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© Wiley 2007
Chapter 9
Capacity Planning & Facility
Location
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OUTLINE
Capacity Planning Making Capacity Planning Decisions Decision Trees Location Analysis Making Location Decisions Capacity Planning and Facility Location
Across the Organization
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Capacity Planning
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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
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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 BusinessInput Measures of
CapacityOutput Measures
of Capacity
Car manufacturer Labor hours Cars per shift
Hospital Available beds Patients per month
Pizza parlor Labor hours Pizzas per day
Retail storeFloor space in square feet
Revenue per foot
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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
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Calculating Capacity Utilization Measures how much of the available
capacity is actually being used:
Measures effectiveness Use either effective or design
capacity in denominator
100%capacity
rateoutput actualnUtilizatio
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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?
93%(100%)30
28(100%)
capacity design
output actual nUtilizatio
140%(100%)20
28(100%)
capacity effective
output actual nUtilizatio
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
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How Much Capacity Is Best?
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
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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
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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
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Making Capacity Planning Decisions
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Making Capacity Planning Decisions
The three-step procedure for making capacity planning decisions is as follows: Step 1: Identify Capacity Requirements Step 2: Develop Capacity Alternatives Step 3: Evaluate Capacity Alternatives
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Identifying capacity requirements 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
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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
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Evaluating Capacity Alternatives
Many tools exist to assist in evaluating alternatives
Most popular tool is Decision Trees Decision Trees analysis tool is:
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)
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Decision Trees
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Decision tree diagrams 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
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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
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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?
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
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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 Figure 9-3 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
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Evaluating the Decision Tree - continued
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!
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Location Analysis
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Location Analysis Three most important factors in
real estate:1. Location2. Location3. Location
Facility location is the process of identifying the best geographic location for a service or production facility
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Factors Affecting Location Decisions Proximity to source of supply:
Reduce transportation costs of perishable or bulky raw materials
Proximity to customers: E.g.: high population areas, close to JIT
partners Proximity to labor:
Local wage rates, attitude toward unions, availability of special skills (e.g.: silicon valley)
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More Location Factors Community considerations:
Local community’s attitude toward the facility (e.g.: 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.
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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: Language barriers, different laws & regulations, different
business cultures
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Making Location Decisions
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Making Location Decisions Analysis should follow 3 step process:
Step 1: Identify dominant location factors Step 2: Develop location alternatives Step 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
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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.
Calculate the rectilinear distance:
Multiply by the number of loads between each site and the
four cities
miles 4515401030dAB
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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 SpringfieldCity Load Distance ld
Cleveland 15 20.5 307.5Columbus 10 4.5 45Cincinnati 12 7.5 90Dayton 4 3.5 14
Total Load-Distance Score(456.5)
Computing the Load-Distance Score for MansfieldCity Load Distance ld
Cleveland 15 8 120Columbus 10 8 80Cincinnati 12 20 240Dayton 4 16 64
Total Load-Distance Score(504)
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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?
10.641
436
l
YlY ; 7.9
41
325
l
XlX
i
iic.g.
i
iic.g.
Computing the Center of Gravity for Matrix ManufacturingCoordinates Load
Location (X,Y) (li) lixi liyi
Cleveland (11,22) 15 165 330Columbus (10,7) 10 165 70Cincinnati (4,1) 12 165 12
Dayton (3,6) 4 165 24Total 41 325 436
100
48
12
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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
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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 quantityp = price/unitc = variable cost/unitF = fixed cost
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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 AnalysisLocation Fixed Cost Variable Cost Total Cost
A $350,000 $ 5(10,000) $400,000B $170,000 $25(10,000) $420,000C $100,000 $40(10,000) $500,000D $250,000 $20(10,000) $450,000
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 the best site is A
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The Transportation Method
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
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Capacity Planning and Facility Location Across the Organization
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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
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End of The Lecture