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Capacity Planning

Chapter 4

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What is Capacity?

Capacity

The maximum rate of output of a process or a system.

Strategic capacity planning

is an approach for determining the overall capacity level of capital intensive resources, including facilities, equipment, and overall labor force size

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What is Capacity Management?

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Measures of Capacity and Utilization

Output Measures of Capacity

Input Measures of Capacity

Utilization

Utilization =  100%

Average output rate

Maximum capacity

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Measures of Capacity

Use Output Measures when:

The firm uses high volume, standardized processes

Use Input Measures when:

The firm uses low-volume, flexible processes

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Economies and Diseconomies of Scale

Economies of scale

Spreading fixed costs

Reducing construction costs

Cutting costs of purchased materials

Finding process advantages

Diseconomies of scale

Complexity

Loss of focus

Inefficiencies

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Economies and Diseconomies of Scale

Figure 4.1

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Capacity Timing and Sizing Strategies

Sizing Capacity Cushions

Timing and Sizing Expansion

Linking Process Capacity and Other Decisions

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Sizing Capacity Cushions

Capacity cushions – the amount of reserve capacity a process uses to handle sudden increases in demand or temporary losses of production capacity.

It measures the amount by which the average utilization (in terms of total capacity) falls below 100 percent. (should average 70-80%)

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Sizing Capacity Cushions

Capacity cushion =

100% – Average Utilization rate (%)

Capacity cushions vary with industry

Capital intensive industries prefer cushions well under 10 percent while hotel industry can live with 30 to 40 percent cushion.

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Capacity Timing and Sizing

Planned unused capacity

Time

Capacity

Forecast of capacity required

Time between increments

Capacity increment

(a) Expansionist strategy

Figure 4.2

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Time

Capacity

(b) Wait-and-see strategy

Planned use of short-term options

Time between increments

Capacity increment

Capacity Timing and Sizing

Forecast of capacity required

Figure 4.2

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A Systematic Approach to Long-Term Capacity Decisions

Estimate future capacity requirements

Identify gaps by comparing requirements with available capacity

Develop alternative plans for reducing the gaps

Evaluate each alternative, both qualitatively and quantitatively, and make a final choice

All a part of the Strategic Management Process

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Step 1 - Estimate Capacity Requirements

For one service or product processed at one operation with a one year time period, the capacity requirement, M, is

Capacity requirement

Processing hours required for year’s demand

Hours available from a single capacity unit (such as an employee or machine) per year, after deducting desired cushion

M =

N[1 – (C/100)]

where

D = demand forecast for the year (number of customers served or units produced)

p = processing time (in hours per customer served or unit produced)

N = total number of hours per year during which the process operates

C = desired capacity cushion (expressed as a percent)

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Step 1 - Estimate Capacity Requirements

Setup times may be required if multiple products are produced

Set-up times are a prime opportunity to increase capacity

If you can minimize set-up times you get capacity back

As an example P&G took on a Total Quality project to reduce line change-overs (or the time to breakdown one product and set-up for another) and were able to reduce an average 2 day change-over to 2 hours.

This provided each of these manufacturing lines with 46 extra hours of capacity.

How could this new excess capacity be used?

Making additional volume as the company grows (less of a need to build/buy new capacity)

Making new products

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Example 4.1

A copy center in an office building prepares bound reports for two clients. The center makes multiple copies (the lot size) of each report. The processing time to run, collate, and bind each copy depends on, among other factors, the number of pages. The center operates 250 days per year, with one 8-hour shift. Management believes that a capacity cushion of 15 percent (beyond the allowance built into time standards) is best. It currently has three copy machines. Based on the following information, determine how many machines are needed at the copy center.

Item	Client X	Client Y
Annual demand forecast (copies)	2,000	6,000
Standard processing time (hour/copy)	0.5	0.7
Average lot size (copies per report)	20	30
Standard setup time (hours)	0.25	0.40

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Example 4.1

M =

[Dp + (D/Q)s]product 1 + [Dp + (D/Q)s]product 1 + … + [Dp + (D/Q)s]product n

N[1 – (C/100)]

[2,000(0.5) + (2,000/20)(0.25)]client X

+ [6,000(0.7) + (6,000/30)(0.40)]client Y

[(250 day/year)(1 shift/day)(8 hours/shift)][1.0 - (15/100)]

= = 3.12

5,305

1,700

Rounding up to the next integer gives a requirement of four machines.

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Application Problem 4.1

You have been asked to put together a capacity plan for a critical operation at the Surefoot Sandal Company. Your capacity measure is number of machines. Three products (men’s, women’s, and children’s sandals) are manufactured. The time standards (processing and setup), lot sizes, and demand forecasts are given in the following table. The firm operates two 8-hour shifts, 5 days per week, 50 weeks per year. Experience shows that a capacity cushion of 5 percent is sufficient.

a. How many machines are needed?

b. If the operation currently has two machines, what is the capacity gap?

	Time Standards
Product	Processing (hr/pair)	Setup (hr/pair)	Lot size (pairs/lot)	Demand Forecast (pairs/yr)
Men’s sandals	0.05	0.5	240	80,000
Women’s sandals	0.10	2.2	180	60,000
Children’s sandals	0.02	3.8	360	120,000

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Application Problem 4.1

a. The number of hours of operation per year, N, is N = (2 shifts/day)(8 hours/shifts) (250 days/machine-year) = 4,000 hours/machine-year

The number of machines required, M, is the sum of machine-hour requirements for all three products divided by the number of productive hours available for one machine:

M =

[Dp + (D/Q)s]men + [Dp + (D/Q)s]women + [Dp + (D/Q)s]children

N[1 - (C/100)]

[80,000(0.05) + (80,000/240)0.5] + [60,000(0.10) + (60,000/180)2.2] + [120,000(0.02) + (120,000/360)3.8]

4,000[1 - (5/100)]

= 3.83 or 4 machines

14,567 hours/year

3,800 hours/machine-year

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Application Problem 4.1

b. The capacity gap is 1.83 machines (3.83 –2). Two more machines should be purchased, unless management decides to use short-term options to fill the gap.

The Capacity Requirements Solver in OM Explorer confirms these calculations, as Figure 6.5 shows, using only the “Expected” scenario for the demand forecasts.

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Application Problem 4.1

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Step 2 - Identify Gaps

Identify gaps between projected capacity requirements (M) and current capacity

Complicated by multiple operations and resource inputs

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Steps 3 and 4 – Develop and Evaluate Alternatives

Base case is to do nothing and suffer the consequences

Many different alternatives are possible

Build new lines

Build new plants

Make existing lines/plants more efficient

Outsource

Qualitative concerns include strategic fit and uncertainties.

Quantitative concerns may include cash flows and other quantitative measures.

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Example 4.2

Grandmother’s Chicken Restaurant is experiencing a boom in business. The owner expects to serve 80,000 meals this year. Although the kitchen is operating at 100 percent capacity, the dining room can handle 105,000 diners per year. Forecasted demand for the next five years is 90,000 meals for next year, followed by a 10,000-meal increase in each of the succeeding years. One alternative is to expand both the kitchen and the dining room now, bringing their capacities up to 130,000 meals per year. The initial investment would be $200,000, made at the end of this year (year 0). The average meal is priced at $10, and the before-tax profit margin is 20 percent. The 20 percent figure was arrived at by determining that, for each $10 meal, $8 covers variable costs and the remaining $2 goes to pretax profit.

What are the pretax cash flows from this project for the next five years compared to those of the base case of doing nothing?

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Example 4.2

The base case of doing nothing results in losing all potential sales beyond 80,000 meals.

With the new capacity, the cash flow would equal the extra meals served by having a 130,000-meal capacity, multiplied by a profit of $2 per meal.

In year 0, the only cash flow is –$200,000 for the initial investment.

In year 1, the incremental cash flow is (90,000 – 80,000)($2) = $20,000.

Year 2: Demand = 100,000; Cash flow = (100,000 – 80,000)$2 = $40,000

Year 3: Demand = 110,000; Cash flow = (110,000 – 80,000)$2 = $60,000

Year 4: Demand = 120,000; Cash flow = (120,000 – 80,000)$2 = $80,000

Year 5: Demand = 130,000; Cash flow = (130,000 – 80,000)$2 = $100,000

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Example 4.2

The owner should account for the time value of money, applying such techniques as the net present value or internal rate of return methods (see Supplement F, “Financial Analysis,” in MyOMLab).

For instance, the net present value (NPV) of this project at a discount rate of 10 percent is calculated here, and equals $13,051.76.

NPV = –200,000 + [(20,000/1.1)] + [40,000/(1.1)2] + [60,000/(1.1)3] + [80,000/(1.1)4] + [100,000/(1.1)5]

= –$200,000 + $18,181.82 + $33,057.85 + $45,078.89 + $54,641.07 + $62,092.13

= $13,051.76

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Application Problem 4.2

The base case for Grandmother’s Chicken Restaurant (see Example 6.2) is to do nothing. The capacity of the kitchen in the base case is 80,000 meals per year. A capacity alternative for Grandmother’s Chicken Restaurant is a two-stage expansion. This alternative expands the kitchen at the end of year 0, raising its capacity from 80,000 meals per year to that of the dining area (105,000 meals per year). If sales in year 1 and 2 live up to expectations, the capacities of both the kitchen and the dining room will be expanded at the end of year 3 to 130,000 meals per year. This upgraded capacity level should suffice up through year 5. The initial investment would be $80,000 at the end of year 0, and an additional investment of $170,000 at the end of year 3. The pretax profit is $2 per meal. What are the pretax cash flows for this alternative through year 5, compared with the base case?

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Application Problem 4.2

The following table shows the cash inflows and outflows.

Year 3 cash flow:

The cash inflow from sales is $50,000 rather than $60,000.

The increase in sales over the base is 25,000 meals (105,000 – 10,000) instead of 30,000 meals (110,000 – 80,000)

A cash outflow of $170,000 occurs at the end of year 3, when the second-stage expansion occurs.

The net cash flow for year 3 is $50,000 – $170,000 = –$120,000

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Application Problem 4.2

CASH FLOWS FOR TWO-STAGE EXPANSION AT GRANDMOTHER’S CHICKEN RESTAURANT
Year	Projected Demand (meals/yr)	Projected Capacity (meals/yr)	Calculation of Incremental Cash Flow Compared to Base Case (80,000 meals/yr)	Cash Inflow (outflow)
0	80,000	80,000	Increase kitchen capacity to 105,000 meals =	-$80,000
1	90,000	105,000	90,000 – 80,000 = (10,000 meals)($2/meal) =	$20,000
2	100,000	105,000	100,000 – 80,000 = (20,000 meals)($2/meal) =	$40,000
3	110,000	105,000	105,000 – 80,000 = (25,000 meals)($2/meal) =	$50,000
			Increase total capacity to 130,000 meals =	-$170,000
				-$120,000
4	120,000	130,000	120,000 – 80,000 = (40,000 meals)($2/meal) =	$80,000
5	130,000	130,000	130,000 – 80,000 = (50,000 meals)($2/meal) =	$100,000

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Application Problem 4.2

NPV = –80,000 + (20,000/1.1) + [40,000/(1.1)2] – [120,000/(1.1)3] + [80,000/(1.1)4] + [100,000/(1.1)5]

= –$80,000 + $18,181.82 + $33,057.85 – $90,157.77 + $54,641.07 + $62,092.13

= –$2,184.90

On a purely monetary basis, a single-stage expansion seems to be a better alternative than this two-stage expansion.

However, other qualitative factors as mentioned earlier must be considered as well.

For comparison purposes, the NPV of this project at a discount rate of 10 percent is calculated as follows, and equals negative $2,184.90.

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Tools for Capacity Planning

Waiting-line models

Useful in high customer-contact processes

Simulation

Useful when models are too complex for waiting-line analysis

Decision trees

Useful when demand is uncertain and sequential decisions are involved

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Waiting Line Models

Figure 4.3

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Decision Trees

Low demand [0.40]

High demand [0.60]

Low demand [0.40]

High demand [0.60]

$70,000

$220,000

$40,000

$135,000

$90,000

Small expansion

Large expansion

Do not expand

Expand

$135,000

$109,000

$148,000

Figure 4.4

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