1. Long-Range Capacity Planning
William J. Stevenson
9th edition

2. Learning Objectives Explain the importance of capacity planning.
Discuss ways of defining and measuring capacity.
Describe the determinants of effective capacity.
Discuss the major considerations related to developing capacity alternatives.
Briefly describe approaches that are useful for evaluating capacity alternatives

3. The Hierarchy of Production Decisions
All planning starts with the demand forecast.
Demand forecasts are the basis for the top level long_range capacity, and medium term aggregate planning.
The Master Production Schedule (MPS) is the result of disaggregating aggregate plans down to the individual item level.
Based on the MPS, MRP is used to determine the size and timing of component and subassembly production.
Detailed shop floor schedules are required to meet production plans resulting from the MRP.

4. Hierarchy of Production Decisions
Long-range Capacity Planning

5. Capacity Planning
Capacity is the upper limit or ceiling on the load that an operating unit can handle.
The basic questions in capacity handling are:
What kind of capacity is needed?
How much is needed? (Forecasts are key inputs)
When is it needed?

6. Importance of Capacity Decisions
Capacity decisions are important to all departments of the organization;
An accountant would be interested in collecting cost accounting information in order to ensure that correct capacity expansion decision is reached.

7. Importance of Capacity Decisions
Similarly a financial manager would be interested in performing the financial analysis of whether the investment decision is justified for a plant or capacity increase.

8. Importance of Capacity Decisions
An Information Technology Manager would end up preparing data bases that would aid the organization to decide about the capacity and last but not the least an operations manager would select strategies that would help the organization achieve the optimum capacity levels to meet the customer demand.

9. Importance of Capacity Decisions
Impacts ability to meet future demands
Affects operating costs
Major determinant of initial costs
Involves long-term commitment
Affects competitiveness
Affects ease of management
Globalization adds complexity
Impacts long range planning

10. Globalization adds complexity
Capacity decision often involves making a decision in a foreign country which requires the management to know about the political, economic and cultural issues.

11. Capacity Design capacity Effective capacity Actual output
maximum output rate or service capacity an operation, process, or facility is designed for
Effective capacity
Design capacity minus allowances such as personal time, maintenance, and scrap
Actual output
rate of output actually achieved--cannot exceed effective capacity.

12. Efficiency and Utilization
Actual output
Efficiency =
Effective capacity
Utilization =
Design capacity
Both measures expressed as percentages

13. Efficiency/Utilization Example
Design capacity = 50 trucks/day
Effective capacity = 40 trucks/day
Actual output = 36 units/day
Actual output = units/day
Efficiency = = 90%
Effective capacity units/ day
Utilization = Actual output = units/day
= 72% Design capacity units/day

14. Key Decisions of Capacity Planning
Amount of capacity needed
Timing of changes
Need to maintain balance
Extent of flexibility of facilities
Capacity cushion – extra demand intended to offset uncertainty
The greater the degree of demand uncertainity, the greater the
amount of cushion

15. Steps for Capacity Planning
Estimate future capacity requirements
Evaluate existing capacity
Identify alternatives
Conduct financial analysis
Assess key qualitative issues
Select one alternative
Implement alternative chosen
Monitor results

16. Calculating Processing Requirements
If annual capacity is 2000 (8hr/day*250 days *1 machine) hours, then we need
three machines to handle the required volume:
5,800 hours/2,000 hours = 2.90 machines

17. Planning Service Capacity
Need to be near customers
Capacity and location are closely tied
Inability to store services
Capacity must be matched with timing of demand
Degree of volatility of demand
Peak demand periods

18. Make or Buy?
Available capacity. If an organization has available the equipment, necessary skills, and time, it often makes sense to produce an item or perform a service in-house.
Expertise. If a firm lacks the expertise to do a job satisfactorily, buying might be a reasonable alternative.
Quality considerations. Firms that specialize can usually offer higher quality than an organization can attain itself. Conversely, unique quality requirements or the desire to closely monitor quality may cause an organization to perform a job itself.
The nature of demand. When demand for an item is high and steady, the organization is often better off doing the work itself. However, wide fluctuations in demand or small orders are usually better handled by specialists who are able to combine orders from multiple sources, which results in higher volume and tends to offset individual buyer fluctuations.
Cost. Cost savings might come from the item itself or from transportation cost savings. If there are fixed costs associated with making an item that cannot be reallocated if the service or product is outsourced, that has to be recognized in the analysis. Conversely, outsourcing may help a firm avoid incurring fixed costs.
Risk. Outsourcing may involve certain risks. One is loss of control over operations. Another is the need to disclose proprietary information.

19. Capacity Planning Based-on Bottleneck Operation
Figure 5.2
Bottleneck operation: An operation in a sequence of operations whose capacity is lower than that of the other operations
Bottleneck
Operation
Machine #1
Machine #3
Machine #4
10/hr
30/hr
Machine #2

20. Bottleneck Operation Operation 1 20/hr. Operation 2 10/hr.
Maximum output rate limited by bottleneck

21. Developing Capacity Alternatives
1. Design flexibility into systems
2. Take stage of life cycle into account
3. Take a “big picture” approach to capacity changes
4.Prepare to deal with capacity “chunks”
5. Attempt to smooth out capacity requirements
(due to random variations or seasonal variations)
6. Identify the optimal operating level

22. Prepare to deal with capacity “chunks
Prepare to deal with capacity “chunks.” Capacity increases are often acquired in fairly large chunks rather than smooth increments, making it difficult to achieve a match between desired capacity and feasible capacity. Attempt to smooth out capacity requirements. Unevenness in capacity requirements also can create certain problems.

23. Economies of Scale Economies of scale Diseconomies of scale
If the output rate is less than the optimal level, increasing output rate results in decreasing average unit costs. This results from fixed costs, labor cost being spread over more units
Diseconomies of scale
If the output rate is more than the optimal level, increasing the output rate results in increasing average unit costs. Due to scheduling problems, quality problems, reduced morale, increased use of overtime.

24. Evaluating Alternatives
Figure 5.3
Production units have an optimal rate of output for minimal cost.
Minimum
cost
Average cost per unit
Rate of output
Minimum average cost per unit

25. Economies and Diseconomies of Scale
Average Unit
Cost of Output ($)
Economies
of Scale
Diseconomies
of Scale
Best Operating Level
Annual Volume (units)

26. Larger Plants Tend to Have Higher Optimal Output Rates
Figure 5.4
Minimum cost & optimal operating rate are
functions of size of production unit.
Small
plant
Average cost per unit
Medium
plant
Large
plant
Output rate

27. Evaluating Alternatives
Cost-volume analysis
Break-even point
Financial analysis
Cash flow
Present value
Decision theory
Waiting-line analysis
Simulation

28. Assumptions of Cost-Volume Analysis
One product is involved
Everything produced can be sold
Variable cost per unit is the same regardless of volume
Fixed costs do not change with volume
Revenue per unit constant with volume
Revenue per unit exceeds variable cost per unit

29. Cost-Volume Relationships
Figure 5.5a
Amount ($)
Q (volume in units)
Total cost = VC + FC
Total variable cost (VC)
Fixed cost (FC)

30. Cost-Volume Relationships
Figure 5.5b
Amount ($)
Q (volume in units)
Total revenue

31. Cost-Volume Relationships
Figure 5.5c
Amount ($)
Q (volume in units)
BEP units
Profit
Total revenue
Total cost

32. Break-Even Problem with Step Fixed Costs
Figure 5.6a
Quantity
FC + VC = TC
Step fixed costs and variable costs.
1 machine
2 machines
3 machines

33. Break-Even Problem with Step Fixed Costs
Figure 5.6b $ TC
BEP 2 3 TR
Quantity 1
Multiple break-even points

34. Example 4: page 195
A manager has the option of purchasing one, two, or three machines.
# of mach Tot. Annual FC Correspond. Output
$ – 300
– 900
Variable cost is $10, revenue is $40 per unit.
Determine the break-even point for each range.
If projected demand is between 580 and 660 units, how many machines should the manager purchase?

35. Example 2 a) For one machine Q = 9600/(40-10)= 320 units
For two machines Q= 15000/(40-10)= 500 units
For three machines Q=20000/(40-10)= units
b) Manager should choose two machines. Because even if demand is at low end of the range (i.e., 580), it would be above the break-even point and thus yield a profit. If three machines are purchased, even at the top end of projected demand (i.e., 660), the volume would still be less than the break-even point for that range, so there would be no profit.

36. Financial Analysis
Cash Flow - the difference between cash received from sales and other sources, and cash outflow for labor, material, overhead, and taxes.
Present Value - the sum, in current value, of all future cash flows of an investment proposal.

37. Decision Tree Analysis
Structures complex, multiphase decisions
Allows objective evaluation of alternatives
Incorporates uncertainty
Develops expected values

38. Example: Decision Tree Analysis
Good Eats Café is about to build a new restaurant. An architect has developed three building designs, each with a different seating capacity. Good Eats estimates that the average number of customers per hour will be 80, 100, or 120 with respective probabilities of 0.4, 0.2, and The payoff table showing the profits for the three designs is on the next slide.

39. Example: Decision Tree Analysis
Payoff Table
Average Number of Customers Per Hour
c1 = c2 = c3 = 120
Design A $10, $15, $14,000
Design B $ 8, $18, $12,000
Design C $ 6, $16, $21,000

40. Example: Decision Tree Analysis
Expected Value For Each Decision
Choose the design with largest EV -- Design C.
EV = .4(10,000) + .2(15,000) + .4(14,000)
= $12,600 d1 2
Design A
EV = .4(8,000) + .2(18,000) + .4(12,000)
= $11,600
Design B d2 1 3 d3
Design C
EV = .4(6,000) + .2(16,000) + .4(21,000)
= $14,000 4

41. Waiting-Line Analysis
Useful for designing or modifying service systems
Waiting-lines occur across a wide variety of service systems
Waiting-lines are caused by bottlenecks in the process
Helps managers plan capacity level that will be cost-effective by balancing the cost of having customers wait in line with the cost of additional capacity