1. Capacity Planning & Facility Location
Chapter 9
Capacity Planning & Facility Location
© Wiley 2007

2. OUTLINE Capacity Planning Making Capacity Planning Decisions
Decision Trees
Location Analysis
Making Location Decisions
Capacity Planning and Facility Location Across the Organization
© Wiley 2007

3. Capacity Planning

4. 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
© Wiley 2007

5. 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
© Wiley 2007

6. 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
© Wiley 2007

7. Calculating Capacity Utilization
Measures how much of the available capacity is actually being used:
Measures effectiveness
Use either effective or design capacity in denominator
© Wiley 2007

8. The bakery can only operate at this level for a short period of time
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?
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

9. 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
© Wiley 2007

10. 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
© Wiley 2007

11. 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
© Wiley 2007

12. Making Capacity Planning Decisions

13. 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
© Wiley 2007

14. 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
© Wiley 2007

15. 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
© Wiley 2007

16. 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)
© Wiley 2007

17. Decision Trees

18. 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
© Wiley 2007

19. 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
© Wiley 2007

20. 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
© Wiley 2007

21. 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) ($200,000) = $164,000
© Wiley 2007

22. Evaluating the Decision Tree - continued
Calculate expected value of large expansion:
EVlarge = 0.30($50,000) ($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!
© Wiley 2007

23. Location Analysis

24. Location Analysis Three most important factors in real estate:
Facility location is the process of identifying the best geographic location for a service or production facility
© Wiley 2007

25. 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)
© Wiley 2007

26. More Location Factors Community considerations: Site 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.
© Wiley 2007

27. 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
© Wiley 2007

28. Making Location Decisions

29. 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
© Wiley 2007

30. Factor Rating Example
© Wiley 2007

31. Calculate the rectilinear distance:
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
© Wiley 2007

32. 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.
© Wiley 2007

33. 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?
100 48 12
© Wiley 2007

34. 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
© Wiley 2007

35. 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
© Wiley 2007

36. 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.
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
© Wiley 2007

37. 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
© Wiley 2007

38. Capacity Planning and Facility Location Across the Organization

39. 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
© Wiley 2007

40. End of The Lecture
© Wiley 2007