Lecture 12 Capacity Management and Planning (continued) Books Introduction to Materials Management, Sixth Edition, J. R. Tony Arnold, P.E., CFPIM, CIRM, Fleming College, Emeritus, Stephen N. Chapman, Ph.D., CFPIM, North Carolina State University, Lloyd M. Clive, P.E., CFPIM, Fleming College Operations Management for Competitive Advantage, 11th Edition, by Chase, Jacobs, and Aquilano, 2005, N.Y.: McGraw-Hill/Irwin. Operations Management, 11/E, Jay Heizer, Texas Lutheran University, Barry Render, Graduate School of Business, Rollins College, Prentice Hall

Objectives Managing Demand Tactics for managing demand Approaches to capacity expansion Breakeven analysis Decision tree and capacity expansion Net present value Capacity planning issues

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

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

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

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

Approaches to Capacity Expansion (a)Leading demand with incremental expansion Expected demand New capacity Demand Time (years) 123

Approaches to Capacity Expansion (b)Leading demand with one-step expansion New capacity Expected demand Demand Time (years) 123

Approaches to Capacity Expansion (c)Capacity lags demand with incremental expansion Expected demand Demand Time (years) 123 New capacity

Approaches to Capacity Expansion (d)Attempts to have an average capacity with incremental expansion Expected demand New capacity Demand Time (years) 123

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

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

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

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)

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 cost per unit TC=total costs = F + Vx TR = TC or Px = F + Vx Break-even point occurs when BEP x = F P - V

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 cost per unit 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

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)]

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, ( )

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

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

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

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

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 = 32.6  33 sandwiches per day

Decision Trees and Capacity Decision -$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

Decision Trees and Capacity Decision -$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 EMV =(.4)($100,000) + (.6)(-$90,000) Large Plant EMV = -$14,000

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

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

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

Net Present Value (NPV) whereF= future value P= present value i= interest rate N= number of years P = F (1 + i) N While this works fine, it is cumbersome for larger values of N

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

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

Present Value of an Annuity Year5%6%7%…10%

Present Value of an Annuity $7,000 in receipts per for 5 years Interest rate = 6% From Table S7.2 X = S = RX S = $7,000(4.212) = $29,484

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, ,0009, ,0009, ,0009,

Present Value With Different Future Receipts Year 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) 3 6,352 =(.794)($8,000) 7,146 =(.794)($9,000) 4 5,145 =(.735)($7,000) 6,615 =(.735)($9,000) Totals$28,470$29,808 Minus initial investment -25,000-26,000 Net present value $3,470$3,808

Capacity Planning Issues To determine the capacity required to achieve the MPS relative to the capacity available To make necessary capacity adjustments before creating crises To determine an the appropriate level of safety capacity To determine the required level of detail and the critical machines and work centers To use an appropriate technique given the tradeoff between accuracy and computational effort

Finite Capacity Planning Example The Single Square Company summarizes the capacity requirements for three of its key resources from each of its three product lines. A typical report (before any action is taken) is shown on the next slide.

Finite Capacity Planning Example (Continued) Key resource typePercent capacity by line MachineNumberShiftsABCTotalRemarks Drill Drill Drill Filer Filer Dryer Dryer Dryer a.What actions would you recommend? (Assume each machine type is equivalent in terms of capacity.) b.What other observations would you have for management, based on the preceding report?

Finite Capacity Planning Example: Single Square Company Key Resource Type% Capacity by Line MachineNumberShiftsTotal ABCTot.Equiv.Remarks Drill Req'd. Drill Move Drill from to 1 Filer Excess Filer _capacity Dryer Increase Dryer to three Dryer shifts

Finite Capacity Planning Example: Single Square Company (continued) a.There is enough capacity now in the Drill and Filer areas. To correct the imbalance in the Drills, it is necessary to move some of the load from Drill 2 to Drill 1. In the case of the Dryers, it is necessary to increase capacity. Adding shifts will provide enough for the current load. b.Why is there so much capacity for the Filers? They can be brought back to one shift and are okay. Secondly, if there is any upward trend in the loads for the Dryers, it behooves management to begin to worry about where they can get additional dryer capacity.

41 Twin Disc Capacity Bill Report

Twin Disc Capacity Bill Example Suppose, in the Twin Disc example, it was decided to move all production for product lines F and I from the Maag grinder (CEA) to the Reishauer grinder (CAB). What's the resulting total percentage of capacity for each machine and the amount for product lines F and I? (Note the Reishauer is three times faster than the Maag grinder so the Maag takes three times as many hours to complete a job.) Assume setup time is negligible.

Twin Disc Capacity Bill Example For Line I Grinding Hours On Maag= 3044 x.08 = On Reishauer= /3 = % of Reishauer= 81.17/950 = 9 New % of Line I on Reishauer= = 10% New % of Line I on Maag= 0% For Line F: Grinding Hours On Maag= 3044 x.05 = On Reishauer= /3 = % of Reishauer= 50.73/950 = 5 New % of Line F on Reishauer= = 7% New % of Line F on Maag= 0% New Totals: New total for Reishauer= = 83% New total for Maag= = 100%

44 Applicon Capacity Status Report

Applicon Capacity Bill Example Applicon has the following capacity bills for items 207 and 208: Work centerHours/unitWork centerHours/unit ALF-A 0.5 ALF-T 0.3 HLT-A 1.0 HLT-T 0.8 MIS-A 0.8 MIS-T 0.6 MVX-A 0.8 MVX-T 0.5 PCB-A 0.5 PCB-P 0.9 PCB-P 1.0 PCB-T 1.4

Applicon Capacity Bill Example a.A customer wants to know if Applicon can deliver 100 units each of items 207 and 208 during the next month (20 working days). Assume there are adequate materials, work center MVX-T'S crew has been increased to one full person (making standard capacity = 160), the increase has come by reducing MVX-A to 6.5 persons. and no other orders have been booked. Use the standard capacity data and conditions in the previous slides as the basis for your analysis. b.Suppose the customer (in part a. above) decided to delay the order for several months. How many units of item 207 alone could be added to the MPS in the next month? How about item 208?

Applicon Analysis:For Item 207 Work CenterUnits Possible ALF-A ( )/0.5 = 820 units HLT-A ( )/1.0 = 362 units MIS-A ( )/0.8 = 662 units MVX-A( )/0.8 = 801 units PCB-A ( )/0.5 = 216 units PCB-P ( )/1.0 = 552 units BUT this is if only item 207 is made.

Applicon If BOTH items are made in equal quantities, PCB-P is a shared work center so: PCB-P( )/( ) = 291 of each. For Item 208 Work CenterUnits Possible ALF-T (80 - 5)/0.3 = 250 units HLT-T( )/0.8 = 94 units MIS-T( )/0.6 = 110 units MVX-T( )/0.5 = 162 units PCB-P( )/( ) = 291 units PCB-T( )/1.4 = 544 units

Applicon a.The analysis says that 100 units of each cannot be added to the MPS without something else being done. The problem is with item 208 in work center HLT-T. To make 100 units of item 208, work center HLT-T will have to work overtime-unless capacity can be provided from a less highly utilized work center or perhaps greater productivity can be gained in some other way. b.The analysis shows that 216 units of item 207 or a total of 94 units of item 208 can be made.

Concluding Principles Capacity plans must be developed concurrently with material plans if the material plans are to be realized. The capacity measure should reflect realizable output from the key resources. It's not always capacity that should change when capacity availability doesn't equal need. Capacity not only must be planned, but use of that capacity must also be monitored and controlled. Capacity planning techniques can be applied to selected key resources (which need not correspond to production work centers).

Concluding Principles The particular capacity planning technique(s) chosen must match the level of detail and actual company circumstances to permit making effective management decisions. The more detail in the capacity planning system, the more data and data base maintenance are required. The better the resource and production planning process, the less difficult the capacity planning process. The better the shop-floor system, the less short-term capacity planning is required. Capacity planning can be simplified in a JIT environment.

End of Lecture 12