Operations Management Supplement 7 – Capacity Planning PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 7e Operations Management, 9e © 2008 Prentice Hall, Inc. S7 – 1 Outline Capacity Design and Effective Capacity Capacity and Strategy Capacity Considerations Managing Demand Demand and Capacity Management in the Service Sector © 2008 Prentice Hall, Inc. S7 – 2 Outline – Continued Capacity Planning Break-Even Analysis Single-Product Case Multiproduct Case Applying Decision Trees to Capacity Decisions © 2008 Prentice Hall, Inc. S7 – 3 Outline – Continued Applying Investment Analysis to Strategy-Driven Investments Investment, Variable Cost, and Cash Flow Net Present Value © 2008 Prentice Hall, Inc. S7 – 4 Learning Objectives When you complete this supplement, you should be able to: 1. Define capacity 2. Determine design capacity, effective capacity, and utilization 3. Compute break-even analysis 4. Apply decision trees to capacity decisions 5. Compute net present value © 2008 Prentice Hall, Inc. S7 – 5 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 © 2008 Prentice Hall, Inc. S7 – 6 Planning Over a Time Horizon Long-range planning Add facilities Add long lead time equipment Intermediaterange planning Subcontract Add equipment Add shifts Short-range planning Add personnel Build or use inventory * Modify capacity * Schedule jobs Schedule personnel Allocate machinery Use capacity * Limited options exist Figure S7.1 © 2008 Prentice Hall, Inc. S7 – 7 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 © 2008 Prentice Hall, Inc. S7 – 8 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 © 2008 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 © 2008 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 © 2008 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% © 2008 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 Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4% © 2008 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, 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% © 2008 Prentice Hall, Inc. S7 – 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% © 2008 Prentice Hall, Inc. S7 – 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 Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls © 2008 Prentice Hall, Inc. S7 – 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 © 2008 Prentice Hall, Inc. S7 – 17 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 © 2008 Prentice Hall, Inc. S7 – 18 Capacity Considerations Forecast demand accurately Understand the technology and capacity increments Find the optimum operating level (volume) Build for change © 2008 Prentice Hall, Inc. S7 – 19 Average unit cost (dollars per room per night) Economies and Diseconomies of Scale 25 - room roadside motel Economies of scale 25 © 2008 Prentice Hall, Inc. 50 - room roadside motel 75 - room roadside motel Diseconomies of scale 50 Number of Rooms 75 Figure S7.2 S7 – 20 Build In Flexibility Percent of North American Vehicles Made on Flexible Assembly Lines 100% – 80% – 0– © 2008 Prentice Hall, Inc. Ford Toyota GM Honda 20% – Nissan 40% – Chrysler 60% – Figure S7.3 S7 – 21 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 © 2008 Prentice Hall, Inc. S7 – 22 Complementary Demand Patterns Sales in units 4,000 – 3,000 – 2,000 – 1,000 – JFMAMJJASONDJFMAMJJASONDJ Time (months) © 2008 Prentice Hall, Inc. Jet ski engine sales Figure S7.3 S7 – 23 Complementary Demand Patterns Sales in units 4,000 – 3,000 – Snowmobile motor sales 2,000 – 1,000 – JFMAMJJASONDJFMAMJJASONDJ Time (months) © 2008 Prentice Hall, Inc. Jet ski engine sales Figure S7.3 S7 – 24 Complementary Demand Patterns Sales in units 4,000 – Combining both demand patterns reduces the variation 3,000 – Snowmobile motor sales 2,000 – 1,000 – JFMAMJJASONDJFMAMJJASONDJ Time (months) © 2008 Prentice Hall, Inc. Jet ski engine sales Figure S7.3 S7 – 25 Tactics for Matching Capacity to Demand 1. Making staffing changes 2. Adjusting equipment Purchasing additional machinery Selling or leasing out existing equipment 3. Improving processes to increase throughput 4. Redesigning products to facilitate more throughput 5. Adding process flexibility to meet changing product preferences 6. Closing facilities © 2008 Prentice Hall, Inc. S7 – 26 Demand and Capacity Management in the Service Sector Demand management Appointment, reservations, FCFS rule Capacity management Full time, temporary, part-time staff © 2008 Prentice Hall, Inc. S7 – 27 Approaches to Capacity Expansion Expected demand Demand (c) Capacity lags demand with incremental expansion New capacity Expected demand Demand New capacity (b) Leading demand with one-step expansion New capacity Expected demand (d) Attempts to have an average capacity with incremental expansion Demand Demand (a) Leading demand with incremental expansion New capacity Expected demand Figure S7.5 © 2008 Prentice Hall, Inc. S7 – 28 Approaches to Capacity Expansion (a) Leading demand with incremental expansion Demand New capacity Expected demand 1 © 2008 Prentice Hall, Inc. 2 3 Time (years) Figure S7.5 S7 – 29 Approaches to Capacity Expansion (b) Leading demand with one-step expansion New capacity Demand Expected demand 1 © 2008 Prentice Hall, Inc. 2 3 Time (years) Figure S7.5 S7 – 30 Approaches to Capacity Expansion (c) Capacity lags demand with incremental expansion New capacity Demand Expected demand 1 © 2008 Prentice Hall, Inc. 2 3 Time (years) Figure S7.5 S7 – 31 Approaches to Capacity Expansion (d) Attempts to have an average capacity with incremental expansion Demand New capacity Expected demand 1 © 2008 Prentice Hall, Inc. 2 3 Time (years) Figure S7.5 S7 – 32 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 © 2008 Prentice Hall, Inc. S7 – 33 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 © 2008 Prentice Hall, Inc. S7 – 34 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 © 2008 Prentice Hall, Inc. S7 – 35 Break-Even Analysis – Total revenue line 900 – 800 – Cost in dollars 700 – Break-even point Total cost = Total revenue Total cost line 600 – 500 – Variable cost 400 – 300 – 200 – 100 – Fixed cost | | | | | | | | | | | – 0 100 200 300 400 500 600 700 800 900 1000 1100 | Figure S7.6 © 2008 Prentice Hall, Inc. Volume (units per period) S7 – 36 Break-Even Analysis 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 Break-even point occurs when TR = TC or Px = F + Vx © 2008 Prentice Hall, Inc. F BEPx = P-V S7 – 37 Break-Even Analysis 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 F = P P-V F = (P - V)/P F = 1 - V/P Profit = TR - TC = Px - (F + Vx) = Px - F - Vx = (P - V)x - F © 2008 Prentice Hall, Inc. S7 – 38 Break-Even Example Fixed costs = $10,000 Direct labor = $1.50/unit Material = $.75/unit Selling price = $4.00 per unit $10,000 F BEP$ = = 1 - [(1.50 + .75)/(4.00)] 1 - (V/P) © 2008 Prentice Hall, Inc. S7 – 39 Break-Even Example Fixed costs = $10,000 Direct labor = $1.50/unit Material = $.75/unit Selling price = $4.00 per unit $10,000 F BEP$ = = 1 - [(1.50 + .75)/(4.00)] 1 - (V/P) $10,000 = = $22,857.14 .4375 $10,000 F BEPx = = = 5,714 4.00 - (1.50 + .75) P-V © 2008 Prentice Hall, Inc. S7 – 40 Break-Even Example 50,000 – Revenue Dollars 40,000 – Break-even point 30,000 – Total costs 20,000 – Fixed costs 10,000 – | – 0 © 2008 Prentice Hall, Inc. | | 2,000 4,000 | 6,000 Units | | 8,000 10,000 S7 – 41 Break-Even Example Multiproduct Case BEP$ = where © 2008 Prentice Hall, Inc. V P F W i F ∑ Vi 1x (Wi) Pi = variable cost per unit = price per unit = fixed costs = percent each product is of total dollar sales = each product S7 – 42 Multiproduct Example Fixed costs = $3,500 per month Item Sandwich Soft drink Baked potato Tea Salad bar © 2008 Prentice Hall, Inc. Price $2.95 .80 1.55 .75 2.85 Cost $1.25 .30 .47 .25 1.00 Annual Forecasted Sales Units 7,000 7,000 5,000 5,000 3,000 S7 – 43 Multiproduct Example Fixed costs = $3,500 per month 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 Annual 5,000 Weighted % of Contribution Tea Selling Variable .75 .25Forecasted 5,000 Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7) Salad bar 2.85 1.00 3,000 Sandwich Soft drink Baked potato Tea Salad bar © 2008 Prentice Hall, Inc. $2.95 .80 1.55 $1.25 .30 .47 .42 .38 .30 .58 .62 .70 $20,650 5,600 7,750 .446 .121 .167 .259 .075 .117 .75 2.85 .25 1.00 .33 .35 .67 .65 3,750 8,550 $46,300 .081 .185 1.000 .054 .120 .625 S7 – 44 BEP Example = Multiproduct V ∑ 1 - P x (W ) F $ i i i Fixed costs = $3,500 per month $3,500 x Forecasted 12 Annual = = $67,200 .625 Item Price Cost Sales Units Sandwich $2.95 $1.25 7,000 $67,200 Daily Soft drink .80 .30 7,000 = = $215.38 sales 312 days Baked potato 1.55 .47 Annual 5,000 Weighted % of Contribution Tea Selling Variable .75 .25Forecasted 5,000 Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7) Salad bar 2.85 1.00 3,000 .446 x $215.38 = 32.6 .259 33 Sandwich $2.95 $1.25 .42 .58 $20,650 .446 $2.95 sandwiches Soft drink Baked potato Tea Salad bar © 2008 Prentice Hall, Inc. .80 1.55 .30 .47 .38 .30 .62 .70 5,600 7,750 .75 2.85 .25 1.00 .33 .35 .67 .65 3,750 8,550 $46,300 .121 .075 per day .167 .117 .081 .185 1.000 .054 .120 .625 S7 – 45 Decision Trees and Capacity Decision Market favorable (.4) Market unfavorable (.6) Market favorable (.4) Medium plant Market unfavorable (.6) Market favorable (.4) Market unfavorable (.6) $100,000 -$90,000 $60,000 -$10,000 $40,000 -$5,000 $0 © 2008 Prentice Hall, Inc. S7 – 46 Decision Trees and Capacity Decision Market favorable (.4) Market unfavorable (.6) Market favorable (.4) Medium plant Large Plant Market unfavorable (.6) EMV = (.4)($100,000) + (.6)(-$90,000) Market favorable (.4) EMV = -$14,000 Market unfavorable (.6) $100,000 -$90,000 $60,000 -$10,000 $40,000 -$5,000 $0 © 2008 Prentice Hall, Inc. S7 – 47 Decision Trees and Capacity Decision -$14,000 Market favorable (.4) Market unfavorable (.6) $100,000 -$90,000 $18,000 Market favorable (.4) Medium plant Market unfavorable (.6) $60,000 -$10,000 $13,000 Market favorable (.4) Market unfavorable (.6) $40,000 -$5,000 $0 © 2008 Prentice Hall, Inc. S7 – 48 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 © 2008 Prentice Hall, Inc. S7 – 49 Net Present Value (NPV) F P= (1 + i)N where © 2008 Prentice Hall, Inc. F P i N = future value = present value = interest rate = number of years S7 – 50 Net Present Value (NPV) F P= (1 + i)N While this works where F = future value fine, it isP = present value cumbersome for larger values iof= Ninterest rate N = number of years © 2008 Prentice Hall, Inc. S7 – 51 NPV Using Factors F P= = FX N (1 + i) where Portion of Table S7.1 © 2008 Prentice Hall, Inc. Year 1 2 3 4 5 X = a factor from Table S7.1 defined as = 1/(1 + i)N and F = future value 5% .952 .907 .864 .823 .784 6% .943 .890 .840 .792 .747 7% .935 .873 .816 .763 .713 … 10% .909 .826 .751 .683 .621 S7 – 52 Present Value of an Annuity An annuity is an investment which generates uniform equal payments S = RX where © 2008 Prentice Hall, Inc. X = 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 S7 – 53 Present Value of an Annuity Portion of Table S7.2 Year 1 2 3 4 5 © 2008 Prentice Hall, Inc. 5% .952 1.859 2.723 4.329 5.076 6% .943 1.833 2.676 3.465 4.212 7% .935 1.808 2.624 3.387 4.100 … 10% .909 1.736 2.487 3.170 3.791 S7 – 54 Present Value of an Annuity $7,000 in receipts per for 5 years Interest rate = 6% From Table S7.2 X = 4.212 S = RX S = $7,000(4.212) = $29,484 © 2008 Prentice Hall, Inc. S7 – 55 Present Value With Different Future Receipts Investment A’s Cash Flow Investment B’s Cash Flow Year Present Value Factor at 8% $10,000 $9,000 1 .926 9,000 9,000 2 .857 8,000 9,000 3 .794 7,000 9,000 4 .735 © 2008 Prentice Hall, Inc. S7 – 56 Present Value With Different Future Receipts Investment A’s Present Values Investment B’s Present Values 1 $9,260 = (.926)($10,000) $8,334 = (.926)($9,000) 2 7,713 = (.857)($9,000) 7,713 = (.857)($9,000) 3 6,352 = (.794)($8,000) 7,146 = (.794)($9,000) 4 5,145 = (.735)($7,000) 6,615 = (.735)($9,000) Year Totals Minus initial investment Net present value © 2008 Prentice Hall, Inc. $28,470 $29,808 -25,000 -26,000 $3,470 $3,808 S7 – 57

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