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© 2006 Prentice Hall, Inc.S7 – 1 Operations Management Supplement 7 – Capacity Planning © 2006 Prentice Hall, Inc. PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 6e Operations Management, 8e

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© 2006 Prentice Hall, Inc.S7 – 2 Capacity The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time Determines fixed costs Determines fixed costs Determines if demand will be satisfied Determines if demand will be satisfied Three time horizons Three time horizons

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© 2006 Prentice Hall, Inc.S7 – 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 * * Limited options exist Figure S7.1

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© 2006 Prentice Hall, Inc.S7 – 4 Design and Effective Capacity Design capacity is the maximum theoretical output of a system Design capacity is the maximum theoretical output of a system Normally expressed as a rate Normally expressed as a rate Effective capacity is the capacity a firm expects to achieve given current operating constraints Effective capacity is the capacity a firm expects to achieve given current operating constraints Often lower than design capacity Often lower than design capacity

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© 2006 Prentice Hall, Inc.S7 – 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

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© 2006 Prentice Hall, Inc.S7 – 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, 3 – 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

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© 2006 Prentice Hall, Inc.S7 – 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, 3 – 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

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© 2006 Prentice Hall, Inc.S7 – 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, 3 – 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

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© 2006 Prentice Hall, Inc.S7 – 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, 3 – 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

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© 2006 Prentice Hall, Inc.S7 – 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 Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

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© 2006 Prentice Hall, Inc.S7 – 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 Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

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© 2006 Prentice Hall, Inc.S7 – 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 Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

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© 2006 Prentice Hall, Inc.S7 – 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, three- 8 hour shifts Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

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© 2006 Prentice Hall, Inc.S7 – 14 Managing Demand Demand exceeds capacity Demand exceeds capacity Curtail demand by raising prices, scheduling longer lead time Curtail demand by raising prices, scheduling longer lead time Long term solution is to increase capacity Long term solution is to increase capacity Capacity exceeds demand Capacity exceeds demand Stimulate market Stimulate market Product changes Product changes Adjusting to seasonal demands Adjusting to seasonal demands Produce products with complimentary demand patterns Produce products with complimentary demand patterns

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© 2006 Prentice Hall, Inc.S7 – 15 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 Average unit cost (dollars per room per night) Figure S7.2

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© 2006 Prentice Hall, Inc.S7 – 16 Capacity Considerations Forecast demand accurately Forecast demand accurately Understanding the technology and capacity increments Understanding the technology and capacity increments Find the optimal operating level (volume) Find the optimal operating level (volume) Build for change Build for change

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© 2006 Prentice Hall, Inc.S7 – 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 Figure S7.4

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© 2006 Prentice Hall, Inc.S7 – 18 Break-Even Analysis Technique for evaluating process and equipment alternatives Technique for evaluating process and equipment alternatives Objective is to find the point in dollars and units at which cost equals revenue Objective is to find the point in dollars and units at which cost equals revenue Requires estimation of fixed costs, variable costs, and revenue Requires estimation of fixed costs, variable costs, and revenue

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© 2006 Prentice Hall, Inc.S7 – 19 Break-Even Analysis Fixed costs are costs that continue even if no units are produced Fixed costs are costs that continue even if no units are produced Depreciation, taxes, debt, mortgage payments Depreciation, taxes, debt, mortgage payments Variable costs are costs that vary with the volume of units produced Variable costs are costs that vary with the volume of units produced Labor, materials, portion of utilities Labor, materials, portion of utilities Contribution is the difference between selling price and variable cost Contribution is the difference between selling price and variable cost

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© 2006 Prentice Hall, Inc.S7 – 20 Break-Even Analysis Costs and revenue are linear functions Costs and revenue are linear functions Generally not the case in the real world Generally not the case in the real world We actually know these costs We actually know these costs Very difficult to accomplish Very difficult to accomplish There is no time value of money There is no time value of money Assumptions

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© 2006 Prentice Hall, Inc.S7 – 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 – – – – – – – – – – – |||||||||||| Cost in dollars Volume (units per period) Figure S7.5

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© 2006 Prentice Hall, Inc.S7 – 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

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© 2006 Prentice Hall, Inc.S7 – 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

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© 2006 Prentice Hall, Inc.S7 – 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, [( )/(4.00)]

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© 2006 Prentice Hall, Inc.S7 – 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, [( )/(4.00)] = = $22, $10, BEP x = = = 5,714 F P - V $10, ( )

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© 2006 Prentice Hall, Inc.S7 – 26 Break-Even Example BEP $ = F 1 - x (W i ) 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

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© 2006 Prentice Hall, Inc.S7 – 27 Multiproduct Case Derivation

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© 2006 Prentice Hall, Inc.S7 – 28 Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$2.95$1.257,000 Soft drink ,000 Baked potato ,000 Tea ,000 Salad bar ,000 Fixed costs = $3,500 per month

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© 2006 Prentice Hall, Inc.S7 – 29 Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$2.95$1.257,000 Soft drink ,000 Baked potato ,000 Tea ,000 Salad bar ,000 Sandwich$2.95$ $20, Soft drink , Baked , potato Tea , Salad bar , $46, 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

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© 2006 Prentice Hall, Inc.S7 – 30 Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$2.95$1.257,000 Soft drink ,000 Baked potato ,000 Tea ,000 Salad bar ,000 Fixed costs = $3,500 per month Sandwich$2.95$ $20, Soft drink , Baked , potato Tea , Salad bar , $46, 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 Daily sales = = $ $67, days.446 x $ $2.95 = sandwiches per day

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© 2006 Prentice Hall, Inc.S7 – 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

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© 2006 Prentice Hall, Inc.S7 – 32 Strategy-Driven Investment Operations may be responsible for return-on-investment (ROI) Operations may be responsible for return-on-investment (ROI) Analyzing capacity alternatives should include capital investment, variable cost, cash flows, and net present value Analyzing capacity alternatives should include capital investment, variable cost, cash flows, and net present value

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© 2006 Prentice Hall, Inc.S7 – 33 Net Present Value (NPV) whereF= future value P= present value i= interest rate N= number of years P = F (1 + i) N

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© 2006 Prentice Hall, Inc.S7 – 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% Portion of Table S7.1

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© 2006 Prentice Hall, Inc.S7 – 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

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© 2006 Prentice Hall, Inc.S7 – 36 Present Value of an Annuity

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© 2006 Prentice Hall, Inc.S7 – 37 Present Value of an Annuity Portion of Table S7.2 Year5%6%7%…10%

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© 2006 Prentice Hall, Inc.S7 – 38 Process, Volume, and Variety Process Focus projects, job shops (machine, print, carpentry) Standard Register Repetitive (autos, motorcycles) Harley Davidson Product Focus (commercial baked goods, steel, glass) Nucor Steel High Variety one or few units per run, high variety (allows customization) Changes in Modules modest runs, standardized modules Changes in Attributes (such as grade, quality, size, thickness, etc.) long runs only Mass Customization (difficult to achieve, but huge rewards) Dell Computer Co. Poor Strategy (Both fixed and variable costs are high) Low Volume Repetitive Process High Volume Volume Figure 7.1

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