MD707 Operations Management Professor Joy Field Capacity Planning MD707 Operations Management Professor Joy Field

Capacity Planning Capacity is the maximum rate of output for a facility. Capacity planning considers questions such as: What should be the balance between long-term and short-term capacity? Should we expand capacity before the demand is there or wait until demand is more certain?  What facility size is optimal? Capacity decisions follow from a firm’s operations strategy and forecasted demand pattern.

Measuring Capacity Type Utilization Output measures Input measures Average output rate/maximum capacity Maximum capacity = effective or design capacity?

Capacity Bottlenecks and Flow Three-Stage Process 1 200/hr 2 50/hr 3 Inputs Outputs

Capacity Cushion Pressures for a large capacity cushion Uneven demand Uncertain demand Uncertain supply Changing product mix Capacity comes in large increments (economies of scale) Pressures for a small capacity cushion Capital costs

Links with Other Operational Characteristics and Priorities Operational Characteristic/Priority Capacity Cushion Faster delivery times Larger High quality levels Smaller Higher capital intensity Less worker flexibility More stable schedules

Timing of Capacity Increments Two Capacity Strategies Planned unused capacity Forecast of capacity required Planned use of short-term options

Optimal Operating Level

Steps in the Capacity Planning Process Estimate capacity requirements Identify gaps Develop alternatives Evaluate the alternatives  Select an alternative and implement

Make or Buy Decision Problem Hahn Manufacturing has been purchasing a key component of one of its products from a local supplier. The current purchase price is $1,500 per unit. Efforts to standardize parts have succeeded to the point that this same component can now be used in five different products. Annual component usage should increase from 150 to 750 units. Management wonders whether it is time to make the component in-house, rather than to continue buying it from the supplier. Fixed costs would increase by about $40,000 per year for the new equipment and tooling needed. The cost of raw materials and variable overhead would be about $1,100 per unit, and labor costs would go up by another $300 per unit produced. Should Hahn make rather than buy? What is the break-even quantity? What other considerations might be important?

Determining Resource Requirements The amount of resources (e.g., machines, people, service counters, etc.) needed at a bottleneck operation is based on the total processing and setup time required to meet demand. where M = number of bottleneck resources needed to meet production requirements D = yearly demand (in number of units/year) p = processing time per unit (in hours) Q = lot size s = setup time/lot (in hours) N = number of hours available/machine/year c = capacity cushion (in percentage)

Resource Capacity Problem You have been asked to put together a capacity plan for a critical bottleneck operation at the Surefoot Sandal Company. Your capacity measure is number of machines. Three products (men’s women’s, and kid’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. Assume a new setup for each lot produced. Product Processing (hr/pair) Setup (hr/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 Kid’s sandals 0.02 3.8 360 120,000 How many machines are needed at the bottleneck? If the operation currently has two machines, what is the capacity gap? If the operation can not buy any more machines, which products can be made? If the operation currently has five machines, what is the utilization?

Resource Capacity Problem Solutions Total time available per machine per year (2 shifts/day)(8 hours/shift)(5 days/week)(50 weeks/year) = 4000 hours/machine/year With a 5% capacity cushion, the hours/machine/year that are available = 4000(1-0.05) = 3800 hours/machine/year Total time to produce the yearly demand of each product (this is equal to the processing time plus the setup time) Men’s =(0.05)(80,000)+(80,000/240)(0.5)= 4167 hrs Women’s =(0.10)(60,000)+(60,000/180)(2.2)= 6733 hrs Kid’s =(0.02)(120,000)+(120,000/360)(3.8)= 3667 hrs Total time for all products =4167+6733+3667= 14567 hrs

Resource Capacity Problem Solutions (cont.) Machines needed = (14,567/3800) = 3.83 = 4 machines Capacity gap is 4 - 2 = 2 machines With two machines, we have (3800)(2) = 7600 hours of machine capacity. We can make all of the women’s sandals (6733 hours) and some of the men’s sandals, for example. With five machines, (5)(4000) = 20,000 machine-hours/year are available. The total number of machine-hours/year needed for production are 14,567. Utilization = (14,567/20,000)(100%) = 73%. Thus, the capacity cushion is (100% - 73%) = 27%.