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Chapter 8 - Capacity

Chapter 8 - Capacity

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Chapter 8 - Capacity

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  1. Chapter 8 -Capacity

  2. Utilization

  3. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Example 8.1

  4. Average output rate Peak capacity Utilizationpeak = Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Example 8.1

  5. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day 50 100 Utilizationpeak = Example 8.1

  6. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day 50 100 Utilizationpeak = x 100% = 50% Example 8.1

  7. Average output rate Effective capacity Utilizationeffective = Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day 50 100 Utilizationpeak = x 100% = 50% Example 8.1

  8. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day 50 100 Utilizationpeak = x 100% = 50% 50 45 Utilizationeffective = Example 8.1

  9. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day 50 100 Utilizationpeak = x 100% = 50% 50 45 Utilizationeffective = x 100% = 111% Example 8.1

  10. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Utilizationpeak = 50% Utilizationeffective = 111% Example 8.1

  11. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Utilizationpeak = 50% Utilizationeffective = 111% Capacity cushionpeak = 100% – 50% = 50% Capacity cushioneffective = 100% – 111% = – 11% Figure 8.1

  12. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Utilizationpeak = 50% Utilizationeffective = 111% Capacity cushionpeak = 100% – Utilizationpeak Capacity cushioneffective = 100% – Utilizationeffective Example 8.1

  13. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Utilizationpeak = 50% Utilizationeffective = 111% Capacity cushionpeak = 100% - 50% Capacity cushionpeak = 100% – 50% Capacity cushioneffective = 100% – 111% Example 8.1

  14. Utilization Fabrication can make 100 engines/day Management wants 45 engines/day Currently producing 50 engines/day Utilizationpeak = 50% Utilizationeffective = 111% Capacity cushionpeak = 100% – 50% = 50% Capacity cushioneffective = 100% – 111% = – 11% Example 8.1

  15. Capacity Bottlenecks

  16. To customers Inputs 1 2 3 200/hr 200/hr 50/hr (a) Operation 2 a bottleneck Capacity Bottlenecks Figure 8.2

  17. To customers Inputs 1 2 3 200/hr 200/hr 200/hr Capacity Bottlenecks (b) All operations bottlenecks Figure 8.2

  18. 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

  19. Economies and Diseconomies of Scale Average unit cost (dollars per patient) Output rate (patients per week) Figure 8.3

  20. Economies and Diseconomies of Scale 250-bed hospital Average unit cost (dollars per patient) Output rate (patients per week) Figure 8.3

  21. Economies and Diseconomies of Scale 250-bed hospital 500-bed hospital Average unit cost (dollars per patient) Output rate (patients per week) Figure 8.3

  22. Economies and Diseconomies of Scale 250-bed hospital 500-bed hospital Average unit cost (dollars per patient) Economies of scale Output rate (patients per week) Figure 8.3

  23. Economies and Diseconomies of Scale 250-bed hospital 750-bed hospital 500-bed hospital Average unit cost (dollars per patient) Economies of scale Output rate (patients per week) Figure 8.3

  24. Economies and Diseconomies of Scale 250-bed hospital 750-bed hospital 500-bed hospital Average unit cost (dollars per patient) Economies of scale Diseconomies of scale Output rate (patients per week) Figure 8.3

  25. Capacity Strategies

  26. Capacity Strategies Forecast of capacity required Capacity Time Figure 8.4

  27. Capacity Strategies Forecast of capacity required Planned unused capacity Capacity Time (a) Expansionist strategy Figure 8.4

  28. Capacity Strategies Forecast of capacity required Planned unused capacity Capacity Time (a) Expansionist strategy Figure 8.4

  29. Capacity Strategies Forecast of capacity required Planned unused capacity Capacity increment Capacity Time between increments Time (a) Expansionist strategy Figure 8.4

  30. Capacity Strategies Forecast of capacity required Capacity Time (b) Wait-and-see strategy Figure 8.4

  31. Capacity Strategies Forecast of capacity required Planned use of short-term options Capacity Time (b) Wait-and-see strategy Figure 8.4

  32. Capacity Strategies Forecast of capacity required Planned use of short-term options Capacity increment Capacity Time between increments Time (b) Wait-and-see strategy Figure 8.4

  33. Linking Capacity and Other Decisions • Competitive Priorities • Quality Management • Capital Intensity • Resource Flexibility • Inventory • Scheduling

  34. Capacity Decisions

  35. Item Client X Client Y Annual demand forecast (copies) 2000.00 6000.00 Standard processing time (hour/copy) 0.50 0.70 Average lot size (copies per report) 20.00 30.00 Standard setup time (hours) 0.25 0.40 Capacity Decisions Estimate Capacity Requirements Example 8.2

  36. Item Client X Client Y Annual demand forecast (copies) 2000.00 6000.00 Standard processing time (hour/copy) 0.50 0.70 Average lot size (copies per report) 20.00 30.00 Standard setup time (hours) 0.25 0.40 [Dp + (D/Q)s]product 1 + ... + [Dp + (D/Q)s]product n N[1 – (C/100)] M = Capacity Decisions Estimate Capacity Requirements Example 8.2

  37. Item Client X Client Y Annual demand forecast (copies) 2000.00 6000.00 Standard processing time (hour/copy) 0.50 0.70 Average lot size (copies per report) 20.00 30.00 Standard setup time (hours) 0.25 0.40 [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) M = Capacity Decisions Estimate Capacity Requirements Example 8.2

  38. Item Client X Client Y Annual demand forecast (copies) 2000.00 6000.00 Standard processing time (hour/copy) 0.50 0.70 Average lot size (copies per report) 20.00 30.00 Standard setup time (hours) 0.25 0.40 [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) M = Capacity Decisions Estimate Capacity Requirements Example 8.2

  39. Item Client X Client Y Annual demand forecast (copies) 2000.00 6000.00 Standard processing time (hour/copy) 0.50 0.70 Average lot size (copies per report) 20.00 30.00 Standard setup time (hours) 0.25 0.40 5305 1700 M = = 3.12  4 machines Capacity Decisions Estimate Capacity Requirements Example 8.2

  40. Capacity Decisions Identify Capacity Gaps

  41. Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  42. 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  43. 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Kitchen Capacity Gaps Example 8.3

  44. 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Kitchen Capacity Gaps Year 1: 90,000 – 80,000 = 10,000 Example 8.3

  45. 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 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  46. Dining Room Capacity Gaps Year 1: Year 2: Year 3: Year 4: Year 5: 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  47. Dining Room Capacity Gaps Year 1: no gaps Year 2: no gaps Year 3: Year 4: Year 5: 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  48. Dining Room Capacity Gaps Year 1: no gaps Year 2: no gaps Year 3: 110,000 – 105,000 = 5,000 Year 4: Year 5: 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  49. 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 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 Capacity Decisions Identify Capacity Gaps Kitchen capacity = 80,000 meals Dining room capacity = 105,000 meals Example 8.3

  50. Capacity Decisions Evaluate Alternatives