Capacity Planning (Long-Term Capacity Planning) Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–1
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6 Capacity Planning (Long-Term Capacity Planning) Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–1 Planning Management Capacity management Chapter 6 – Chapter 7 – Capacity planning Constraint management (long-term capacity planning) (short-term capacity planning) 1. Economies and diseconomies of scale 2. Capacity timing and sizing strategies 3. Systematic approach to capacity decisions Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. Theory of constraints Identification and management of bottlenecks Product mix decisions using bottlenecks Managing constraints in a line process 6–2 Capacity and Scale Average unit cost (dollars per patient) best operating level = 500 beds (blue dot in the diagram) 250-bed hospital 500-bed hospital Economies of scale 750-bed hospital Diseconomies of scale Output rate (patients per week) Figure 6.1 – Economies and Diseconomies of Scale Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–3 A. Expansionist strategy Forecast of capacity required Capacity Planned unused capacity Capacity increment Time between increments Time Figure 6.2 – Two Capacity Strategies Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–4 B. Wait-and-see strategy Capacity Planned use of short-term options Forecast of capacity required Capacity increment Time between increments Time Figure 6.2 – Two Capacity Strategies Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–5 Output Measures for Estimating Capacity Requirements Output Measures are the simplest way to express capacity. Products produced or customers served per unit of time Example: Current capacity is 50 per day and demand is expected to double in five years. Management uses a capacity cushion of 20%. Capacity (M) in 5 years should be: M = 100/(1 - 0.2) = 125 customers 6–6 Input Measures for Estimating Capacity Requirements Input Measures are typically based on resource availability: e.g. Availability of workers, machines, workstations, seats, etc. For one service or product processed at one operation with a one year time period, the capacity requirement, M, is Processing hours required for year’s demand Capacity requirement = Hours available from a single capacity unit (such as an employee or machine) per year, after deducting desired cushion Dp M= N[1 – (C/100)] where D = demand forecast for the year (number of customers serviced or units of product) 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) Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–7 Input Measures for Estimating Capacity Requirements if multiple products are produced, setup times may be required Capacity requirement = M= Processing and setup hours required for year’s demand, summed over all services or products Hours available from a single capacity unit per year, after deducting desired cushion [Dp + (D/Q)s]product 1 + [Dp + (D/Q)s]product 1 + … + [Dp + (D/Q)s]product n N[1 – (C/100)] where Q = number of units in each lot s = setup time (in hours) per lot Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–8 Decision Trees Low demand [0.40] $70,000 Don’t expand $109,000 High demand [0.60] 2 $135,000 1 Low demand [0.40] $148,000 $148,000 High demand [0.60] $90,000 Expand $135,000 $40,000 $220,000 Figure 6.4 – A Decision Tree for Capacity Expansion Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 6–9