Long Rang Capacity Planning
Long Range Capacity Planning
Capacity is the Productive Capability of a Production Facility
Capacity Measurement: Aggregate Unit of Output/Input Rate
Single Item: Output Rate (e.g., TV/month., ton/day).
o Aggregate unit of Output (Ton, SQFT,..), or
o Aggregate unit of Input (Labor hour/Machine hour).
In Service: Input Rate (e.g., Available Bed per mon. in hospital).
Why Capacity Planning: Matching Demand Fluctuation.
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Measurements of Capacity
Output Rate Capacity
For a facility having a single straight product or a few
homogeneous products, the unit of measure is straight forward
(barrels of beer per month)
For a facility having a diverse mix of products, an aggregated
unit of capacity must be established using a common unit of
output (sales dollars per week)
Input Rate Capacity
Commonly used for service operations where output measures
are particularly difficult
o Hospitals use available beds per month
o Airlines use available seat-miles per month
o Movie theaters use available seats per month
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
An additional amount of capacity added onto the expected
demand to allow for:
o Greater than expected demand
o Demand during peak seasons
o Lower production costs
o Product and volume flexibility
o Improved quality of products and services
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Design Capacity vs. Maximum Capacity
Design Capacity (Q*): the amount of Output at which the AUC
(Average Unit Cost) of a production facility is the Minimum.
Practical Maximum Capability (Qm): the Maximum amount of
Output that a facility can produce (at a Higher AUC).
When: Q < Q*, (Under-capacity) , then, AUC > AUC*,
When: Q > Q*, (Over-capacity), then, AUC > AUC*.
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Capacity can be expressed in terms of outputs or inputs.
Output measures—the usual choice for flow processes
Input measures—used for flexible flow processes
Peak (Maximum) Capacity: Calling for extraordinary effort under
ideal conditions that are not sustainable
Effective (Design) Capacity: Economically sustainable under
Increased Designed Capacity: to remove the “bottleneck”—and
operation that has the lowest effective capacity of any operation in
the facility and thus limits the system’s output
Expansion of a facility’s capacity occurs only when bottleneck
capacity is increased.
Flexible flow processes may have floating bottlenecks due to
widely varying workloads on different operations at different
Job shops have low equipment utilization rates.
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Economy of Scale: Refer to the Cost Reduction Resulting from the
Increase in Production Quantity.
"Economies of Scale are so vague that it can be used to justify
any number of decisions, which all too often turn out to be
Plant Des Cap. Act. Prod. Proc. Tech AUC
A 100 100 X $10
B 100 60 X $12
C 200 200 X $5
D 200 200 Y $2
AUC(A) < AUC(B) Volume Economy
AUC(C) < AUC(A) Capacity Economy
AUC(D) < AUC(C) Technology Economy
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Increases in Incremental Facility Capacity
Year Forecast Least Unit
Annual Volume Cost Design
1 200,000 A
2 250,000 A
3 320,000 B
4 360,000 B
Average 5 400,000 B
6 450,000 B
per Unit A B 7 520,000 C
Cost of B C 8 560,000 C
Output ($) 9 600,000 C
10 640,000 C
Plant Large Plant
240,000 450,000 640,000
Annual Volume (units)
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Economies of Scale
Best operating level- least average unit cost
Economies of scale- average cost per unit decreases as the
volume increases towards the best operating level
Diseconomies of scale- average cost per unit increases as the
volume increases beyond the best operating level
Declining cost result from:
o Fixed costs being spread more over more and more units
o Longer production runs result in a smaller proportion of
labor being allocated to setups
o Proportionally less material scrap
o … and other economies
Diseconomies of Scale
Increasing costs result from increased congestion of workers and
material, which contributes to:
Difficult in scheduling
Increased use of overtime
… and other diseconomies
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Three Level Capacity Planning
1. Long Range Capacity Planning: T > 1 year (3 - 5 year).
Decisions: Planning for Capacity that Requires a Long Time to
(e.g., Plant/Building/Equipment/High Cost Facility/....)
2. Intermediate Range Capacity Planning: T (6 - 18 Month)
Decision: Planning for Capacity Requirement
(Monthly or Quarterly).
(e.g., Work Force Size/New Tools/Inventory/Subcontracting/...)
3. Short Range Capacity Planning: T (1 - 6 Month)
Decision: Weekly (or Daily) Capacity Planning
(e.g., Overtime Use/Personnel Transfer/Alternative
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Capacity Planning Process
1. Determining Capacity Requirement:
Long Range Demand Forecasting
2. Generating Alternative Capacity Plans:
When should New Capacity be Added? (Timing)
How Much New Capacity should be Added? (Sizing)
What Kind of Capacity should be Added? (Type)
3. Evaluating Alternative Capacity Plans:
4. Selecting Best Capacity Plan Under Given Objectives
5. Locating New Capacity (Facility Location).
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The Timing of Capacity Increments
Policy A: Capacity Leads Policy B: Capacity Lags Demand
Policy C: Capacity is matched, as Nearly as Possible, To Demand
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The Sizing of Capacity Increments
Should The Capacity Be Added More Often In Small Increments
(Options A) Or In Large Increments Less Frequently (Option B)?
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Factors Leading to Large Capacity Strategy
When demand is variable, uncertain, or product mix changes
When finished goods inventory cannot be stored
When customer service is important
When capacity comes in large increments
When supply of material or human resources is uncertain
Factors Leading to Small Capacity Strategy
Unused capacity costs money
Large cushions hide inefficiencies, absenteeism, and unreliable
When subcontractors are available to handle demand peaks
Keeps ahead of demand, maintains a capacity cushion
Large, infrequent jumps in capacity/higher financial risk
Lower risk of losing market share/economies of scale
Lags behind demand, relying on short-term peak capacity
options (overtime, subcontractors) to meet demand
Lower financial risk with overly optimistic demand forecast
Lower risk of a technological advancement making a new
Higher risk of losing market share
An intermediate strategy of copying competitors’ actions
Tends to prevent anyone from gaining a competitive advantage
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Evaluation of Capacity Plans
1. Net Present Value Analysis 2. Breakeven Analysis
3. Decision Tree Model 4. Computer Simulation
Decision Making: Select a Plan/Policy/Method among Available
Decision Model: A Simplified Representation of a Real World
Problem. There are many decision models developed in the
literature for different problems.
Three Major Elements of a Decision Model:
1. Objectives must be Measurable.
2. Decision Variables must be Controllable.
3. Constraints and Assumptions.
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Decision Tree Model
Decision Tree model is primarily developed for problems where:
A series of (multiple) decisions must be made sequentially,
All decisions are interrelated and interdependent, and
Outcomes associated with each decision are uncertain.
Assumptions of Decision Tree Model:
1. Objective is a Single Measurement (Gain or Loss).
2. All Possible Outcomes associated with a Decision have a Known
3. Best Plan is represented by the Optimal Expected Value.
Probability of Outcome
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Tom Hawkins, president of Textrom, Inc., was pacing up and
down his office in the corporate headquarters pondering about the
situation facing his company. What bothered him most was that he
had little time to gather additional information and had to make a
fast decision. The situation involved choosing between three
alternative strategies to add much needed production capacity. The
decision is to be made concerned WoodSmith, one of Textrom
divisions that manufactured industrial woodworking tools. Tom’s
concerns were mainly about the assumptions made by his director of
Systems Department, Ron Collins, who had originally come up with
the analyses and the alternative capacity expansion strategies. The
validity of these assumptions were crucial to the outcome of any of
the strategies. Tom had asked Ron to present his report to the
board’s meeting tomorrow morning. Tom knew that the
presentation would involve a great deal of quantitative analysis and
was wondering if the board members were quite ready for that.
Based on experience, he knew that most of the members were
mainly concerned about the qualitative aspects of proposed projects.
This was particularly true of Jerry Caldwell, the director of Human
Company Background and Issues
Last year Textrom’s sales were over $255 million making it one
of the largest industrial tool manufacturers in the industry. The
company supplied large manufacturing firms both domestically and
internationally. For the past 10 years, Textrom’s sales and earnings
had grown at an average rate of 9% a year. Top management had
felt that this growth rate was too low and had established a long
range objective of 15 percent growth per year. Achieving this
objective was not easy. Competition was intense and the industry
somewhat mature. WoodSmith division, which manufactured
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woodworking tools, was of prime importance in reaching this goal.
The primary market for WoodSmith was furniture manufacturing
firms and the housing industry. This division’s sales was quite good
and the first quarter reports indicated that WoodSmith orders were
up 21.7 percent over last years orders. In fact, demand from the
current customers alone was already consuming main WoodSmith’s
main plant production in Greenville, North Carolina. Additional
capacity was clearly necessary. However, the best method for
attaining that additional capacity was unclear.
Three alternatives were under consideration for increasing
1. Expanding the existing plant in Greenville. Th initial cost of
such expansion would be less than any new facilities since the
land and most required additional plant space were already
available. However, this expansion would be limited to only 10
percent of existing capacity. This would solve the problem of
undercapacity only for the next 3 to 4 years, whereas a new
plant would had such effect for at least 10 years.
2. Jackson, Tennessee. This location would allow Textrom to
reduce the $15 per ton freight equalization that it was
currently paying to supply its major mid-western customer.
Furthermore, Textrom already owned a plant, belonging to
another division, in this area that was being phased out of its
operations. Therefore land and building were already available
at a price well below building a new facility. This location was
big enough to allow 25% capacity increase. Production would
be possible by next year and half.
3. Birmingham, Alabama. The Birmingham are would provide
an estimated $930,000 in sales in 1969, up from $720,000 in
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1968 and was considered a very fast growing area in the
nation. However, this location was the center of competition
and would also increase the freight equalization charge to $18
per ton. It would cost almost $3.4 million for building, land
and equipment and new production would not begin for next 3
years. By building the plant specifically for WoodSmith
production, however, the company could automate much of the
production process and have the most cost efficient facility in
The board meeting was presided by Tom. Billy Young, vice
president for finance, Jerry Caldwell, Ron Collins, and Peter
Shapiro, manufacturing vice president were the other members in
Tom: We’ve got to decide and soon. You know the objectives of
the company. If we want to reach that 15 percent growth rate, we
should do something fast. Ron has done a preliminary analysis of
the situation and has come up with three alternatives. Let’s look at
these alternatives. Please don’t hold back your comments.
(Ron presents his analysis of the alternatives)
Ron: I personally believe that we need to take advantage of
technology and make our plants as cost efficient as possible.
Building a new plant in Birmingham, Alabama would allow us that.
But you can see it is pretty expensive. What is most important is that
the Birmingham location is right in the middle of a rapid expanding
new market. We should consider our strengths and how can we fight
already established competition in the area.
Peter: But we should also be aware of the present constrain on
our capacity and how fast we want it to increase. A new plant in
Birmingham would take too long to start production. Maybe we
should stick with expanding our plant in Greenville. This way, we
will not commit ourselves to too much investment, should the
demand pattern change.
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Ron: Marketing department forecasts indicate that if there is
going to be any demand change it is going to be a step increase. I
don’t think we will be talking much risk if we add additional
capacity beyond our present needs. Besides, having a plant in
Birmingham would make it easier to deliver our products faster to
the potential customer. The Birmingham area is growing quite fast,
you all know.
Peter: What about our place in Jackson. It certainly has some
Tom: Yes. But I have a report on that location. It needs
substantial renovation, especially if we want to automate the plant. I
am not sure if it will cost much less than a new plant.
Ron: Birmingham alternative seems to be the best bet,
considering the significance of be cost efficient.
Peter: The trouble is that that plant will not be ready soon
enough to remove our present capacity constrain. We need some
Tom: There is a way to do both. I think we could publicly
announce that we are going to build a plant in Birmingham This will
preempt the competitors from entering that market. It is important
to release such information to the public, since it is an industry
practice to develop one’s strategy on competitor’s strategies. We
already have some report indicating that one of our major
competitors is doing a feasibility study for a new plant in the
Birmingham area. Meanwhile we could expand the plant in
Greenville just enough to meet short term demand. This doe not
have to be announced to the public. You understand.
Peter: It sounds like a very good idea.
Ron and Billy: Yes. This is very good.
Jerry: I don’t question your financial analysis and your
figures, I just don’t feel comfortable about this publicly announcing
something and doing something else. What do you all think about
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Decision Tree Analysis Problem
XYZ Company is considering whether to build a large plant or a
small plant for a new product which has an estimated life of 7 years.
A small plant requires an investment of $3.4 million. A large plant
requires an investment of $4.9 million. The small plant can be
expanded after a year at an additional investment of $800,000. The
following estimates are available for after-tax income and demand.
1. If demand is high, a large or expanded plant would yield an
annual income of $900,000.
2. If demand is low, a large plant would yield an annual income
3. If demand is high, a small plant would yield an annual income
4. If demand is low, a small plant would yield an annual income
5. Probability if high demand in the first year is 0.6. If demand is
high the first year, probabilities if high and low demand in
subsequent years are 0.7 and 0.3, respectively.
6. Probability of low demand in the first year is 0.4. If demand is
low in the first year, the probabilities of high and low demand
in subsequent years are 0.2 and 0.8 respectively.
Using decision trees, evaluate each alternative. Which alternative
should be followed by XYZ?
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The decision tree for this problem is given. At decision point 1, the choice is to
build either a small plant or a large plant. Chance events A and B show
whether the demand will be high or low in the first year. Decision points 2 and
3 show whether the small plant should be expanded at the end of the first
year. Chance events C, D, E, F, G, and H show whether the demand will be
high or low in subsequent years.
We evaluated the three from the right-hand side. Investment and income are
given in thousands of dollars.
Event C: $900(6)(0.7) + $300 (6)(0.3)= $4,320
Event D: $600(6)(0.7) + $500 (6)(0.3)= $3,420
Event E: $900(6)(0.2) + $300 (6)(0.8)= $2,520
Event F: $600(6)(0.2) + $500 (6)(0.8)= $3,120
Event G: $900(6)(0.7) + $300 (6)(0.3)= $4,320
Event H: $900(6)(0.2) + $300 (6)(0.8)= $2,520
Decision Point 2:
Expand: Income= $4,320- $800 = $3,520
Do not expand: Income=…………….....= $3,420
At this point the decision will be to expand the plant because the income for
this alternative is larger. Event D will therefore be served.
Decision Point 3:
Expand: Income= $42,520- $800 = $1,720
Do not expand: Income=…………………= $3,120
At this point the decision will be “do not expand” because the income for this
alternative is larger. Event E will therefore be served.
Decision Point 1:
Expand: Income= $3,920- $3,400 = $520
Do not expand: Income= $4,260- $4,00 = $260
At this point the decision will be to build a small plant. Event B therefore will
Thus, XYZ should initially build a small plant. At the end of one year, if
demand is high, the company should expand the plant. If demand is low, the
company should not expand the plant. Expected income is $520,000.
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Long-Range Facility Planning Exercises
1. A company has formalized a new-product concept and must now decide whether to provide
for long-range production capacity in its five year plan. The company has three opportunities for
profiting from the new product: sell the idea outright now to another company, lease the concept
for a royalty, or develop the product in-house. If the concept is sold outright, it will bring
$1,500,000. A consulting firm has surveyed the potential markets for the idea. If the concept is
leased for royalty, two companies have submitted proposals and this information applies:
Size of Market Probability Payoffs
Large 0.5 $2,800,000
Marginal 0.5 2,200,000
Large 0.5 $2,600,000
Marginal 0.5 2,300,000
If the company develops the concept into a new product, it can sell the rights out to the
product. If this alternative is selected this information applies:
Size of Market Probability Payoffs
Large 0.5 $2,500,00
Marginal 0.5 2,200,000
If the company develops the new product and then produces and markets it, this information
Size of Market Probability Payoffs
Large 0.5 $3,000,000
Marginal 0.5 1,800,000
a. Use a decision tree analysis and recommend a course of action for this new product idea.
b. If the company follows your recommendation, what returns should the company expect
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2. A home product discount store is considering expanding its capacity to meet a growing
demand for its products. The alternatives are to build a new store at a side nearby, expand and
refurnish the old store, or do nothing. Economists have projected the regional economic outlook:
a 50 percent probability that the economy will remain unchanged, a 20 percent of an economic
upturn, and a 30 percent probability of an economic downturn. The following estimates of annual
returns have been prepared (in millions of dollars):
Market Downturn Stable Market Market Upturn
Build new store $(0.8) $0.5 $2.1
Expand old store (0.4) 0.8 1.4
Do nothing (0.1) 0.2 0.5
a. Use a decision tree to analyze these decision alternatives.
b. What should the company do based on your decision three analysis?
c. What returns will accrue to the company if the recommendation is followed?
3. A company manufactures stamped steel products. Increasingly, foreign producers are
undercutting the company’s price for these stampings, and the company is studying the
technology of its production capacity to determine if it should be upgraded to become
competitive with foreign firms. If production processes are automated, the net present value of
the returns (net present value means that the returns are expressed in terms of today’s dollars) to
the company is dependent on the market for the plant’s products:
Process Market Level Likelihood Return
Automated High 0.1 $4,000,000
Med 0.5 2,600,000
Low 0.4 1,500,000
If the company decides to do nothing now and review the situation in five years, two alternatives
will probably be present then- continue operating with the existing production processes or shut
the plant down and liquidate its assets. If the plant continues to be operated in its existing
condition after five years, the net present value of the returns is dependent on the market for the
plant’s products at that time:
Alternative Market Level Likelihood Return
Do nothing now, High 0.3 $3,000,000
continue operating in Med 0.4 2,500,000
existing conditions Low 0.3 2,000,000
If the company shuts the plant down and liquidates its assents after five years, the net present
value of the returns is estimated to be $2,000,000.
a. Use a decision tree analysis and recommend a course of action for the company.
b. What returns should the company actually expect from following your recommendations.
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Use <POM-Window> for Decision-Tree Problems
Step-1: Start <POM-Windows> - click <Decision Analysis> from the [Module] menu.
Step-2: Under <File>, Click <New> - you will see a downward menu – listing available two
1. Decision Table
2. Decision Tree
Now, selecting the <Decision Tree>.
Step-3: Now you well see data input screen <Creating a new data>:
Before you can start to input, now you must draw the tree on the paper first (like the ones
you see in your Sup. Text, and PPT files) in which, labeling each decision point (Square)
with numbers (like, 1, 2, ..) and event point (Node) with letters (like A, B, C, ..). You
have the power to decide on this labeling process, just making your tree looks good.
Then, on this screen,
Type in: <Problem #1 > in the [Title] box
(or any name you like)
Typing in the [No. of Branches] box (you count the number of branches in
Selecting a name for each row data [like, Branch1, Branch 2, ….]
Then, Click on [OK], you will see data input matrix screen.
Step-4: On <Data input matrix screen>:
I can tell you too much for this screen. You need typing in based the one on your paper
tree – you made earlier. Be aware – look at the top-right corner for the specific
instructions the program will provide to you.
Step-5: Now, click on <Solve> - you will see <Output> screen.
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