Transcript Chapter 7– Capacity Planning & Facility Location

Chapter 9
Capacity Planning
& Facility Location
© Wiley 2007
OUTLINE
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Capacity Planning
Making Capacity Planning Decisions
Decision Trees
Location Analysis
Making Location Decisions
Capacity Planning and Facility Location Across
the Organization
© Wiley 2007
Capacity Planning
Capacity planning
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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
© Wiley 2007
Measuring Capacity Examples
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There is no one best way to measure capacity
Output measures like kegs per day are easier to understand
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With multiple products, inputs measures work better
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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
© Wiley 2007
Measuring Available Capacity
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Design capacity:
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Maximum output rate under ideal conditions
A bakery can make 30 custom cakes per day
when pushed at holiday time
Effective capacity:
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Maximum output rate under normal (realistic)
conditions
On the average this bakery can make 20
custom cakes per day
© Wiley 2007
Calculating Capacity Utilization
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Measures how much of the available
capacity is actually being used:
actual output rate
100%
Utiliz atio
n
capacity
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Measures effectiveness
Use either effective or design capacity in
denominator
© Wiley 2007
Example of Computing Capacity Utilization: In the bakery
example the 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?
Utiliz atio
n effective 
Utiliz atio
n design
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actual output
28
(100%)  (100%)  140%
e ffe ctivecapacity
20
actual output
28
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(100%)  (100%)  93%
de sign capacity
30
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
© Wiley 2007
How Much Capacity Is Best?
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The Best Operating Level is the output that results in
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Economies of Scale:
the lowest average unit cost
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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:
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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
© Wiley 2007
Best Operating Level and Size
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Alternative 1: Purchase one large facility, requiring one large
initial investment
Alternative 2: Add capacity incrementally in smaller chunks as
needed
© Wiley 2007
Other Capacity Considerations
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Focused factories:
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Plant within a plant (PWP):
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Small, specialized facilities with limited
objectives
Segmenting larger operations into smaller
operating units with focused objectives
Subcontractor networks:
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Outsource non-core items to free up
capacity for what you do well
© Wiley 2007
Making Capacity Planning Decisions
Making Capacity Planning Decisions
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The three-step procedure for making
capacity planning decisions is as
follows:
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Step 1: Identify Capacity Requirements
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Step 2: Develop Capacity Alternatives
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Step 3: Evaluate Capacity Alternatives
© Wiley 2007
Identifying capacity
requirements
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Long-term capacity requirements based on
future demand
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Identifying future demand based on forecasting
Forecasting, at this level, relies on qualitative
forecast models
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Executive opinion
Delphi method
Forecast and capacity decision must included
strategic implications
Capacity cushions
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Plan to underutilize capacity to provide flexibility
© Wiley 2007
Evaluating Capacity Alternatives
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Capacity alternatives include
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Could do nothing,
expand large now (may included
capacity cushion), or
expand small now with option to add
later
© Wiley 2007
Evaluating Capacity Alternatives
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Many tools exist to assist in evaluating
alternatives
Most popular tool is Decision Trees
Decision Trees analysis tool is:
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a modeling tool for evaluating sequential
decisions which,
identifies the alternatives at each point in time
(decision points), estimate probable
consequences of each decision (chance events)
& the ultimate outcomes (e.g.: profit or loss)
© Wiley 2007
Decision Trees
Decision tree diagrams
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Diagramming technique which uses
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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
© Wiley 2007
Decision tree diagrams
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Decision trees developed by
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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
© Wiley 2007
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?
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The likelihood of demand being high is .70
The likelihood of demand being low is .30
Large expansion yields profits of $300K(high dem.) or $50k(low dem.)
Small expansion yields profits of $80K if demand is low
Small expansion followed by high demand and later expansion yield a profit of
$200K at that point. No expansion at that point yields profit of $150K
© Wiley 2007
Evaluating the Decision Tree
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Decision tree analysis utilizes expected value
analysis (EVA)
EVA is a weighted average of the chance events
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Probability of occurrence * chance event outcome
Refer to Figure 9-3
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At decision point 2, choose to expand to maximize
profits ($200,000 > $150,000)
Calculate expected value of small expansion:
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EVsmall = 0.30($80,000) + 0.70($200,000) = $164,000
© Wiley 2007
Evaluating the Decision Tree continued
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Calculate expected value of large expansion:
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EVlarge = 0.30($50,000) + 0.70($300,000) =
$225,000
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At decision point 1, compare alternatives &
choose the large expansion to maximize the
expected profit:
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$225,000 > $164,000
Choose large expansion despite the fact that
there is a 30% chance it’s the worst decision:
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Take the calculated risk!
© Wiley 2007
Location Analysis
Location Analysis
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Three most important factors in real
estate:
1.
2.
3.
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Location
Location
Location
Facility location is the process of
identifying the best geographic location
for a service or production facility
© Wiley 2007
Factors Affecting Location
Decisions
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Proximity to source of supply:
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Proximity to customers:
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Reduce transportation costs of perishable or bulky
raw materials
E.g.: high population areas, close to JIT partners
Proximity to labor:
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Local wage rates, attitude toward unions,
availability of special skills (e.g.: silicon valley)
© Wiley 2007
More Location Factors
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Community considerations:
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Site considerations:
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Local zoning & taxes, access to utilities, etc.
Quality-of-life issues:
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Local community’s attitude toward the facility (e.g.:
prisons, utility plants, etc.)
Climate, cultural attractions, commuting time, etc.
Other considerations:
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Options for future expansion, local competition, etc.
© Wiley 2007
Globalization - Should Firm Go
Global?
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Globalization is the process of locating facilities
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Potential advantages:
around the world
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Potential disadvantages:
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Inside track to foreign markets, avoid trade barriers, gain access
to cheaper labor
Political risks may increase, loss of control of proprietary
technology, local infrastructure (roads & utilities) may be
inadequate, high inflation
Other issues:
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Language barriers, different laws & regulations, different
business cultures
© Wiley 2007
Making Location Decisions
Making Location Decisions
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Analysis should follow 3 step process:
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Step 1: Identify dominant location factors
Step 2: Develop location alternatives
Step 3: Evaluate locations alternatives
Procedures for evaluation location alternatives
include
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Factor rating method
Load-distance model
Center of gravity approach
Break-even analysis
Transportation method
© Wiley 2007
Factor Rating Example
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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.
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Calculate the rectilinear distance: dAB  30  10  40  15  45 miles
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Multiply by the number of loads between each site and the four cities
© Wiley 2007
Calculating the Load-Distance Score
for Springfield vs. Mansfield
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)
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The load-distance score for Mansfield is higher than for
Springfield. The warehouse should be located in Springfield.
© Wiley 2007
The Center of Gravity Approach
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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
Location
Cleveland
Columbus
Cincinnati
Dayton
Coordinates
Load
(X,Y)
(11,22)
(10,7)
(4,1)
(3,6)
(li)
15
10
12
4
41
Total
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liyi
330
70
12
24
436
Computing the Center of Gravity for Matrix
Manufacturing
Xc.g.
l X 325
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 7.9 ; Y
 l 41
i
i
c.g.
i
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lixi
165
165 100
165 48
165 12
325
lY
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l
i
i
i
436
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 10.6
41
Is there another possible warehouse location closer to the
© Wiley 2007
C.G. that should be considered??
Why?
Break-Even Analysis
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Break-even analysis computes the amount of goods required
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Break-even analysis includes fixed and variable costs
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Break-even analysis can be used for location analysis
especially when the costs of each location are known
to be sold to just cover costs
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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
© Wiley 2007
Break-Even Analysis
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Remember the break even equations used for calculation total
cost of each location and for calculating the breakeven
quantity Q.
 Total cost = F + cQ
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Total revenue = pQ
Break-even is where Total Revenue = Total Cost
Q = break-even quantity
p = price/unit
c = variable cost/unit
F = fixed cost
Q = F/(p-c)
© Wiley 2007
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.
Example 9.6 Using Break-Even Analysis
Location Fixed Cost Variable Cost Total Cost
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
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From the graph you can see that the two lowest cost intersections
occur between C & B (4667 units) and B & A (9000 units)
The best alternative up to 4667 units is C, between 4667 and 9000
units the best is B, and above 9000
units
© Wiley
2007 the best site is A
The Transportation Method
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The transportation method of linear programming
can be used to solve specific location problems
It is discussed in detail in the supplement to this
text
It could be used to evaluate the cost impact of
adding potential location sites to the network of
existing facilities
It could also be used to evaluate adding multiple
new sites or completely redesigning the network
© Wiley 2007
Capacity Planning and Facility
Location Across the Organization
Capacity Planning and Facility
Location Across the Organization
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Capacity planning and location analysis
affect operations management and are
important to many others
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Finance provides input to finalize capacity
decisions
Marketing impacted by the organizational
capacity and location to customers
© Wiley 2007
End of The Lecture
© Wiley 2007