1. Capacity Planning Production Planning and Control

2. 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  Used to plan overtime horizon

3. Modify capacity Use capacity Planning Over a Time Horizon Intermediate- range planning SubcontractAdd personnel Add equipmentBuild or use inventory Add shifts Short-range planning Schedule jobs Schedule personnel Allocate machinery * Long-range planning Add facilities Add long lead time equipment *

4. 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

5. Utilization and Efficiency Utilization is the percent of design capacity achieved Efficiency is the percent of effective capacity achieved Utilization = Actual Output/Design Capacity Efficiency = Actual Output/Effective Capacity

6. 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, 8 hours, 3 shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

7. 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, 8 hours, 3 shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

8. 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, 8 hours, 3 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%

9. 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, 8 hours, 3 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%

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, 8 hours, 3 shifts Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

11. 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

12. Managing Demand  Demand exceeds capacity  Limit 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 complimentary demand patterns

13. Economies and Diseconomies of Scale Economies of scale Diseconomies of scale 25 - Room Roadside Motel 50 - Room Roadside Motel 75 - Room Roadside Motel Number of Rooms 255075 Average unit cost (dollars per room per night)

14. Capacity Considerations  Forecast demand accurately  Understanding the technology and capacity increments  Find the optimal operating level (volume)  Build for change

15. Tactics for Matching Capacity to Demand 1.Making staffing changes 2.Adjusting equipment and processes  Purchasing additional machinery  Selling or leasing out existing equipment 3.Improving methods to increase throughput 4.Redesigning the product to facilitate more throughput

16. Complementary Demand Patterns 4,000 4,000 – 3,000 3,000 – 2,000 2,000 – 1,000 1,000 – 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 Sales in units Time (months) By combining both, the variation is reduced Snowmobile sales Jet ski sales

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

18. 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

19. 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

20. Break-Even Analysis  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 Assumptions

21. Profit corridor Loss corridor Break-Even Analysis Total revenue line Total cost line Variable cost Fixed cost Break-even point Total cost = Total revenue – 900 900 – 800 800 – 700 700 – 600 600 – 500 500 – 400 400 – 300 300 – 200 200 – 100 100 – – |||||||||||| 010020030040050060070080090010001100 Cost in dollars Volume (units per period)

22. Break-Even Analysis BEP x =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 costs TC=Total costs = F + Vx TR = TC or Px = F + Vx Break-even point occurs when BEP x = F P - V

23. Break-Even Analysis BEP x =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 costs TC=Total costs = F + Vx BEP $ = BEP x P = P ==F (P - V)/P F P - V F 1 - V/P Profit= TR - TC = Px - (F + Vx) = Px - F - Vx = (P - V)x - F

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

25. Break-Even Example Fixed costs = $10,000 Material = $.75/unit Direct labor = $1.50/unit Selling price = $4.00 per unit BEP $ = = F 1 - (V/P) $10,000 1 - [(1.50 +.75)/(4.00)] = = $22,857.14 $10,000.4375 BEP x = = = 5,714 F P - V $10,000 4.00 - (1.50 +.75)

26. Break-Even Example 50,000 50,000 – 40,000 40,000 – 30,000 30,000 – 20,000 20,000 – 10,000 10,000 – – |||||| 02,0004,0006,0008,00010,000 Dollars Units Fixed costs Total costs Revenue Break-even point

27. Break-Even Example BEP $ = F ∑ 1 - x (W i ) ViViPiPiViViPiPi Multiproduct Case whereV= variable cost per unit P= price per unit F= fixed costs W= percent each product is of total dollar sales i= each product

28. Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$2.95$1.257,000 Soft drink.80.307,000 Baked potato1.55.475,000 Tea.75.255,000 Salad bar2.851.003,000 Fixed costs = $3,500 per month

29. Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$2.95$1.257,000 Soft drink.80.307,000 Baked potato1.55.475,000 Tea.75.255,000 Salad bar2.851.003,000 Sandwich$2.95$1.25.42.58$20,650.446.259 Soft drink.80.30.38.625,600.121.075 Baked 1.55.47.30.707,750.167.117 potato Tea.75.25.33.673,750.081.054 Salad bar2.851.00.35.658,550.185.120 $46,3001.000.625 AnnualWeighted SellingVariableForecasted% ofContribution Item (i)Price (P)Cost (V)(V/P)1 - (V/P)Sales $Sales(col 5 x col 7) Fixed costs = $3,500 per month

30. Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$2.95$1.257,000 Soft drink.80.307,000 Baked potato1.55.475,000 Tea.75.255,000 Salad bar2.851.003,000 Fixed costs = $3,500 per month Sandwich$2.95$1.25.42.58$20,650.446.259 Soft drink.80.30.38.625,600.121.075 Baked 1.55.47.30.707,750.167.117 potato Tea.75.25.33.673,750.081.054 Salad bar2.851.00.35.658,550.185.120 $46,3001.000.625 AnnualWeighted SellingVariableForecasted% ofContribution Item (i)Price (P)Cost (V)(V/P)1 - (V/P)Sales $Sales(col 5 x col 7) BEP $ = F ∑ 1 - x (W i ) ViPiViPi = = $67,200 $3,500 x 12.625 Daily sales = = $215.38 $67,200 312 days.446 x $215.38 $2.95 = 32.6  33 sandwiches per day

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

32. 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

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

34. NPV Using Factors P = = FX F (1 + i) N whereX=a factor from Table S7.1 defined as = 1/(1 + i) N and F = future value Year5%6%7%…10% 1.952.943.935.909 2.907.890.873.826 3.864.840.816.751 4.823.792.763.683 5.784.747.713.621 Portion of Table S7.1

35. Present Value of an Annuity An annuity is an investment which generates uniform equal payments S = RX whereX=factor from Table S7.2 S=present value of a series of uniform annual receipts R=receipts that are received every year of the life of the investment

36. Present Value of an Annuity Portion of Table S7.2 Year5%6%7%…10% 1.952.943.935.909 21.8591.8331.8081.736 32.7232.6762.6242.487 44.3293.4653.3873.170 55.0764.2124.1003.791

37. Questions?