Capacity planning involves establishing the maximum output rate that a facility can achieve. It includes determining how much capacity to install, when to increase capacity, and how much to increase it. Location analysis identifies the best geographic location for facilities based on factors like proximity to suppliers, customers, labor, and community considerations. Methods for evaluating capacity and location alternatives include decision trees, break-even analysis, and load-distance models. Capacity planning and location decisions impact operations strategy and are important across the organization.

1. 1
Capacity Planning
& Facility Location

2. 2
Capacity planning
 Capacity is the maximum output rate of a facility
 Capacity planning is the process of establishing the
output rate that can be achieved at a facility:
 Capacity is usually purchased in “chunks”
 Strategic issues: how much and when to spend
capital for additional facility & equipment
 Tactical issues: workforce & inventory levels, &
day-to-day use of equipment

3. Capacity planning
 Capacity planning is central to the long-term
success of an organization. Capacity plans are
made at two levels:
 (i) Long-term capacity plans : which deal with
investments in new facilities and equipments
covering the requirements for at least two years
into the future and
 (ii) Short-term capacity plans : which focus on
work-force size, overtime budgets, inventories etc.
3

4. Capacity planning
A long term strategic decision that establishes
a firm’s overall level resources.
 Three major capacity decisions are:
 i. How much capacity to be installed,
 ii. When to increase capacity and
 iii. How much to increase
4

5. TYPES OF CAPACITY
 Production capacity: Maximum rate of
production or output of an organization. (e.g.,
100 cars per day etc .. )
 Design capacity: The maximum output that
can possibly be attained.
 Effective capacity: The maximum output given
a product mix, scheduling difficulties, machine
maintenance, quality factors, absenteeism etc.
 Maximum capacity: The maximum output that
a facility can achieve under ideal conditions.
Also known as peak 5

6. DETERMINANTS OF EFFECTIVE CAPACITY
Many decisions about design of the production
system and operation of the production system
may have an impact on capacity.
The main factors relate to the following:
(i) Facilities,
(ii) Product or services,
(iii) Process
(iv) Human resource considerations,
(v) Operations and
(vi) External forces. 6

7. 7
Measuring Capacity Examples
 There is no one best way to measure capacity
 Output measures like kegs per day are easier to understand
 With multiple products, inputs measures work better
Type of Business
Input Measures of
Capacity
Output Measures
of Capacity
Car manufacturer Labor hours Cars per shift
Hospital Available beds Patients per month
Pizza parlor Labor hours Pizzas per day
Retail store
Floor space in
square feet
Revenue per foot

8. 8
Measuring Available Capacity
 Design capacity:
 Maximum output rate under ideal conditions
 A bakery can make 30 custom cakes per day
when pushed at holiday time
 Effective capacity:
 Maximum output rate under normal (realistic)
conditions
 On the average this bakery can make 20
custom cakes per day

9. 9
Measuring Effectiveness of
Capacity Use
 Measures how much of the available
capacity is actually being used:
 Measures effectiveness
 Use either effective or design capacity in
denominator
 
100%
capacity
rate
output
actual
n
Utilizatio 

10. 10
Example of Computing Capacity Utilization: A bakery’s
design capacity is 30 custom cakes per day. Currently the bakery is
producing 28 cakes per day. What is the bakery’s capacity
utilization relative to both design and effective capacity?
93%
(100%)
30
28
(100%)
capacity
design
output
actual
n
Utilizatio
140%
(100%)
20
28
(100%)
capacity
effective
output
actual
n
Utilizatio
design
effective






 The current utilization is only slightly below its design
capacity and considerably above its effective capacity
 The bakery can only operate at this level for a short period
of time

11. 11
Capacity Considerations
 The Best Operating Level is the output that results in
the lowest average unit cost
 Economies of Scale:
 Where the cost per unit of output drops as volume of output
increases
 Spread the fixed costs of buildings & equipment over multiple
units, allow bulk purchasing & handling of material
 Diseconomies of Scale:
 Where the cost per unit rises as volume increases
 Often caused by congestion (overwhelming the process with too
much work-in-process) and scheduling complexity

12. 12
Best Operating Level and Size
 Alternative 1: Purchase one large facility, requiring one large
initial investment
 Alternative 2: Add capacity incrementally in smaller chunks as
needed

13. 13
Other Capacity Considerations
 Focused factories:
 Small, specialized facilities with limited
objectives
 Plant within a plant (PWP):
 Segmenting larger operations into smaller
operating units with focused objectives
 Subcontractor networks:
 Outsource non-core items to free up
capacity for what you do well

14. 14
Making Capacity Planning
Decisions
The three-step procedure for making
capacity planning decisions is as
follows:
1. Identify Capacity Requirements
2. Develop Capacity Alternatives
3. Evaluate Capacity Alternatives

15. 15
Identifying capacity
requirements
 Forecasting Capacity:
 Long-term capacity requirements based on future demand
 Identifying future demand based on forecasting
 Forecasting, at this level, relies on qualitative forecast models
 Executive opinion
 Delphi method
 Forecast and capacity decision must included strategic implications
 Capacity cushions
 Plan to underutilize capacity to provide flexibility
 Strategic Implications
 How much capacity a competitor might have
 Potential for overcapacity in industry a possible hazard

16. 16
Developing & Evaluating Capacity
Alternatives
 Capacity alternatives include
 Could do nothing,
 expand large now (may included
capacity cushion), or
 expand small now with option to add
later
 Use decision support aids to evaluate
decisions (decision tree most popular)

17. 17
Decision trees
Diagramming technique which uses
 Decision points – points in time when decisions
are made, squares called nodes
 Decision alternatives – branches of the tree off
the decision nodes
 Chance events – events that could affect a
decision, branches or arrows leaving circular
chance nodes
 Outcomes – each possible alternative listed

18. 18
Decision tree diagrams
Decision trees developed by
 Drawing from left to right
 Use squares to indicate decision points
 Use circles to indicate chance events
 Write the probability of each chance by the
chance (sum of associated chances = 100%)
 Write each alternative outcome in the right
margin

19. 19
Example Using Decision Trees: A restaurant owner has
determined that she needs to expand her facility. The alternatives
are to expand large now and risk smaller demand, or expand on a
smaller scale now knowing that she might need to expand again in
three years. Which alternative would be most attractive? (see notes)

20. 20
Evaluating the Decision Tree
 Decision tree analysis utilizes expected value
analysis (EVA)
 EVA is a weighted average of the chance events
 Probability of occurrence * chance event outcome
 Refer to previous slide
 At decision point 2, choose to expand to maximize
profits ($200,000 > $150,000)
 Calculate expected value of small expansion:
 EVsmall = 0.30($80,000) + 0.70($200,000) = $164,000

21. 21
Evaluating the Decision
Tree con’t
 Calculate expected value of large expansion:
 EVlarge = 0.30($50,000) + 0.70($300,000) =
$225,000
 At decision point 1, compare alternatives &
choose the large expansion to maximize the
expected profit:
 $225,000 > $164,000
 Choose large expansion despite the fact that
there is a 30% chance it’s the worst decision:
 Take the calculated risk!

22. 22
Location Analysis
Three most important factors in real estate:
1. Location
2. Location
3. Location
Facility location is the process of identifying
the best geographic location for a service
or production facility

23. 23
Factors Affecting Location
Decisions
 Proximity to source of supply:
 Reduce transportation costs of perishable or bulky
raw materials
 Proximity to customers:
 High population areas, close to JIT partners
 Proximity to labor:
 Local wage rates, attitude toward unions,
availability of special skills (silicon valley)

24. 24
More Location Factors
 Community considerations:
 Local community’s attitude toward the facility (prisons,
utility plants, etc.)
 Site considerations:
 Local zoning & taxes, access to utilities, etc.
 Quality-of-life issues:
 Climate, cultural attractions, commuting time, etc.
 Other considerations:
 Options for future expansion, local competition, etc.

25. 25
Globalization –
Should Firm Go Global?
Globalization is the process of locating facilities
around the world
 Potential advantages:
 Inside track to foreign markets, avoid trade barriers, gain access
to cheaper labor
 Potential disadvantages:
 Political risks may increase, loss of control of proprietary
technology, local infrastructure (roads & utilities) may be
inadequate, high inflation
 Other issues to consider:
 Language barriers, different laws & regulations, different
business cultures

26. 26
Making Location Decisions
Analysis should follow 3 step process:
1. Identify dominant location factors
2. Develop location alternatives
3. Evaluate locations alternatives
Procedures for evaluation location alternatives
include
 Factor rating method
 Load-distance model
 Center of gravity approach
 Break-even analysis
 Transportation method

27. 27
Factor Rating Example

28. 28
A Load-Distance Model Example: Matrix Manufacturing is
considering where to locate its warehouse in order to service its four
Ohio stores located in Cleveland, Cincinnati, Columbus, Dayton. Two
sites are being considered; Mansfield and Springfield, Ohio. Use the
load-distance model to make the decision.
 Calculate the rectilinear distance:
 Multiply by the number of loads between each site and the four cities
miles
45
15
40
10
30
dAB 





29. 29
Calculating the Load-Distance Score
for Springfield vs. Mansfield

The load-distance score for Mansfield is higher than for
Springfield. The warehouse should be located in Springfield.
Computing the Load-Distance Score for Springfield
City Load Distance ld
Cleveland 15 20.5 307.5
Columbus 10 4.5 45
Cincinnati 12 7.5 90
Dayton 4 3.5 14
Total Load-Distance Score(456.5)
Computing the Load-Distance Score for Mansfield
City Load Distance ld
Cleveland 15 8 120
Columbus 10 8 80
Cincinnati 12 20 240
Dayton 4 16 64
Total Load-Distance Score(504)

30. 30
The Center of Gravity Approach
 This approach requires that the analyst find the center of
gravity of the geographic area being considered
 Computing the Center of Gravity for Matrix Manufacturing
 Is there another possible warehouse location closer to the C.G. that
should be considered?? Why?
10.6
41
436
l
Y
l
Y
;
7.9
41
325
l
X
l
X
i
i
i
c.g.
i
i
i
c.g. 









Computing the Center of Gravity for Matrix Manufacturing
Coordinates Load
Location (X,Y) (li) lixi liyi
Cleveland (11,22) 15 165 330
Columbus (10,7) 10 165 70
Cincinnati (4,1) 12 165 12
Dayton (3,6) 4 165 24
Total 41 325 436

31. 31
Break-Even Analysis
 Break-even analysis computes the amount of goods required
to be sold to just cover costs
 Break-even analysis includes fixed and variable costs
 Break-even analysis can be used for location analysis
especially when the costs of each location are known
Step 1: For each location, determine the fixed and
variable costs
Step 2: Plot the total costs for each location on one graph
Step 3: Identify ranges of output for which each location
has the lowest total cost
Step 4: Solve algebraically for the break-even points
over the identified ranges

32. 32
Break-Even Analysis
 Remember the break even equations used for calculation total
cost of each location and for calculating the breakeven
quantity Q.
 Total cost = F + cQ
 Total revenue = pQ
 Break-even is where Total Revenue = Total Cost
Q = F/(p-c)
Q = break-even quantity
p = price/unit
c = variable cost/unit
F = fixed cost

33. 33
Example using Break-even Analysis: Clean-Clothes
Cleaners is considering four possible sites for its new
operation. They expect to clean 10,000 garments. The
table and graph below are used for the analysis.
Example9.6UsingBreak-EvenAnalysis
Location FixedCost VariableCost TotalCost
A $350,000 $5(10,000) $400,000
B $170,000 $25(10,000) $420,000
C $100,000 $40(10,000) $500,000
D $250,000 $20(10,000) $450,000

34. 34
The Transportation Method
 Can be used to solve specific location problems
 Is discussed in detail in the supplement to this text
 Could be used to evaluate the cost impact of
adding potential location sites to the network of
existing facilities
 Could also be used to evaluate adding multiple
new sites or completely redesigning the network

35. 35
Capacity Planning & Facility
Location within OM
 Decisions about capacity and location are highly
dependent on forecasts of demand (Ch 8).
 Capacity is also affected by operations strategy (Ch
2), as size of capacity is a key element of
organizational structure.
 Other operations decisions that are affected by
capacity and location are issues of job design and
labor skills (Ch 11), choice on the mix of labor and
technology, as well as choices on technology and
automation (Ch 3).

36. 36
Capacity Planning and Facility
Location Across the Organization
 Capacity planning and location analysis
affect operations management and are
important to many others
 Finance provides input to finalize capacity
decisions
 Marketing impacted by the organizational
capacity and location to customers