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Operations Management

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  1. Operations Management Supplement 7 – Capacity Planning PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 7e Operations Management, 9e

  2. Outline • Capacity • Design and Effective Capacity • Capacity and Strategy • Capacity Considerations • Managing Demand • Demand and Capacity Management in the Service Sector

  3. Outline – Continued • Capacity Planning • Break-Even Analysis • Single-Product Case • Multiproduct Case • Applying Decision Trees to Capacity Decisions

  4. Outline – Continued • Applying Investment Analysis to Strategy-Driven Investments • Investment, Variable Cost, and Cash Flow • Net Present Value

  5. Learning Objectives When you complete this supplement, you should be able to: Define capacity Determine design capacity, effective capacity, and utilization Compute break-even analysis Apply decision trees to capacity decisions Compute net present value

  6. Capacity • The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time • Determines fixed costs • Determines if demand will be satisfied • Three time horizons

  7. * Long-range planning Add facilities Add long lead time equipment Intermediate-range planning Subcontract Add personnel Add equipment Build or use inventory Add shifts Schedule jobs Schedule personnel Allocate machinery * Short-range planning Modify capacity Use capacity Planning Over a Time Horizon *Limited options exist Figure S7.1

  8. Design and Effective Capacity • Design capacity is the maximum theoretical output of a system • Normally expressed as a rate • Effective capacity is the capacity a firm expects to achieve given current operating constraints • Often lower than design capacity

  9. Utilization and Efficiency Utilization is the percent of design capacity achieved Utilization = Actual output/Design capacity Efficiency is the percent of effective capacity achieved Efficiency = Actual output/Effective capacity

  10. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

  11. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

  12. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

  13. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

  14. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

  15. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

  16. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

  17. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

  18. Capacity and Strategy • Capacity decisions impact all 10 decisions of operations management as well as other functional areas of the organization • Capacity decisions must be integrated into the organization’s mission and strategy

  19. Capacity Considerations • Forecast demand accurately • Understand the technology and capacity increments • Find the optimum operating level (volume) • Build for change

  20. 75 - room roadside motel 25 - room roadside motel 50 - room roadside motel Average unit cost (dollars per room per night) Economies of scale Diseconomies of scale 25 50 75 Number of Rooms Economies and Diseconomies of Scale Figure S7.2

  21. 100% – 80% – 60% – 40% – 20% – 0 – Chrysler Nissan Toyota Honda Ford GM Build In Flexibility Percent of North American Vehicles Made on Flexible Assembly Lines Figure S7.3

  22. Managing Demand • Demand exceeds capacity • Curtail demand by raising prices, scheduling longer lead time • Long term solution is to increase capacity • Capacity exceeds demand • Stimulate market • Product changes • Adjusting to seasonal demands • Produce products with complementary demand patterns

  23. 4,000 – 3,000 – 2,000 – 1,000 – Sales in units Jet ski engine sales J F M A M J J A S O N D J F M A M J J A S O N D J Time (months) Complementary Demand Patterns Figure S7.3

  24. 4,000 – 3,000 – 2,000 – 1,000 – Snowmobile motor sales Sales in units Jet ski engine sales J F M A M J J A S O N D J F M A M J J A S O N D J Time (months) Complementary Demand Patterns Figure S7.3

  25. Combining both demand patterns reduces the variation 4,000 – 3,000 – 2,000 – 1,000 – Snowmobile motor sales Sales in units Jet ski engine sales J F M A M J J A S O N D J F M A M J J A S O N D J Time (months) Complementary Demand Patterns Figure S7.3

  26. Tactics for Matching Capacity to Demand • Making staffing changes • Adjusting equipment • Purchasing additional machinery • Selling or leasing out existing equipment • Improving processes to increase throughput • Redesigning products to facilitate more throughput • Adding process flexibility to meet changing product preferences • Closing facilities

  27. Demand and Capacity Management in the Service Sector • Demand management • Appointment, reservations, FCFS rule • Capacity management • Full time, temporary, part-time staff

  28. (a) Leading demand with incremental expansion (b) Leading demand with one-step expansion New capacity New capacity Expected demand Expected demand Demand Demand (c) Capacity lags demand with incremental expansion (d) Attempts to have an average capacity with incremental expansion New capacity New capacity Expected demand Expected demand Demand Demand Approaches to Capacity Expansion Figure S7.5

  29. New capacity Expected demand Demand 1 2 3 Time (years) Approaches to Capacity Expansion (a) Leading demand with incremental expansion Figure S7.5

  30. New capacity Expected demand Demand 1 2 3 Time (years) Approaches to Capacity Expansion (b) Leading demand with one-step expansion Figure S7.5

  31. New capacity Expected demand Demand 1 2 3 Time (years) Approaches to Capacity Expansion (c) Capacity lags demand with incremental expansion Figure S7.5

  32. New capacity Expected demand Demand 1 2 3 Time (years) Approaches to Capacity Expansion (d) Attempts to have an average capacity with incremental expansion Figure S7.5

  33. Break-Even Analysis • Technique for evaluating process and equipment alternatives • Objective is to find the point in dollars and units at which cost equals revenue • Requires estimation of fixed costs, variable costs, and revenue

  34. Break-Even Analysis • Fixed costs are costs that continue even if no units are produced • Depreciation, taxes, debt, mortgage payments • Variable costs are costs that vary with the volume of units produced • Labor, materials, portion of utilities • Contribution is the difference between selling price and variable cost

  35. Break-Even Analysis Assumptions • Costs and revenue are linear functions • Generally not the case in the real world • We actually know these costs • Very difficult to accomplish • There is no time value of money

  36. 900 – 800 – 700 – 600 – 500 – 400 – 300 – 200 – 100 – – Total revenue line Total cost line Break-even point Total cost = Total revenue Profit corridor Cost in dollars Variable cost Loss corridor Fixed cost | | | | | | | | | | | | 0 100 200 300 400 500 600 700 800 900 1000 1100 Volume (units per period) Break-Even Analysis Figure S7.6

  37. BEPx = break-even point in units BEP$ = break-even point in dollars P = price per unit (after all discounts) x = number of units produced TR = total revenue = Px F = fixed costs V = variable cost per unit TC = total costs = F + Vx F P - V BEPx = Break-Even Analysis Break-even point occurs when TR = TC or Px = F + Vx

  38. BEPx = break-even point in units BEP$ = break-even point in dollars P = price per unit (after all discounts) x = number of units produced TR = total revenue = Px F = fixed costs V = variable cost per unit TC = total costs = F + Vx BEP$ = BEPx P = P = = F P - V F 1 - V/P F (P - V)/P Break-Even Analysis Profit = TR - TC = Px - (F + Vx) = Px - F - Vx = (P - V)x - F

  39. BEP$= = F 1 - (V/P) $10,000 1 - [(1.50 + .75)/(4.00)] Break-Even Example Fixed costs = $10,000 Material = $.75/unit Direct labor = $1.50/unit Selling price = $4.00 per unit

  40. BEP$= = F 1 - (V/P) = = $22,857.14 BEPx= = = 5,714 $10,000 1 - [(1.50 + .75)/(4.00)] $10,000 .4375 $10,000 4.00 - (1.50 + .75) F P - V Break-Even Example Fixed costs = $10,000 Material = $.75/unit Direct labor = $1.50/unit Selling price = $4.00 per unit

  41. 50,000 – 40,000 – 30,000 – 20,000 – 10,000 – – Revenue Break-even point Total costs Dollars Fixed costs | | | | | | 0 2,000 4,000 6,000 8,000 10,000 Units Break-Even Example

  42. F BEP$= ∑1 - x (Wi) Vi Pi Break-Even Example Multiproduct Case where V = variable cost per unit P = price per unit F = fixed costs W = percent each product is of total dollar sales i = each product

  43. Annual Forecasted Item Price Cost Sales Units Sandwich $2.95 $1.25 7,000 Soft drink .80 .30 7,000 Baked potato 1.55 .47 5,000 Tea .75 .25 5,000 Salad bar 2.85 1.00 3,000 Multiproduct Example Fixed costs = $3,500 per month

  44. Annual Forecasted Item Price Cost Sales Units Sandwich $2.95 $1.25 7,000 Soft drink .80 .30 7,000 Baked potato 1.55 .47 5,000 Tea .75 .25 5,000 Salad bar 2.85 1.00 3,000 Annual Weighted Selling Variable Forecasted % of Contribution Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7) Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259 Soft drink .80 .30 .38 .62 5,600 .121 .075 Baked 1.55 .47 .30 .70 7,750 .167 .117 potato Tea .75 .25 .33 .67 3,750 .081 .054 Salad bar 2.85 1.00 .35 .65 8,550 .185 .120 $46,300 1.000 .625 Multiproduct Example Fixed costs = $3,500 per month

  45. F BEP$= ∑ 1 - x (Wi) Vi Pi Annual Forecasted Item Price Cost Sales Units Sandwich $2.95 $1.25 7,000 Soft drink .80 .30 7,000 Baked potato 1.55 .47 5,000 Tea .75 .25 5,000 Salad bar 2.85 1.00 3,000 .446 x $215.38 $2.95 $3,500 x 12 .625 = = $67,200 Annual Weighted Selling Variable Forecasted % of Contribution Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7) $67,200 312 days Daily sales = = $215.38 Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259 Soft drink .80 .30 .38 .62 5,600 .121 .075 Baked 1.55 .47 .30 .70 7,750 .167 .117 potato Tea .75 .25 .33 .67 3,750 .081 .054 Salad bar 2.85 1.00 .35 .65 8,550 .185 .120 $46,300 1.000 .625 = 32.6  33 sandwiches per day Multiproduct Example Fixed costs = $3,500 per month

  46. Market favorable (.4) $100,000 Market unfavorable (.6) -$90,000 Large plant Market favorable (.4) $60,000 Medium plant Market unfavorable (.6) -$10,000 Small plant Market favorable (.4) $40,000 Do nothing Market unfavorable (.6) -$5,000 $0 Decision Trees and Capacity Decision

  47. Market favorable (.4) $100,000 Market unfavorable (.6) -$90,000 Large plant Market favorable (.4) $60,000 Medium plant Market unfavorable (.6) -$10,000 Small plant Market favorable (.4) $40,000 Do nothing Market unfavorable (.6) -$5,000 $0 Decision Trees and Capacity Decision Large Plant EMV = (.4)($100,000) + (.6)(-$90,000) EMV = -$14,000

  48. -$14,000 Market favorable (.4) $100,000 Market unfavorable (.6) -$90,000 Large plant $18,000 Market favorable (.4) $60,000 Medium plant Market unfavorable (.6) -$10,000 $13,000 Small plant Market favorable (.4) $40,000 Do nothing Market unfavorable (.6) -$5,000 $0 Decision Trees and Capacity Decision

  49. Strategy-Driven Investment • Operations may be responsible for return-on-investment (ROI) • Analyzing capacity alternatives should include capital investment, variable cost, cash flows, and net present value

  50. F (1 + i)N P = Net Present Value (NPV) where F = future value P = present value i = interest rate N = number of years