1. Capacity
After deciding what products/services should be offered and how they should be made, management must plan the capacity of its processes.
Capacity is the maximum rate of output for a process. Must have capacity to meet current and future demands. Long-term capacity plans deal with investments in new facilities and equipment. Short-term capacity plans focus on workforce size, overtime budgets, and inventories.
This presentation covers the material in Chapter 8, Capacity. The graphic is a mock decision tree. 1

2. Capacity Planning
This activity is central to the long-term success of an organization.
Too much capacity can be as problematic as too little
Capacity planning considers questions such as:
How much of a cushion is needed?
Should we expand capacity before the demand is there or wait until demand is more certain?

3. Capacity Planning
Capacity can be defined as the ability to hold, receive, store, or accommodate.
Strategic capacity planning is an approach for determining the overall capacity level of capital intensive resources, including facilities, equipment, and overall labor force size.

4. Measuring capacity
No single capacity measure is universally applicable.
Capacity can be expressed in terms of outputs or inputs.
Output measures—the usual choice for line flow processes, usually high-volume
Low amount of customization
Product mix becomes an issue when the output is not uniform in work content.
Input measures—used for flexible flow, low-volume processes
High amount of customization
Output varies in work content; a measure of total units produced is meaningless.
Output is converted to some critical homogeneous input, such as labor hours or machine hours.

5. Utilization Fabrication can make 100 engines/day
Management wants 45 engines/day
Currently producing 50 engines/day
Utilizationpeak =
Average output rate
Peak capacity
x 100%
And this is the basic equation for Utilization. In this application we are looking at utilization with respect to the designed capacity of the system.
Utilizationeffective =
Average output rate
Effective capacity
x 100% 4

6. Utilization Fabrication can make 100 engines/day
Management wants 45 engines/day
Currently producing 50 engines/day 50
100
Utilizationpeak = x 100% = 50%
We solve for the utilization. 50 45
Utilizationeffective = x 100% = 111%
The average output rate and the capacity must be measured in the same terms. 9

7. Types of Capacity Peak capacity Effective capacity
Calling for extraordinary effort under ideal conditions that are not sustainable
Allows for downtime for maintenance and repair.
Engineering assessment of maximum annual output
Effective capacity
Economically sustainable under normal conditions

8. Utilization
This slide presents the output of the OM Explorer Capacity Utilization analysis showing the same results we obtained manually
What does it mean? Even through the department falls well short of peak capacity, it is well beyond the output rate judged to be most economical. It’s operations could be sustained at that level only through the use of considerable overtime; capacity expansion should be evaluated. 13

9. Utilization Utilizationpeak = 50% Utilizationeffective = 111%
Capacity cushion – amount of reserve capacity that a firm maintains to handle sudden increases in demand or temporary loss of production capacity.
We find the capacity cushions are as shown. This might support an extended discussion of the implications of a negative capacity cushion.
Capacity cushionpeak = 100% – 50% = 50%
Capacity cushioneffective = 100% – 111% = – 11% 13

10. Best Operating Level Average unit cost of output Underutilization
Overutilization
Best Operating
Level
Volume 4

11. Capacity Bottlenecks
“A bottleneck is an operation that has the lowest effective capacity of any operation in the facility and thus limits the system’s output.”
Inputs
To customers
(a) Operation 2 a bottleneck
50/hr 1 2 3
200/hr
This slide and the next are based on Figure 8.2. The Figure is shown in two sections to improve legibility. 14

12. Capacity Bottlenecks 2 3 1 Inputs To customers 200/hr
(b) All operations bottlenecks
In effect, the process can produce only as fast as the slowest operation. True expansion of a process’s capacity occurs only when bottleneck capacity is increased. In the first slide, adding capacity at Operation 1 or 3 will not impact system capacity. However, when adding capacity to Operation 2, must then increase capacity at all 3 operations to increase capacity further.
To increase capacity: new equipment, new facilities, expanded operating hours, increased shifts, increased work hours, or redesign the process 15

13. Theory of Constraints
Focus is on whatever impedes, (i.e., bottlenecks) progress toward the goal of maximizing flow of total value-added funds (sales less discounts and variable costs)
The focus on bottlenecks is the means to increase throughput and, consequently, the flow of value added funds.
The performance of the overall system is a function of how bottleneck operations or processes are scheduled.

14. Theory of Constraints
Short-term: overtime, temporary employees, outsource
Increase effective capacity utilization at bottlenecks without experiencing the higher costs and poor customer service usually associated with maintaining output rates at peak capacity.
Carefully monitor short-term schedules, minimize idle time, setups (changes from one product to another).

15. Theory of Constraints Identify the system bottleneck(s)
Exploit the bottleneck(s)
Subordinate all other decisions to step 2
Elevate the bottleneck(s)
Do not let inertia set in
This slide presents the basic elements of the Theory of Constraints as listed in the text. 14

16. Economies of Scale
Increasing output rate decreases the average unit cost
Fixed costs are spread over more units
Construction costs are reduced
Costs of purchased materials are cut
Process advantages are found

17. Diseconomies of Scale
When the average costs per unit increases as the facility’s size increases.
Excessive size can bring complexity, loss of focus, and inefficiencies, which raise the average unit cost.
Characterized by loss of agility, less innovation, risk avoidance, and excessive analysis and planning at the expense of action.
Nonlinear growth of overhead leads to employee ceilings.

18. Average unit cost (dollars per patient)
Economies and Diseconomies of Scale
Best operating level is 500-beds; optimal depends on number of patients per week.
250-bed hospital
750-bed hospital
500-bed hospital
Average unit cost (dollars per patient)
The extended overall cost curve shows diseconomies of scale in this size range.
Economies of scale
Diseconomies of scale
Output rate (patients per week) 21

19. Capacity strategy Sizing capacity cushions
Average utilization rates near 100% indicate:
Need to increase capacity
Poor customer service or declining productivity
Utilization rates tend to be higher in capital-intensive industries.

20. Capacity Strategy Factors Leading to Large Capacity Cushions
When demand is variable, uncertain, or product mix changes
When finished goods inventory cannot be stored
When customer service is important
When capacity comes in large increments
When supply of material or human resources is uncertain
Factors leading to small capacity cushions
Unused capacity costs money.
Large cushions hide inefficiencies, absenteeism, unreliable material supply.
When subcontractors are available to handle demand peaks

21. Capacity Strategy Timing and sizing of expansion Expansionist strategy
Keeps ahead of demand, maintains a capacity cushion
Large, infrequent jumps in capacity
Higher financial risk
Lower risk of losing market share
Economies of scale may reduce fixed cost per unit
May increase learning and help compete on price
Preemptive marketing

22. Capacity Strategy Wait-and-see strategy
Lags behind demand, relying on short-term peak capacity options (overtime, subcontractors) to meet demand
Lower financial risk associated with overly optimistic demand forecast
Lower risk of a technological advancement making a new facility obsolete
Higher risk of losing market share
Follow-the-leader strategy
An intermediate strategy of copying competitors’ actions
Tends to prevent anyone from gaining a competitive advantage

23. Capacity Strategies Forecast of capacity required
Planned unused capacity
Forecast of capacity required
Capacity increment
Capacity
Time between increments
We add in the details describing the various components of the graph.
Time
(a) Expansionist strategy 26

24. Capacity Strategies Forecast of capacity required
Planned use of short-term options
Forecast of capacity required
Capacity increment
Capacity
Time between increments
The detailed descriptions are added in this slide.
Time
(b) Wait-and-see strategy 29

25. Linking Capacity and Other Decisions
Competitive Priorities
Quality Management
Capital Intensity
Resource Flexibility
Inventory
Scheduling
The authors present a systematic approach to capacity decisions and this series of slides supports that discussion. This slide advances automatically. 30

26. [Dp + (D/Q)s]product 1 + ... + [Dp + (D/Q)s]product n
Capacity Decisions
Estimate Capacity Requirements
Item Client X Client Y
Annual demand forecast (copies)
Standard processing time (hour/copy)
Average lot size (copies per report)
Standard setup time (hours)
We need to determine the number of machines required for this set of tasks. This is the basic equation. Note, this has been shortened from the example in the book due to space limitations.
[Dp + (D/Q)s]product [Dp + (D/Q)s]product n
N[1 – (C/100)]
M = 32

27. (250 days/year)(1 shift/day)(8 hours/shift)(1.0 – 15/100)
Capacity Decisions
Estimate Capacity Requirements
Item Client X Client Y
Annual demand forecast (copies)
Standard processing time (hour/copy)
Average lot size (copies per report)
Standard setup time (hours)
This slide allows for a detailed discussion of the equation.
M =
[2000(0.5) + (2000/20)(0.25)]client X + [6000(0.7) + (6000/30)(0.4)]client Y
(250 days/year)(1 shift/day)(8 hours/shift)(1.0 – 15/100) 34

28. Capacity Decisions Estimate Capacity Requirements
Item Client X Client Y
Annual demand forecast (copies)
Standard processing time (hour/copy)
Average lot size (copies per report)
Standard setup time (hours)
The equation is solved and the number of machines is known. Notice the rounding up, necessary to actually meet the capacity requirements.
M = =  4 machines
5305
1700
Example 8.2 35

29. Capacity Decisions Identify Capacity Gaps
Kitchen capacity = 80,000 meals
Dining room capacity = 105,000 meals
Demand
Year 1: 90,000 meals
Year 2: 100,000 meals
Year 3: 110,000 meals
Year 4: 120,000 meals
Year 5: 130,000 meals
Kitchen Capacity Gaps
Year 1: 90,000 – 80,000 = 10,000
Year 2: 100,000 – 80,000 = 20,000
Year 3: 110,000 – 80,000 = 30,000
Year 4: 120,000 – 80,000 = 40,000
Year 5: 130,000 – 80,000 = 50,000
This slide completes the analysis for all five years. 41

30. Capacity Decisions Identify Capacity Gaps
Kitchen capacity = 80,000 meals
Dining room capacity = 105,000 meals
Demand
Year 1: 90,000 meals
Year 2: 100,000 meals
Year 3: 110,000 meals
Year 4: 120,000 meals
Year 5: 130,000 meals
Dining Room Capacity Gaps
Year 1: no gaps
Year 2: no gaps
Year 3: 110,000 – 105,000 = 5,000
Year 4: 120,000 – 105,000 = 15,000
Year 5: 130,000 – 105,000 = 25,000
And this slide completes the analysis. 45

31. Expand capacity to meet expected demand through Year 5
Capacity Decisions
Evaluate Alternatives
Expand capacity to meet expected demand through Year 5
Year Demand Cash Flow
1 90,000 (90,000 – 80,000)2 = $20,000
2 100,000 (100,000 – 80,000)2 = $40,000
3 110,000 (110,000 – 80,000)2 = $60,000
4 120,000 (120,000 – 80,000)2 = $80,000
5 130,000 (130,000 – 80,000)2 = $100,000
This slide completes the analysis. It might be important to stress that such an analysis is only valuable in-so-far as it is measured against other alternatives or some pre-defined standard. Students with some background in finance might point out that this is a simplistic example but as long as one methodology is applied consistently, the comparison between alternatives should be meaningful. 50

32. Capacity Decisions Evaluate Alternatives
This slide shows the results of this analysis using the OM Explorer software. 50

33. Capacity Decisions Simulation TIME TO PERFORM (SECONDS) Standard
OPERATION Average Deviation
Review renewal application for correctness 15 3
Check file for violations and restrictions 60 15
Process and record payment 25 6
Conduct eye test 35 10
Photograph applicant 20 5
Issue temporary license 30 5
The example starts with the basic data about the operation.
AVERAGE CUSTOMER ARRIVAL
TIME (PEOPLE PER MINUTE)
8:00 A.M. — 9:00 A.M. 1.25
9:00 A.M. — 12:00 P.M. 0.75
12:00 P.M. — 1:00 P.M. 2.00
1:00 P.M. — 4:00 P.M. 0.75 51

34. Capacity Decisions Bottleneck
These two slides support Solved Problem 1 at the end of the Chapter. 51

35. Capacity Decisions
Bottleneck 51