shoots excess footage and then
edits it, removing scenes to create the final version of the film. An
increase in yield would mean shoo�ng less “extra” footage.

Comstock Images/Thinkstock

Improving quality can o�en increase the capacity of opera�ons. Simply stated, if an
opera�on produces a product of inferior quality and the product is rejected, the
capacity used to produce that product is wasted. Poor quality gives the
organiza�on’s customers a bad impression of its product, and also robs opera�ons
of needed capacity. Consider the following case.

Real World Scenarios: Downey Carpet Cleaning

Downey Carpet Cleaning is a family-owned business that cleans carpets, furniture, and drapery. It also performs general housekeeping services. For several years, Downey has
offered a carpet service that thoroughly cleans high-traffic areas at one low price although some compe�tors charge extra for high-traffic areas. Why should Downey charge the
lower rate? According to the owner, who is also the manager, it is a sound business decision.

A callback to clean a carpet a second �me for a dissa�sfied customer takes as much �me as making two regular carpet-cleaning stops because regular stops are scheduled to
avoid as much nonproduc�ve travel �me as possible. Callbacks o�en require much longer drives. Each callback robs Downey of capacity and addi�onal poten�al revenue.
Compara�vely, the extra �me and money for the chemicals needed to clean the high-traffic areas right the first �me are small.

The typical carpet-cleaning worker can perform 10 jobs per day with an average revenue of $43 per job. One callback for which the company receives no addi�onal revenue
causes Downey to lose $86 in revenue. The company misses out on two regular jobs at $43 per job. Plus, the out-of-pocket costs for the chemicals to clean the carpet a second
�me, and the costs of opera�ng the truck for the return trip are incurred. In one day, the extra costs of the chemicals, and the �me for the worker to complete all 10 jobs
correctly the first �me is less than $20. By avoiding callbacks, Downey is able to increase its capacity. In addi�on to a sound financial policy, customers also like the policy and
frequently have Downey return for other services as well as for their next carpet cleaning.

Increasing Product Yield

In many opera�ons, the quan�ty of output is less than the quan�ty of input. In other words, some inputs are lost
during the produc�on of a good or service. Yield is the ra�o of the quan�ty of output to the input quan�ty.

Yield is a func�on of the characteris�cs of the process for producing the product. For example, an oil refinery
begins with one barrel of crude oil, but when it is finished, there is less than one barrel of finished product. Small
amounts evaporate, are spilled, or are otherwise lost in the produc�on process. Some is burned as waste gas. The
yield is the percentage of the output that is a useful product. A 96% yield means 96 of every 100 barrels of input
are made into useful products. If a refinery’s engineers find methods to increase the yield by 1%, the refinery will
have more product to sell, which increases effec�ve capacity. Making movies follows a similar process. A director
may shoot eight hours of film but may edit the film so that the final movie is two hours or less. The extra �me
used to shoot the movie costs money and prevents using the actors, sound stage, loca�ons, cameras, and
equipment to make other movies. Increasing yield would mean shoo�ng less than eight hours of film to make the
two-hour movie.

Highlight: Intel and Computer Chips

A�er Intel introduces new computer chips, it usually experiences a drama�c improvement in yield during produc�on. Ini�ally, the number of chips that meet standards may be
only 60%. As the company learns more about the process, the yield may increase to 90% or more. This 30-point increase in yield leads to 50% more product to sell. (Previously
only 60 of 100 chips could be sold. Now 90 chips, that is, 30 more, are available.) Thus, capacity is increased. Because these 30 addi�onal chips add no produc�on cost, most
of the revenue from their sale contributes directly to the company’s bo�om line. For Intel, moving up the yield curve as quickly as possible has a substan�al impact on mee�ng
customer demand and on increasing profitability.

Points to Consider

Capacity es�ma�on is a necessary prerequisite to capacity planning. Without knowledge of the exis�ng limits on capacity, meaningful capacity planning or produc�on planning
cannot take place. As the earlier sec�on indicates, capacity is not a fixed number. Capacity is a func�on of management ingenuity. It can be influenced by good planning, goodProcessing math: 0%

opera�ng procedures, effec�ve maintenance programs, and other management decisions. One of the important responsibili�es of opera�ons managers is to inves�gate ways to
increase capacity before inves�ng substan�al capital in new facili�es.

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8.3 Determining System Capacity

Un�l this point, the discussion of es�ma�ng and improving capacity has focused on only one machine or one opera�on within a company. The reality is that opera�ons are a
combina�on of different machines, equipment, and processes that make finished products. To plan effec�vely, management must know the capacity of the en�re produc�on system,
not just the capacity of individual parts. System capacity is the ability of the organiza�on to produce a sufficient number of goods and services to meet the demands of customers.
The capacity of an insurance company is not dependent only on the capacity of its sales personnel, the capacity of a hospital is not set only by the number of surgery rooms, and
the capacity of a pizza parlor is not determined only by the capacity of its ovens.

For convenience, the term department is used when referring to a por�on of the produc�on system. To analyze system capacity, it is important to determine how departments are
related. The two basic arrangements, product layout and process layout, are discussed in Chapter 7 and are also used here.

Product Layout

Product-oriented layout is characterized by high demand for the same or similar products. Examples include refining steel, making paper, and processing checks in a bank. In this
arrangement, there are few, if any, product varia�ons, and the layout fits the dominant flow of the product—thus, the name “product layout.”

For example, to make paper, wooden logs are ground and chemically treated to produce a watery mixture called pulp. The pulp is pumped to the papermaking machine where
excess water is gradually squeezed out, leaving a thin sheet of wet paper. The wet paper passes through a series of dryers that remove most of the remaining moisture. The paper is
then rolled into logs that can be 30 feet wide and several feet in diameter. These huge logs are later cut into many different widths. Most types of paper are made using the same
process and follow the same flow (see Figure 8.1).

Figure 8.1: Product-oriented layout of paper mill

Process Layout

Process-oriented layout is characterized by the produc�on of many different products with the same equipment and low volume of any individual product. No single product has
enough volume to support a dedicated set of machines. Each product has different produc�on requirements that place different demands on the equipment. Examples include a
machine shop that produces specialty automo�ve parts for racing engines, a hospital emergency room, and an automo�ve repair shop that offers a wide variety of services. In this
arrangement, the layout is grouped by similar machine types because there is no dominant product flow—thus the name “process layout.”

An automo�ve center contains the equipment to analyze a variety of mechanical problems. As seen in the following list, different customers desire a different set of services. The
facili�es are arranged by process because there is no dominant flow (see Figure 8.2).

Figure 8.2: Process-oriented layout of an automo�ve service
center

Customer Services Requested

A Tires, shock absorbers, wheel alignment

B Tires, brakes, tune-up

C Brakes, tune-up, exhaust system

D Tires, brakes, shock absorbers, muffler

E Shock absorbers

The capacity of the product-oriented and process-oriented layouts is determined by analyzing the capacity of individual departments. Approaches to determining the capacity of
both layouts are discussed next.

Product Layout and System Capacity

The capacity of a product-oriented system can be visualized as a series of pipes of varying capacity, with the smallest diameter or capacity holding back the en�re system. Figure 8.3
shows five pipes (departments or machines) with different diameters (capaci�es). The output from one pipe becomes the input to the next un�l the finished product exits pipe
number five. In Figure 8.3, pipe number two cannot handle all the flow that pipe number one can deliver and, therefore, it restricts the flow. Because of pipe number two’s limited

Processing math: 0%

capacity, it restricts the flow from upstream pipes and starves the downstream pipes. Pipes three, four, and five can work on only what pipe two can deliver. This restric�on is called
a bo�leneck, and it determines the system’s capacity.

Figure 8.3: A bo�leneck in the product flow

Analysis of System Capacity

In a product-oriented layout, iden�fying the bo�leneck is cri�cal. The importance of this analysis cannot be overstated because the results are used not only in determining capacity,
but also in planning and scheduling produc�on, which are discussed later in the book.

The approach to determining the bo�leneck is illustrated in Figure 8.4. Start at the beginning of the system, and determine the capacity of the first opera�on or department. This is
the system capacity so far. Use this capacity as the input to the next department in the sequence. Can that department take the total input from the previous department and
process it completely? If it can, then the system capacity has not changed. If it cannot, then the system capacity is reduced to the capacity of that department. The procedure
con�nues un�l the end of the process is reached and the system capacity is known.

Figure 8.4: A sequen�al approach to bo�leneck
analysis

Consider the example shown in Figure 8.5. The basic oxygen furnace has a maximum rate of 4,200 tons per day (tpd), while the con�nuous caster’s rate is 6,000 tpd. According to
the example, the capacity of that part of the system is limited by the capacity of the slower department.

Figure 8.5: Simple steel produc�on flow

Determining the Bo�leneck

Now consider the en�re system for making steel shown in Figure 8.6. The capacity of a department is listed below the department name. At two points in the steel-making process,
outputs from two departments are inputs to a single department. The ra�o of each input is listed above the arrow that illustrates the flow. For example, in the blast furnace, three
pounds of iron ore are mixed with one pound of coke. This is like a recipe for a cake, three cups of flour to one cup of sugar, or three parts gin and one part vermouth for a mar�ni.
The capacity to mix mar�nis depends on both gin and vermouth. To supply the blast furnace with what it needs, iron ore and coke oven output should be combined in the correct
propor�on un�l at least one of these inputs is exhausted or un�l the capacity of the blast furnace is completely consumed.Processing math: 0%

Figure 8.6: Steel produc�on flow: a product layout

What is the system capacity? Follow along in Figure 8.6. Iron ore processing and coke ovens can deliver 3,000 and 1,000 tpd, respec�vely. (Only 3,000 tons can be used from iron
ore processing because of the ra�o requirements.) The combined 4,000 tpd is more than sufficient for the blast furnace, which can process only 3,000 tpd total. So far, the blast
furnace is holding back produc�on. The blast furnace and scrap handling, in turn, supply 3,000 and 1,500 tpd, which is more than adequate for the basic oxygen furnace capacity of
4,200 tpd. Because the basic oxygen furnace cannot process all available inputs, the blast furnace cannot be the bo�leneck. The basic oxygen furnace cannot deliver sufficient
output to the remaining departments. Therefore, the basic oxygen furnace is the bo�leneck for the system, and the capacity of the system is 4,200 tpd.

To calculate the produc�on rates that allow the system to produce 4,200 tpd, begin at the bo�leneck department in Figure 8.7. Trace the product flow from the bo�leneck to the
beginning and the end of the process. In order to achieve 4,200 tpd of basic oxygen furnace input, (2/3)(4,200) = 2,800 tpd comes from the blast furnace and (1/3)(4,200) = 1,400
tpd comes from scrap. The requirements are listed above each department. The blast furnace requires (3/4)(2,800) = 2,100 tpd of iron ore and (1/4)(2,800) = 700 tpd of coke.
Moving from the basic oxygen furnace to the end of the process is simpler because there are no pairs of departments. The requirement for those departments is 4,200 tpd. When
making steel, each opera�on in this process would suffer a yield loss, which is not considered here in order to simplify discussion.

Figure 8.7: Determining system capacity

Rounding Out System Capacity

It is also important to know which department, machine, or step in the process restricts the system’s capacity. An opera�ons manager may be charged with increasing the system’s
capacity. If he or she tries to do so by increasing blast furnace capacity, there will be no increase in the system’s capacity. This organiza�on could spend hundreds of millions of
dollars on a new blast furnace without producing one addi�onal ton of steel because the bo�leneck constricts the flow, and the bo�leneck is the basic oxygen furnace.

The system capacity can be increased by applying resources to the bo�leneck department. This approach is called rounding out capacity because resources are applied to the
bo�leneck to bring it into balance with other parts (departments) in the system. Rounding out capacity has a limit, however. Simply stated, if the opera�ons manager doubles basic
oxygen furnace capacity because it is the bo�leneck, the system’s capacity will not double.

There is not enough capacity in other departments to absorb that large an increase. As a result of doubling basic oxygen furnace capacity, the bo�leneck simply jumps to another
department. Managers should understand this issue and carefully analyze the effect on the system when departmental capacity is increased.

An important and useful piece of informa�on is how far the system’s capacity can be increased before another bo�leneck appears. To answer this ques�on, examine the
requirements listed above each department in Figure 8.7. A quick review shows that scrap handling and the blast furnace will be bo�lenecks as basic oxygen furnace capacity is
increased. With a cushion of 100 tons per day in scrap handling, the capacity of the system could increase by only 300 tpd. (Remember that one part scrap and two parts hot metal
from the blast furnace are required.) The scrap handling and blast furnace departments have insufficient capacity to handle an increase of more than 300 tpd in basic oxygen
furnace capacity.

Another way of thinking about it is to simply set the capacity of the present bo�leneck to infinity and rework the problem. The results are shown in Figure 8.8. The system’s
capacity is 4,500 tpd. There are two bo�lenecks: blast furnace and scrap handling. Remember, the basic oxygen furnace capacity was set to infinity. It actually does not need to be
infinitely large, but it must be 4,500 tpd or more if the system capacity is 4,500 tpd.

The analysis of system capacity and associated bo�lenecks is extremely important to determine capacity. Ra�onal decisions about capacity can be made only if these concepts are
fully understood.

Figure 8.8: Rounding out capacityProcessing math: 0%

Process Layout and System Capacity

The process-oriented layout is characterized as a mul�ple-product facility with low volume per product. The products are different from one another and usually require different
methods and procedures in produc�on. There is no dominant product flow to guide the arrangement of departments as there is in the paper or steel industry, so similar opera�ons
are grouped together. The process-oriented layout does not have enough volume in any one product to require dedicated specialized produc�on facili�es.

A medical center is an example of a process-oriented opera�on. Pa�ents are screened at the recep�on desk to determine the nature and seriousness of their injuries, and then
proceed to a wai�ng room to be called by a nurse or physician. A�er an ini�al examina�on, the method of treatment for each pa�ent is determined. Each treatment could be
different and is based on the pa�ent’s individual needs. A pa�ent in an automobile accident may be scheduled for X-rays, orthopedic surgery, and applica�on of a cast. The next
pa�ent may have heart problems. Each follows a different path through the medical center. The equipment should be flexible enough to handle a wide range of needs. For example,
X-ray machines can provide images of legs, feet, hands, and other areas of the body.

Analysis of System Capacity

Determining system capacity in a process-oriented layout is more complex than doing so in a product-oriented layout. In the process layout, each product does not follow the same
path through the system. The func�ons and machines are grouped into departments, and different products follow different paths. The layout shown in Figure 8.9 has six
departments and four different pa�erns of treatment or products. The departments’ capaci�es are given in pa�ents per week (ppw) and are based on average �me per treatment.

Figure 8.9: A process layout of a medical center

System capacity is not merely a search for the minimum department capacity because there is no dominant flow. The capacity of the system is a func�on of the jobs presented. If
the medical center only processed one type of pa�ent, the system capacity could be easily and accurately es�mated. If all the pa�ents arriving at the medical center are type-A
pa�ents (those needing orthopedic care), the capacity of the system will be 250 pa�ents per week. In the very specific and highly specialized case, the analysis is like that of a
product layout. This is completed by finding the minimum capacity for departments 1, 2, and 3. If all pa�ents are of type B, then the capacity will be 500 pa�ents per week. For
pa�ents of types C and D, the system capaci�es are 300 and 400 pa�ents per week, respec�vely. The following table shows the various capaci�es if all of the pa�ents in one week
were a single type. This is not likely to occur, so the system’s capacity is a func�on of the job types presented. This is called the product mix or, in this case, pa�ent mix.

Mix System’s Capacity Bo�leneck Department

100% A pa�ents 250 ppw Orthopedic care

100% B pa�ents 500 ppw Cardiology

100% C pa�ents 300 ppw Neurology

100% D pa�ents 400 ppw X-ray

Product Mix and Capacity in a Process Layout

What would the system capacity be if the medical center processed all four types during the same week? To simplify the problem, assume that only type A pa�ents arrive on
Monday and Tuesday, type B on Wednesday and Thursday, type C on Friday and Saturday, and type D on Sunday. The system capacity per week for that mix would be calculated as
follows:

Processing math: 0%

Services cannot be inventoried and are typically produced and consumed simultaneously.
Consequently, service organiza�ons must effec�vely manage demand. Although it is not the most
efficient method, allowing long wai�ng lines to occur is one way to manage demand.

©Klaus Lahnstein/Stone/Ge�y Images

The frac�ons in the preceding equa�on are the pa�ent mix. A different assump�on concerning the number of days per week assigned to each pa�ent type would cause a different
product mix and would result in a different system capacity.

In reality, not all orthopedic care pa�ents (type A) will arrive on Monday and Tuesday. The method illustrated in the prior calcula�on is likely to underes�mate the system capacity
because we have assumed that no pa�ent other than an orthopedic pa�ent arrives on Monday or Tuesday. However, the system does have the capacity to process type B, C, and D
pa�ents on Monday and Tuesday in addi�on to (2/7) (250 ppw) = 71.4 type A pa�ents. How can managers of a medical center get an accurate es�mate of system capacity and
determine which department is the bo�leneck? An o�en-used technique for es�ma�ng capacity in a process layout is simula�on.

In this approach, an es�mate of product mix (pa�ent mix) is used to randomly generate arriving pa�ents. The �me to service each pa�ent is based on historical data, and is also
randomly generated. The simula�on is run for a long period of �me, and sta�s�cs about the number of pa�ents served and the use of each department are kept. U�liza�on data
should be kept regularly for equipment in a process layout so that bo�lenecks can be an�cipated and correc�ve ac�on taken. Management can change the mix of arriving pa�ents
in the simula�on to determine how the system capacity and bo�leneck department change. A different mix places different demands on the resources. Managers should plan for
the present mix of pa�ents and the associated bo�leneck, as well as for the mix of possibili�es that the future holds.

Capacity Decisions for Service Operations

Most of the concepts discussed in this text apply to producers of services and producers of goods. It is important to note, however, that service opera�ons are different from
manufacturing opera�ons in some aspects. First, services are direct and cannot be inventoried. Whereas the consump�on of goods can be delayed, the general rule is that services
are produced and consumed simultaneously. This means that service organiza�ons must (1) build enough capacity to meet maximum demand, (2) manage demand so that people
will use the services at off-peak �mes (allowing long wai�ng lines to occur is one way, albeit a poor way, to manage demand, and offering monetary incen�ves to use the service at
off peak �mes is another way), or (3) choose not to sa�sfy all the demand.

Each of these op�ons has a cost. Building sufficient capacity to meet maximum demand
can mean that a significant por�on of the capacity is used infrequently. This can mean
large capital expenditures with limited return on investment. People who must wait in
long lines for service may become dissa�sfied, and that will result in a loss of business.
For example, a hospital that has long lines in its emergency room is likely to lose
business to another emergency room that is be�er organized and has a shorter wait
�me. Choosing to ignore demand means a loss of customers that may have both short-
and long-term effects.

Second, there is o�en a high degree of producer-consumer interac�on during the
produc�on of a service. This interac�on frequently introduces a significant amount of
uncertainty about processing �me, and processing �me is a determinant of capacity. For
example, a person wai�ng in line at a bank may have one or many transac�ons to
perform and may be skilled or unskilled at communica�ng his or her needs. This
varia�on makes it more difficult to es�mate the capacity required to meet customer
demands.

Third, many services are not transported to the customer, so the customer must come
to the service delivery system. This has important implica�ons for the loca�on decision.
It also means that capacity decisions should result in adequate space for the customer
in the service delivery system. For example, many restaurants use a generous bar area
to deal with excess demand in the dining area.

Service Operations and System Capacity

Despite differences, determining system capacity and finding where a bo�leneck occurs applies to service as well as manufacturing opera�ons. The principles are the same, but in
some cases the applica�on is different. In the following case, managers of an upscale restaurant chain are a�emp�ng to determine the capacity of their restaurant.

Problem

The flow of people through the restaurant follows this sequence. People arrive at the restaurant and park their cars. According to the records that the restaurant keeps, 20% of
the guests spend �me in the bar. The remaining 80% of the arrivals go directly to the dining area.

According to standards that management has developed over the years, each dinner served per hour requires approximately four square feet of kitchen space. Listed below are
the resources of the restaurant:

Department/Area Capacity/Size

Parking area 100 spaces

Bar area 80 seats

Dining area 200 seats

Cooking area 600 square feet

On average, 2.2 people arrive per car, only 80% of the seats in the bar are normally available because tables for four are some�mes occupied by two or three people, and only
85% of the dining area seats are normally available for the same reason. The average stay is 90 minutes. Everyone in the dining area orders a meal, and 40% of the people in

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the bar area order a meal. What is the capacity of the system? To begin, the capacity of each area can be calculated in terms of persons served per hour.

Department/Area Capacity/Size

Parking area (100 spaces)(2.2 people/car)/(1.5 hrs.) = 147 people/hr.

Bar area (80 seats) (0.8)/(1.5 hrs.) = 43 people/hr.

Dining area (200 seats)(0.85)/(1.5 hrs.) = 113 people/hr.

Cooking area (600 square feet)/(4 square feet/meal) = 150 people/hr.

If every customer spent �me both in the bar and in the dining area, the system capacity would be easy to determine because each customer would place demands on each
area. This would make the restaurant product layout similar to the steel industry, and the system capacity would be the smallest of the four department’s capaci�es. However,
only a por�on of the guests use both the bar and the dining areas.

To calculate the capacity of the system and determine the bo�leneck department in this case, the approach illustrated in the medical center example men�oned earlier could
be used. That method requires tracking two different flows: one involving the dining area and a second following the bar area. The process begins by selec�ng a level of
demand that the restaurant can sa�sfy. If it cannot, the demand level is decreased, and another a�empt is made. If it can, the demand level is increased. This trial and error
method can quickly lead to the capacity if care is used in selec�ng the demand targets. This trial and error approach could also be used to solve problems, such as the steel
industry problem described earlier. Inspec�ng the department capaci�es indicates that the system’s capacity cannot exceed 147 people per hour because that is the capacity of
the parking lot, and the assump�on of this model is that all patrons drive. It is also clear that the capacity of the system is at least 100 because all of the department
capaci�es are at least 100, except for the bar area which only serves 20% of the customers.

Therefore, the trial and error process begins by se�ng the arrival rate (demand) equal to 100 people per hour. This means that during each hour 100 people use the parking
lot, 20 people use the bar, 80 people use the dining area, and 88 people order a meal. People in the bar that order a meal eat the meal in the bar. None of the individual
departments is at capacity, so the analysis con�nues. The results are shown in the following table:

Set Demand Equal To

Department Area Capacity (People/ Hr.) 100 (People/ Hr.) 125 (People/ Hr.) 147 (People/ Hr.) 113/0.8 = 141 (People/Hr.)

Parking area 147 100 125 147 141

Bar area 43 20 25 29 28

Dining area 113 80 100 118 113

Cooking area 150 88 110 130 124

Next, what happens if demand is set at 125 people/hour? Assume again that none of the departments is at capacity. As a result, the system capacity must be between 125 and
147 people/hour because the parking lot can hold no more than 147. With demand set at 147 people/hour, the parking lot is at capacity, but demand in the dining area
exceeds capacity. Bar demand is equal to (147) (0.2) = 29. Dining demand is equal to (147)(0.8) = 118. Cooking demand is equal to 118 + (29)(0.4) = 130. At this point, the
bo�leneck is the dining area, but the system capacity is not clear because only some use the dining room. To determine the system capacity, divide the capacity of the dining
area by 0.8, which is the percentage of customers that use the dining area. This calcula�on yields the system capacity, which is 141 people per hour. If the system capacity is
set equal to demand and the department demands are calculated again, the excess capaci�es in the non-bo�leneck departments can be iden�fied. There is considerable excess
capacity in the cooking area and in the bar, but the parking lot is near capacity. Expansion plans, if jus�fied by demand, should be aimed at the dining area and the parking lot.

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8.4 Making Capacity Decisions for Competitive Advantage

Informed capacity decisions can be made only when management: (1) knows the ability of its present resources, which is achieved by accurately es�ma�ng system capacity; (2)
knows the bo�lenecks and what is causing them; and (3) has an es�mate of future demand. The first two topics have been the focus of the chapter to this point. Es�ma�ng
demand is discussed in the chapter on forecas�ng. Now, this informa�on can be used to discuss the capacity decisions listed below:

When to add capacity.
How much capacity to add.
Where to add capacity.
What type of capacity to add.

When to Add Capacity

Many managers argue that determining how much capacity an organiza�on requires should not be difficult. The real problem is obtaining an accurate forecast of demand. These
managers believe that once an es�mate of demand is obtained, it is simply a ma�er of se�ng capacity to meet demand. With knowledge of the point at which demand equals
capacity, and an es�mate of how long it takes to build addi�onal capacity, management subtracts the lead �me to determine when to begin construc�on. In Figure 8.10, capacity is
exceeded two years in the future. If it takes 18 months to add capacity, then management should begin construc�on six months from today; however, the answer is not that simple.
To avoid compounding the ques�on of when to add capacity with forecas�ng error, assume that forecasts are guaranteed to be accurate.

As management considers the �ming decision in Figure 8.10, it should ask the following ques�on: should the capacity be added by the end of the second year? The answer is
probably no, for several sound reasons. Management could simply choose not to sa�sfy all of the demand during the third year. The forecast shows that the significant and long-
term increase does not take place un�l the end of year five. It is possible that the organiza�on has no long-term interest in the market and would choose to allocate resources to
other product. On the other hand, failing to fully sa�sfy demand may not be consistent with a company policy of building market share. If the sales force is asked to increase market
share, but opera�ons cannot deliver the product, then long-term damage to the firm’s reputa�on could result.

Figure 8.10: Capacity versus demand

If ignoring the excess demand in the third year is not acceptable, then management must find a way to meet that demand. One possibility is to set the produc�on rate higher than
demand during the first and second years so that sufficient inventory is created to sa�sfy demand in the third year. Figure 8.11 illustrates this point. Obviously, this solu�on is
limited to goods produc�on because services have no finished goods inventory.

Figure 8.11: Capacity, demand, and produc�on rate

Other methods of dealing with the capacity shor�all in the third year can be understood by recalling the earlier sec�ons on capacity es�ma�on. Capacity is a variable that is subject
to change through management innova�on. If the opera�on runs two shi�s five days per week, then over�me or another shi� could be considered. Be�er scheduling, improved

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opera�ng procedures, or improved quality of raw materials can increase capacity. Another important concept to remember is system level capacity. To increase the capacity of a
system, it is necessary to increase the capacity of only the bo�leneck opera�on. It may be possible to buy produc�on capacity to supplement the bo�leneck opera�on and increase
overall capacity.

How Much Capacity to Add

If addi�onal capacity is built, how much should be added? Again, assuming that the forecasted demand is accurate, consider the example in Figure 8.12 when deciding how much
capacity to add. In this example, the decision concerning when to add capacity has been made. Construc�on begins in the middle of the third year, and the new capacity will come
on line at the end of the fourth year.

Figure 8.12: How much capacity to add

Op�on 1 adds only enough capacity to handle the demand in the early part of the fi�h year. Op�on 2 adds enough capacity to handle the increase in the sixth year. Whether
Op�on 1 or Op�on 2 is selected, the company should understand the importance of focusing on the bo�leneck to increase system capacity. The financial versus opera�ng tradeoffs
of these op�ons are summarized here.

Advantages of Op�on 1

1. Limits short-term investment and risk. Changes in technology will not find the organiza�on with as much capital �ed up in outdated technology.
2. Limits unused capacity for which no return on investment is provided.

Advantages of Op�on 2

1. May reduce long-term investment. Building capacity at one �me instead of mul�ple �mes can help save on total construc�on costs.
2. May reduce infla�onary effects on construc�on costs by building now.

The primary ques�ons associated with Op�on 2 are:

How long will it be before the capacity is needed?
How likely is it that the forecasted need will occur?
How stable is the technology?

A firm producing products in an industry where the product or process technology is likely to change does not want to build plants that limit its long-term ability to compete.

The decisions about when to add capacity and how much capacity to add are cri�cal capacity decisions that are complicated by the uncertainty in the es�mates of future demand.
Decision theory, which uses sta�s�cs and probability theory, can be used to model these decisions when forecasts are uncertain.

Where to Add Capacity

The decision on where to add capacity (usually called the loca�on decision) is complex and involves many factors. It is strategically important because it commits significant
resources to a loca�on. Great care and considera�on should be given to the long-term implica�ons. The loca�on decision is addressed in another chapter.

What Type of Capacity to Add

In addi�on to determining how much capacity to add and when to add it, management should consider what type of capacity to add. Type of capacity can be separated into a
technological or engineering ques�on and an economy of scale or business ques�on. These topics are the focus of Chapter 7.

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Chapter Summary

Capacity is a measure of an organiza�on’s ability to provide customers with demanded services and goods in the amount requested and in a �mely manner.
Capacity decisions are cri�cal to an organiza�on’s success because they commit significant resources to assets that usually cannot be changed easily or economically. Capacity
decisions should be based on the best es�mate of the future and should be made so that as much flexibility as possible is retained.
Capacity should also be obtained in the proper amount. Too much capacity means that money has been invested in resources that are not really needed. Too li�le means that
poten�al sales and market share are lost.
Es�ma�ng an organiza�on’s capacity is not easy because capacity is affected by management decisions regarding changing the number of hours worked, changing the product
mix, adding staff, improving worker mo�va�on, improving machine capabili�es, enhancing quality, and increasing product yield.
Machine and departmental capaci�es are needed to determine the capacity of the system. The capacity of a system can only be as much as its slowest department, which is the
bo�leneck.
An increase in system capacity can be achieved by increasing capacity in the bo�leneck department. This is called rounding out capacity.
Capacity decisions include the following: when to add capacity, how much capacity to add, where to add capacity, what type of capacity to add, and when to reduce capacity.

Case Study

Beck Manufacturing

Al Beck, president of Beck manufacturing, wants to determine the capacity of his facility, which produces steering gears for auto manufacturers. He has asked you to sort through
the data and determine the capacity of the system and how that capacity may be increased. The opera�on is a product layout that produces large numbers of nearly iden�cal
products. The process includes milling, grinding, boring, drilling, and assembling, in that order. Each finished product requires one opera�on on each type of machine. For example,
each finished part is processed on one of the five milling machines, one of the seven grinding machines, etc.

The facility runs two 8-hour shi�s per day, with a third shi� for maintenance. The industrial engineering department has provided you with the following data on present opera�ons.
In addi�on, you have been told that assembly opera�ons, while not unlimited, can be easily changed to meet the need.

Opera�on Number of Machines Run Time per Piece (min.) % Reject Rate
Milling 5 2 3
Grinding 7 3 5
Boring 3 1 2
Drilling 6 2.5 7

1. Calculate the capacity of each machine center and the capacity of the system.
2. If Beck wants to expand capacity, where should he focus the company’s efforts? How much extra capacity can he get without causing another opera�on to become the bo�leneck?
3. How may Mr. Beck expand capacity without purchasing new equipment? Be specific.

Discussion Ques�ons

Click on each ques�on to reveal the answer.

1. What is capacity, and why is it important?
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Capacity is a measure of the organiza�on’s ability to provide customers with the demanded goods or services in the amount requested and in a �mely manner. More
specifically, capacity is the maximum rate of produc�on. Capacity for any period of �me such as a week, a month, or a year can be determined by mul�plying the maximum
hourly produc�on rate by the number of hours worked during the period. As noted in the text, many assump�ons are required to support this calcula�on and great care should
be used when interpre�ng the result.

Decisions to alter capacity are important to an organiza�on because significant capital outlays are generally required to build capacity. Also, the physical facility is o�en a key
resource in an organiza�on’s efforts to remain compe��ve.

2. Why is it difficult to es�mate capacity? Is capacity a constant? Why or why not?
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At first glance, es�ma�ng capacity appears to be nothing more than determining the maximum rate per hour for produc�on equipment, determining the number of hours
worked in a given �me period, and mul�plying the two numbers. Capacity is not a constant. It is a variable, which is a func�on of management decisions. In most organiza�ons,
managers can decrease the number of hours worked by shortening the work week as well as increase the number of hours worked through over�me or addi�onal shi�s.
Management can also control the number of hours worked in subtler ways. A properly designed preven�ve maintenance program can reduce equipment failures.

In addi�on to the fact that hours can change, capacity is difficult to measure because the produc�on rate is influenced by management decisions. For example, capacity can be
increased by assigning addi�onal people to certain tasks, providing people with be�er tools, and improving procedures and methods for doing work.

3. Should an organiza�on always a�empt to match its capacity to its es�mate of demand? Why or why not?
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Capacity decisions should be based on the organiza�on’s best es�mate of demand. While it is not necessary to exactly match capacity with demand, too much capacity is
damaging to the firm, because funds are invested in resources that are not really needed and could have been be�er commi�ed elsewhere. Too li�le capacity means that
poten�al sales and market share are being lost. Management of an organiza�on may have good reasons for absorbing the costs of unused capacity or suffering the costs of lost
sales. For example, management may an�cipate that sales will increase drama�cally within one or two years and they prepare for it by maintaining some unused capacity
because they are unsure when the increase will occur. In another case, management may choose to phase out produc�on of a product or product line because they do not see
strong profits in the future.

4. Capacity decisions are strategically important. Agree or disagree with the statement, and support your posi�on.
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Capacity decisions are indeed strategically important. First, capacity is a measure of the organiza�on’s ability to provide its customers with the demanded goods or services in
the quan�ty demanded and in a �mely fashion. This has much to do with the organiza�on’s ability to execute its mission and achieve its objec�ves. Second, capacity decisions
effec�vely commit significant organiza�onal resources to long-term assets that cannot be easily or economically changed. These are resources, which undoubtedly have
opportunity costs a�ached.

5. What factors influence the capacity of an organiza�on? List three factors, and explain how they influence capacity.
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The mix of products produced by an organiza�on can influence capacity. Adding people to an opera�on may increase the maximum produc�on rate if the opera�on is
constrained by the labor input. Similarly, decreasing the labor input can reduce capacity. Another factor that influences capacity is the level of mo�va�on of employees.
Increasing mo�va�on can increase capacity, and if mo�va�on of employees slips, then capacity falls. Machine produc�on rate also influences capacity. In an opera�on that is
machine constrained, adding people will not increase capacity if machines are already being operated at the proper speed and for all the available �me. New machines can be
purchased or exis�ng machines can be operated more efficiently to increase capacity in this situa�on. Product quality, also, affects capacity. Improving quality will increase the
capacity of opera�ons, and allowing quality to slip will decrease capacity. If an organiza�on produces a product of inferior quality and the part is rejected, the capacity used to
produce the part has been wasted. Finally, product yield influences capacity. In virtually all opera�ons, the quan�ty of output is less than the quan�ty of input. Increasing or
decreasing yield, which is a ra�o of the quan�ty of output to the quan�ty of input, affects capacity.

6. Explain in detail the difference between departmental and system capacity.
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Departmental capacity is the capacity of a given opera�on. However, the system concept forces management to realize that opera�ons are a combina�on of departments,
machines, and processes which work together to create finished products. To be effec�ve, management must know the capacity of the whole system, not the capaci�es of its,
individual parts.

7. What are the principles for determining system capacity in the product layout?
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In a product layout with a dominant flow, a bo�leneck prevents preceding departments from moving products at top speed and starves departments that follow. Therefore,
determining the bo�leneck is essen�al to determining capacity. Moreover, it is important to know how far the system capacity can be increased before the next bo�leneck
appears. So, we see that the analysis of system capacity and associated bo�lenecks are essen�al for determining capacity, and it is only through understanding these concepts
that ra�onal decisions about capacity can be made.

8. What are the principles for determining system capacity in the process layout?
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In the process layout, each product does not follow the same path through the system. The search for system capacity is not a search for the minimum department capacity,
because there is no dominant flow. The capacity of the process system is a func�on of the jobs it must do. Capacity decisions and capacity planning in a process layout require
a forecast of the product mix.

9. How does a change in the product mix effect system capacity?
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An organiza�on has a product mix any �me it produces and sells more than one product. The product mix is the percent that each product is of the total number of units sold.
If each product produced by a company consumes the same amount per unit of a cri�cal resource, say labor, then the mix of products does not affect capacity. If one product
consumes more labor hours per unit than another, then the organiza�on will be able to produce less of the high resource-consuming product. If the product mix changes so
that an organiza�on is producing more of the high resource-consuming product and less of the low resource-consuming product, then the organiza�on’s capacity is lower. If the
product mix changes so that an organiza�on is producing more of the low resource-consuming product than the high resource-consuming product, then the organiza�on’s
capacity is higher.

10. What are the important decisions for capacity planners?
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Informed capacity decisions can only be made when the manager knows the present capacity, the bo�lenecks and their causes, and has an es�mate of future demand. With
this informa�on, the manager can work to make capacity decisions involving: 1) When to add capacity; 2) How much capacity to add; 3) Where the capacity should be added;
and 4) What type of capacity should be added? The final ques�on regarding type of capacity is also a process selec�on ques�on because it deals with the level and type of
automa�on.

11. What are the key factors that determine when to add capacity?
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Answering the ques�on of when to add capacity is not as simple as it may appear. Capacity is a variable, which is subject to change through management innova�on and
decision making. Adding another shi� or increasing over�me can increase capacity. Be�er scheduling or opera�ng procedures may increase capacity. Improved quality of raw
materials can increase capacity. Because management has the ability to increase capacity without building new facili�es, managers do not have to react by building new
facili�es each �me demand exceeds capacity. Managers need to build facili�es when they an�cipate that the increase in demand is for a long period of �me and the increase is
greater than can be met by the other less expensive alterna�ves described in the chapter.

12. What are the key factors that determine how much capacity to add?
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Once a firm has decided on when to add capacity, it is faced with the ques�on of how much capacity to build. There are many differently-sized facili�es that could be
considered. However, there are two approaches that should be considered. First, enough capacity could be added to meet immediate needs, that is one or two years. Second,
management could build more capacity than required in the next one to two years to meet long term demand and to protect against an unan�cipated increase in demand. If
management is to build the extra capacity it should consider these factors: 1) How long before the extra capacity is needed?; 2) How likely is it that the forecasts are accurate?;
3) How stable is the technology?; 4) If the demand does not materialize can the facility be easily converted to the produc�on of other products?

13. Why would an organiza�on want to reduce its capacity?
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Organiza�ons are faced with reducing capacity because demand for some products has declined, shi�ing capacity to another loca�on because of today’s highly compe��ve
global environment, and replacing exis�ng facili�es with new facili�es with newer technology and improved efficiency. In many cases, subs�tute products eliminate or greatly
reduce the demand for a product. For example, the introduc�on of computers and word processing so�ware has virtually eliminated the use of typewriters.

ProblemsProcessing math: 0%

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1. Determine the system capacity and the bo�leneck department in the following line flow process. The capaci�es in pieces per hour for departments A, B, and C are 5,250, 4,650, and
5,300, respec�vely.

2. Determine the system capacity and the bo�leneck department in the following line flow process. The capaci�es in tons per hour for departments A, B, C, and D are 2,200, 1,100,
1,600, and 2,500, respec�vely. For each ton of output from depart�ment B that is input to department D, two tons from department C must be added.

3. Answer the following ques�ons using the informa�on in Problem 2:
a. How much can the system capacity be increased by adding capacity to the bo�leneck department?
b. How much capacity must be added to the bo�leneck department to achieve this increase in system capacity?
c. Which department is the new bo�leneck department?

4. Examine the following line flow process:
a. Determine the system capacity.
b. Determine which department is the bo�leneck.
c. Determine how much capacity can be gained by adding capacity to the bo�leneck.
d. Explain your answers to a, b, and c.
e. How would the analysis change if department A achieved an 85% yield? Recalculate a, b, and c.

Department Capacity (Parts/Hour)
A 120
B 110
C 140
D 160

5. Macro Galvanizing coats sheet steel for the appliance industry in its plant in Gary, Indiana. Macro has one produc�on line that can coat steel up to 72 inches wide. The produc�on
line runs 80 hours per week. Regardless of width, the steel is processed at 200 feet per minute. Macro processes only the three widths of steel listed here:

Width (in.) Product Mix
36 0.30
50 0.25
60 0.45

a. What is the capacity of Macro’s produc�on line in square feet of steel coated per week?
b. What is the capacity in square feet per week if the mix changes to 0.40, 0.40, and 0.20, respec�vely?
c. What is the capacity in square feet per week if the mix does not change and Macro decides to use 10% over�me per week?
d. What is the capacity in square feet per week if the mix does not change, there is no over�me, and Macro experiences 5% unplanned down�me?
e. What is the capacity in square feet per week if the mix does not change, there is no over�me, and Macro’s engineers find a way to run the line at 220 feet per minute?

6. Monique Food Processing Company produces light snacks that can be heated in a microwave. The following steps are included in the process:

Steps Descrip�on Capacity (Units/Hour)
1 Prepare food 200
2 Measure and place in plas�c pouch 175
3 Prepare cardboard box 200
4 Insert pouch into box 300
5 Shrink-wrap box 200

a. What is the system capacity, and which is the bo�leneck department?
b. How much slack (unused capacity) is available in other departments?
c. How much system capacity can be gained by adding capacity to the bo�leneck?

Processing math: 0%

7. Botkins Bicycle Shop manufactures 10-speed bikes. The assembly process requires the components listed below. Botkins can assemble approximately 350 bicycles per week without
over�me. The labor contract allows Botkins’ management to add up to 10% over�me to assembly opera�ons.

Component Quan�ty per Finished Bicycle Source Capacity (Units/Week)
Wheels 2 Internal 750
Tires 2 External 900
Frame 1 Internal 400
Brakes 2 External 950
Handle bars 1 Internal 600
Pedal and drive sprocket subassembly 1 Internal 500

a. What is the capacity of the facility without using over�me? Which is the bo�leneck department(s)?
b. What is the capacity of the facility with over�me? Which is the bo�leneck department(s)?
c. What increases in department capacity would be required to increase system capacity to 450 units per week?

8. The Mills Brothers Cereal Company makes a wheat and raisin cereal on one of its produc�on lines. One pound of raisins is required for four pounds of wheat flakes in order to make
five pounds of cereal. The following steps are included in the process:

Step Descrip�on Capacity (Pounds/Hour)
A Crush wheat 1,400
B Form flakes 1,200
C Toast flakes 1,600
D Coat raisins 250
E Mix cereal and raisins 1,200
F Put mixture in box 1,100
G Place boxes in shipping containers 1,400

a. What is the system capacity, and which is the bo�leneck department?
b. How much slack (unused capacity) is available in other departments?
c. How much system capacity can be gained by adding capacity to the bo�leneck?

9. White Chemical has a problem with its opera�ons. Analyze the following flow process:

Department Capacity (Gallons/hour)
A 100
B 60
C 50
D 120
E 100
F 40
G 140

The ra�o for mixing the outputs from departments E and F is 2:1. This means that ge�ng three gallons out of G requires mixing two gallons of E’s output and one gallon of F’s
output. The ra�o for departments B and C is 1:1.

a. What is the system’s capacity?
b. Which department(s) is the bo�leneck?
c. How much slack (unused capacity) is available in the other departments?
d. How much system capacity can be gained by adding capacity to the bo�leneck?

10. Pla�num Refining and Chemical Company is examining its pes�cide plant. At this �me, the company is unable to sa�sfy customer demand for a new insect spray. You have been
asked to spend some �me at the facility to determine how output can be increased. Analyze the following line flow process:

Processing math: 0%

Department Capacity (Gallons/Hour)
A 300
B 250
C 200
D 250
E 600
F 550
G 600
H 1,100
I 300
J 1,200

The ra�o for mixing the outputs from departments B, C, and D is 2:2:1, respec�vely. This means that making five gallons for department E requires mixing two gallons of B’s
output, two gallons of C’s output, and one gallon of D’s output. The ra�o for departments F and G is 1:1. The ra�o for departments H and I is 4:1.

a. What is the system capacity, and which is the bo�leneck department?
b. How much slack (unused capacity) is available in other departments?
c. How much system capacity can be gained by adding capacity to the bo�leneck?

11. Bauer Electric makes integrated circuits for the computer industry. Currently, the process for making circuits yields 80% good parts. The facility has the capacity to produce 2,000,000
units per year, including both good and bad units. The variable cost is $2.00 per unit. The annual fixed cost is $10,000,000. The selling price is $12.00 per unit. Currently, the market
demand exceeds the units available.

a. If Bauer Electric works at capacity, what is the total amount of units produced in one year that meet specifica�ons?
b. If the yield can be increased from 80% to 90%, how much does the unit cost for a circuit change?
c. If the yield can be increased from 80% to 90% and demand is unlimited, how much will profits increase?
d. If the yield can be increased from 80% to 90% and demand is 1,600,000 units, what is the impact on profits?
e. Why is there such a difference between the answers to c and d?

12. McComas Educa�onal Service provides training to pass the bar exam. The company offers a money back guarantee if a student does not pass on the first try. Currently, 60% pass the
exam. The company is working on some computer-based training that could increase the pass rate to 80%. The cost of the service is $800, and 10,000 first-�me students enroll in the
course each year. Demand has grown at about 5% per year. The variable cost is only $100, and the annual fixed cost is $2,000,000. For the current cost structure, capacity is 12,000
students per year.

a. Currently, how many first-�me students pass the test each year?
b. If the pass rate increases from 60% to 80%, how much will profits increase?
c. Should McComas consider reducing capacity?

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Key Terms

Click on each key term to see the defini�on.

bo�leneck
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The department, worksta�on, or opera�on that limits the flow of product through the produc�on system. This department restricts the flow of product from upstream departments
and starves downstream departments.

capacity
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A measure of the organiza�on’s ability to provide customers with the demanded services or goods, in the amount requested and in a �mely manner. Capacity is the maximum rate
of produc�on.

machine constrained
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The machine is holding back produc�on. The equipment is opera�ng for all the available �me at its best speed while the operator has some idle �me.

product mix
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The percent of total demand or output that is devoted to each product.
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rounding out capacity
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Adding capacity to a bo�leneck department to increase the capacity of a system by bringing the capacity of the bo�leneck department into balance with the other departments.

system capacity
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The ability of the organiza�on to produce a sufficient number of goods and services to meet the demands of customers.

yield
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The ra�o of the quan�ty of output to the quan�ty of input.

Processing math: 0%

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