Slides prepared
by John Loucks
ã 2002 South-Western/Thomson Learning TM
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Chapter 5, Part A
Facility Capacity and Location
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Overview
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Facility Planning
Long-Range Capacity Planning
Facility Location
Wrap-Up: What World-Class Companies Do
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Facility Planning
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HOW MUCH long range capacity is needed
WHEN additional capacity is needed
WHERE the production facilities should be located
WHAT the layout and characteristics of the facilities
should be
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Facility Planning
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The capital investment in land, buildings, technology,
and machinery is enormous
A firm must live with its facility planning decisions
for a long time, and these decisions affect:
Operating efficiency
Economy of scale
Ease of scheduling
Maintenance costs
… Profitability!
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Long-Range
Capacity Planning
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Steps in the Capacity Planning Process
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Estimate the capacity of the present facilities.
Forecast the long-range future capacity needs.
Identify and analyze sources of capacity to meet these
needs.
Select from among the alternative sources of capacity.
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Definitions of Capacity
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In general, production capacity is the maximum
production rate of an organization.
Capacity can be difficult to quantify due to …
Day-to-day uncertainties such as employee
absences, equipment breakdowns, and materialdelivery delays
Products and services differ in production rates (so
product mix is a factor)
Different interpretations of maximum capacity
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Definitions of Capacity
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The Federal Reserve Board defines sustainable
practical capacity as the greatest level of output that a
plant can maintain …
within the framework of a realistic work schedule
taking account of normal downtime
assuming sufficient availability of inputs to operate
the machinery and equipment in place
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Measurements of Capacity
Output Rate Capacity
For a facility having a single product or a few
homogeneous products, the unit of measure is
straightforward (barrels of beer per month)
For a facility having a diverse mix of products, an
aggregate unit of capacity must be established
using a common unit of output (sales dollars per
week)
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Measurements of Capacity
Input Rate Capacity
Commonly used for service operations where
output measures are particularly difficult
Hospitals use available beds per month
Airlines use available seat-miles per month
Movie theatres use available seats per month
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Measurements of Capacity
Capacity Utilization Percentage
Relates actual output to output capacity
Example: Actual automobiles produced in a
quarter divided by the quarterly automobile
production capacity
Relates actual input used to input capacity
Example: Actual accountant hours used in a
month divided by the monthly account-hours
available
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Measurements of Capacity
Capacity Cushion
an additional amount of capacity added onto the
expected demand to allow for:
greater than expected demand
demand during peak demand seasons
lower production costs
product and volume flexibility
improved quality of products and services
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Forecasting Capacity Demand
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Consider the life of the input (e.g. facility is 10-30 yr)
Understand product life cycle as it impacts capacity
Anticipate technological developments
Anticipate competitors’ actions
Forecast the firm’s demand
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Other Considerations
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Resource availability
Accuracy of the long-range forecast
Capacity cushion
Changes in competitive environment
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Expansion of Long-Term Capacity
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Subcontract with other companies
Acquire other companies, facilities, or resources
Develop sites, construct buildings, buy equipment
Expand, update, or modify existing facilities
Reactivate standby facilities
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Reduction of Long-Term Capacity
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Sell off existing resources, lay off employees
Mothball facilities, transfer employees
Develop and phase in new products/services
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Economies of Scale
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Best operating level - least average unit cost
Economies of scale - average cost per unit decreases
as the volume increases toward the best operating
level
Diseconomies of scale - average cost per unit
increases as the volume increases beyond the best
operating level
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Economies and Diseconomies of Scale
Average Unit
Cost of Output ($)
Economies
of Scale
Diseconomies
of Scale
Best Operating Level
Annual Volume (units)
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Economies of Scale
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Declining costs result from:
Fixed costs being spread over more and more units
Longer production runs result in a smaller
proportion of labor being allocated to setups
Proportionally less material scrap
… and other economies
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Diseconomies of Scale
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Increasing costs result from increased congestion of
workers and material, which contributes to:
Increasing inefficiency
Difficulty in scheduling
Damaged goods
Reduced morale
Increased use of overtime
… and other diseconomies
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Two General Approaches
to Expanding Long-Range Capacity
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All at Once – build the ultimate facility now and
grow into it
Incrementally – build incrementally as capacity
demand grows
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Two General Approaches
to Expanding Long-Range Capacity
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All at Once
Little risk of having to turn down business due to
inadequate capacity
Less interruption of production
One large construction project costs less than
several smaller projects
Due to inflation, construction costs will be higher
in the future
Most appropriate for mature products with stable
demand
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Two General Approaches
to Expanding Long-Range Capacity
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Incrementally
Less risky if forecast needs do not materialize
Funds that could be used for other types of
investments will not be tied up in excess capacity
More appropriate for new products
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Subcontractor Networks
A viable alternative to larger-capacity facilities is to
develop subcontractor and supplier networks.
“Farming out” or outsourcing your capacity needs
to your suppliers
Developing long-range relationships with suppliers
of parts, components, and subassemblies
Relying less on backward vertical integration
Requiring less capital for production facilities
More easily varying capacity during slack or peak
demand periods
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Outsourcing Service Functions
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Building maintenance
Data processing
Delivery
Payroll
Bookkeeping
Customer service
Mailroom
Benefits administration
… and more
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Economies of Scope
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The ability to produce many product models in one
flexible facility more cheaply than in separate
facilities
Highly flexible and programmable automation allows
quick, inexpensive product-to-product changes
Economies are created by spreading the automation
cost over many products
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Analyzing Capacity-Planning Decisions
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Break-Even Analysis (Chapter 4 and this chapter)
Present-Value Analysis
Computer Simulation (Chapter 9)
Waiting Line Analysis (Chapter 9)
Linear Programming (Chapter 8)
Decision Tree Analysis (this chapter)
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Example: King Publishing
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Break-Even Analysis
King Publishing intends to publish a book in
residential landscaping. Fixed costs are $125,000 per
year, variable costs per unit are $32, and selling price
per unit is $42.
A) How many units must be sold per year to
break even? B) How much annual revenue is
required to break even? C) If annual sales are 20,000
units, what are the annual profits? D) What variable
cost per unit would result in $100,000 annual profits
if annual sales are 20,000 units?
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Example: King Publishing
Break-Even Analysis
A) How many units must be sold per year to break even?
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Q = FC/(p-v) = $125,000/(42 – 32) = 12,500 books
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Example: King Publishing
Break-Even Analysis
B) How much annual revenue is required to break even?
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TR = pQ = 42(12,500) = $525,000
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Example: King Publishing
Break-Even Analysis
C) If annual sales are 20,000 units, what are the annual
profits?
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P = pQ – (FC + vQ)
= 42(20,000) – [125,000 + 32(20,000)]
= 840,000 – 125,000 – 640,000
= $75,000
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Example: King Publishing
Break-Even Analysis
D) What variable cost per unit would result in $100,000
annual profits if annual sales are 20,000 units?
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P = pQ – (FC + vQ)
100,000 = 42(20,000) – [125,000 + v(20,000)]
100,000 = 840,000 – 125,000 – 20,000v
20,000v = 615,000
v = $30.75
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Decision Tree Analysis
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Structures complex multiphase decisions, showing:
What decisions must be made
What sequence the decisions must occur
Interdependence of the decisions
Allows objective evaluation of alternatives
Incorporates uncertainty
Develops expected values
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Example: Good Eats Café
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Decision Tree Analysis
Good Eats Café is about to build a new
restaurant. An architect has developed three building
designs, each with a different seating capacity. Good
Eats estimates that the average number of customers
per hour will be 80, 100, or 120 with respective
probabilities of 0.4, 0.2, and 0.4. The payoff table
showing the profits for the three designs is on the
next slide.
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Example: Good Eats Café
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Payoff Table
Average Number of Customers Per Hour
c1 = 80 c2 = 100 c3 = 120
Design A
Design B
Design C
$10,000
$ 8,000
$ 6,000
$15,000
$18,000
$16,000
$14,000
$12,000
$21,000
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Example: Good Eats Café
Expected Value Approach
Calculate the expected value for each decision.
The decision tree on the next slide can assist in this
calculation. Here d1, d2, d3 represent the decision
alternatives of designs A, B, C, and c1, c2, c3 represent
the different average customer volumes (80, 100, and
120) that might occur.
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Example: Good Eats Café
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Payoffs
Decision Tree
2
d1
1
c1
(.4)
c2
c3
(.2)
(.4)
10,000
15,000
14,000
d2
3
d3
4
c1
(.4)
c2
c3
(.2)
(.4)
c1
(.4)
c2
(.2)
c3
8,000
18,000
12,000
6,000
16,000
(.4)
21,000
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Example: Good Eats Café
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Expected Value For Each Decision
EV = .4(10,000) + .2(15,000) + .4(14,000)
= $12,600
d1
2
d2
EV = .4(8,000) + .2(18,000) + .4(12,000)
= $11,600
Design A
1
Design B
3
Design C
d3
EV = .4(6,000) + .2(16,000) + .4(21,000)
= $14,000
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Choose the design with largest EV -- Design C.
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Facility Location
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A Sequence of Decisions
National Decision
Political, social, economic stability;
Currency exchange rates; . . . . .
Regional Decision
Climate; Customer concentrations;
Degree of unionization; . . . . .
Community Decision
Transportation system availability;
Preference of management; . . . . .
Site Decision
Site size/cost; Environmental impact;
Zoning restrictions; . . . . .
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Factors Affecting
the Location Decision
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Economic
Site acquisition, preparation and construction costs
Labor costs, skills and availability
Utilities costs and availability
Transportation costs
Taxes
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Factors Affecting
the Location Decision
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Non-economic
Labor attitudes and traditions
Training and employment services
Community’s attitude
Schools and churches
Recreation and cultural attractions
Amount and type of housing available
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Facility Types and Their
Dominant Locational Factors
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Mining, Quarrying, and Heavy Manufacturing
Near their raw material sources
Abundant supply of utilities
Land and construction costs are inexpensive
Light Manufacturing
Availability and cost of labor
Warehousing
Proximity to transportation facilities
Incoming and outgoing transportation costs
. . . more
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Facility Types and Their
Dominant Locational Factors
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R&D and High-Tech Manufacturing
Ability to recruit/retain scientists, engineers, etc.
Near companies with similar technology interests
Retailing and For-Profit Services
Near concentrations of target customers
Government and Health/Emergency Services
Near concentrations of constituents
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Some Reasons the
Facility Location Decision Arises
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Changes in the market
Expansion
Contraction
Geographic shift
Changes in inputs
Labor skills and/or costs
Materials costs and/or availability
Utility costs
. . . more
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Some Reasons the
Facility Location Decision Arises
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Changes in the environment
Regulations and laws
Attitude of the community
Changes in technology
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Analyzing Service Location Decisions
Consumer Behavior
Research
Market Research
Why do customers buy our
products and services?
Who are our customers?
What are their characteristics?
Data Gathering for
Each Location Alternative
Where are our customers concentrated?
What are their traffic/spending patterns?
Revenue Projections for
Each Location Alternative
What are the economic projections?
What is the time-phased revenue?
Profit Projections for
Each Location Alternative
What are the projected revenues
less time-phased operating costs?
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Analyzing Industrial Facility Locations
Factors that tend to dominate the industrial-facility
location decision are:
Transportation costs
Labor cost and availability
Materials cost and availability
Utilities cost
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Analyzing Industrial Facility Locations
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Locating a Single Facility
A simple way to analyze alternative locations is
conventional cost analysis
Pros – ease of communication and understanding
Cons – time value of money ignored and
qualitative factors not considered
Locating Multiple Facilities
More sophisticated techniques are often used:
Linear programming, computer simulation,
network analysis, and others
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Qualitative Factors in Location Decisions
Often-important qualitative factors include
Housing
Climate
Community activities
Education and health services
Recreation
Churches
Union activities
Community attitudes
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Integrating Qualitative & Quantitative Factors
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Managers often wrestle with the task of trading off
qualitative factors against quantitative ones
Methods for systematically displaying the relative
advantages and disadvantages, both qualitative and
quantitative, of each location alternative have been
developed
The relative-aggregate-scores approach is one such
method
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Relative-Aggregate-Scores Approach
Quantitative and Qualitative Factors
Factor
Location A
Location B
Econ.
Wgt. Econ.
Wgt.
Weight Data Score Score Data Score Score
Prod.cost/ton
Transp.cost/ton
Labor Avail.
Union Activity
Total Score
.45
.35
.15
.05
$65 .923
$18 1.000
.700
.450
.415
.350
.105
.023
.893
$60 1.000
$21 .857
.500
.750
.450
.300
.075
.038
.863
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Wrap-Up: World-Class Practice
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Outstanding long-range business plans
Long-range capacity studies
Justify investment on how it positions their company
to capture market share
Facility location decisions involve worldwide search
for sites
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End of Chapter 5, Part A
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