Suppl Capacity Planning Heizer and Render Principles of Operations Management, 8e PowerPoint slides by Jeff Heyl

1 - 2 Capacity  The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time  Determines capital requirements and, therefore, fixed costs  Determines if demand will be satisfied  Three time horizons

1 - 3 © 2011 Pearson Education, Inc. publishing as Prentice Hall Planning Over a Time Horizon Figure S7.1 Modify capacityUse capacity 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 * * Difficult to adjust capacity as limited options exist Options for Adjusting Capacity

1 - 4 Design and Effective Capacity  Design capacity is the maximum theoretical output of a system in a given period  Normally expressed as a rate  Effective capacity is the capacity a firm expects to achieve given current operating constraints  Often lower than design capacity  Measuring Capacity: maximum number of units produced in a specific time

1 - 5 © 2011 Pearson Education, Inc. publishing as Prentice Hall 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

1 - 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, hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

1 - 7 © 2011 Pearson Education, Inc. publishing as Prentice Hall 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, hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000 / 201,600 = 73.4%

1 - 8 © 2011 Pearson Education, Inc. publishing as Prentice Hall 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, 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%

1 - 9 © 2011 Pearson Education, Inc. publishing as Prentice Hall 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, hour shifts Efficiency = 84.6% Efficiency of new line = 75% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

Capacity and Strategy  Sustained profits come from building competitive advantage, not just from a good financial return on a specific process.  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

Capacity Considerations 1. Forecast demand accurately: whatever the new product, its prospects and the life cycle of existing products must be determined. 2. Understand the technology and capacity increments: Aid technology decisions by analysis of cost, human resources, quality, and reliability. 3. Find the optimum operating level (volume): If smaller, fixed cost is too burdensome, if larger, the facility becomes more than one manger task 1. Build for change: Build flexibility into facility and equipment

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

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

© 2011 Pearson Education, Inc. publishing as Prentice Hall Complementary Demand Patterns 4,000 – 3,000 – 2,000 – 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) Combining both demand patterns reduces the variation Snowmobile motor sales Jet ski engine sales Figure S7.3

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

© 2011 Pearson Education, Inc. publishing as Prentice Hall Bottleneck Analysis and Theory of Constraints  Each work area can have its own unique capacity  Capacity analysis determines the throughput capacity of workstations in a system  A bottleneck is a limiting factor or constraint  A bottleneck has the lowest effective capacity in a system

Process Times for Stations, Systems, and Cycles process time of a station  The process time of a station is the time to produce a unit at that single workstation process time of a system  The process time of a system is the time of the longest process in the system … the bottleneck process cycle time  The process cycle time is the time it takes for a product to go through the production process with no waiting These two might be quite different!

© 2011 Pearson Education, Inc. publishing as Prentice Hall A Three-Station Assembly Line Figure S7.4 2 min/unit4 min/unit3 min/unit ABC

© 2011 Pearson Education, Inc. publishing as Prentice Hall Process Times for Stations, Systems, and Cycles system process time  The system process time is the process time of the bottleneck after dividing by the number of parallel operations system capacity  The system capacity is the inverse of the system process time process cycle time  The process cycle time is the total time through the longest path in the system

© 2011 Pearson Education, Inc. publishing as Prentice Hall Capacity Analysis  Two identical sandwich lines  Lines have two workers and three operations  All completed sandwiches are wrapped Wrap 37.5 sec/sandwich Order 30 sec/sandwich BreadFillToast 15 sec/sandwich 20 sec/sandwich 40 sec/sandwich BreadFillToast 15 sec/sandwich20 sec/sandwich40 sec/sandwich

© 2011 Pearson Education, Inc. publishing as Prentice Hall Capacity Analysis Wrap 37.5 sec Order 30 sec BreadFillToast 15 sec 20 sec 40 sec BreadFillToast 15 sec20 sec40 sec  Toast work station has the longest processing time – 40 seconds  The two lines each deliver a sandwich every 40 seconds so the process time of the combined lines is 40/2 = 20 seconds  At 37.5 seconds, wrapping and delivery has the longest processing time and is the bottleneck  Capacity per hour is 3,600 seconds/37.5 seconds/sandwich = 96 sandwiches per hour  Process cycle time is = seconds

© 2011 Pearson Education, Inc. publishing as Prentice Hall Capacity Analysis  Standard process for cleaning teeth  Cleaning and examining X-rays can happen simultaneously Check out 6 min/unit Check in 2 min/unit Develops X-ray 4 min/unit8 min/unit Dentist Takes X-ray 2 min/unit 5 min/unit X-ray exam Cleaning 24 min/unit

© 2011 Pearson Education, Inc. publishing as Prentice Hall Capacity Analysis  All possible paths must be compared  Cleaning path is = 46 minutes  X-ray exam path is = 27 minutes  Longest path involves the hygienist cleaning the teeth  Bottleneck is the hygienist at 24 minutes  Hourly capacity is 60/24 = 2.5 patients  Patient should be complete in 46 minutes Check out 6 min/unit Check in 2 min/unit Develops X-ray 4 min/unit 8 min/unit Dentist Takes X-ray 2 min/unit 5 min/unit X-ray exam Cleaning 24 min/unit

© 2011 Pearson Education, Inc. publishing as Prentice Hall Theory of Constraints  Five-step process for recognizing and managing limitations Step 1: Step 1:Identify the constraint Step 2: Step 2:Develop a plan for overcoming the constraints Step 3: Step 3:Focus resources on accomplishing Step 2 Step 4: Step 4:Reduce the effects of constraints by offloading work or expanding capability Step 5: Step 5:Once overcome, go back to Step 1 and find new constraints

© 2011 Pearson Education, Inc. publishing as Prentice Hall Bottleneck Management 1. Release work orders to the system at the pace of set by the bottleneck 2. Lost time at the bottleneck represents lost time for the whole system 3. Increasing the capacity of a non-bottleneck station is a mirage 4. Increasing the capacity of a bottleneck increases the capacity of the whole system

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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 verify  Time value of money is often ignored Assumptions

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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 – 800 – 700 – 600 – 500 – 400 – 300 – 200 – 100 – – |||||||||||| Cost in dollars Volume (units per period) Figure S7.5

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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)] = = $22, $10, BEP x = = = 5,714 F P - V $10, ( )

© 2011 Pearson Education, Inc. publishing as Prentice Hall Break-Even Example 50,000 – 40,000 – 30,000 – 20,000 – 10,000 – – |||||| 02,0004,0006,0008,00010,000 Dollars Units Fixed costs Total costs Revenue Break-even point

© 2011 Pearson Education, Inc. publishing as Prentice Hall Break-Even Example BEP $ = F ∑ 1 - x (W i ) ViPiViPi 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

© 2011 Pearson Education, Inc. publishing as Prentice Hall Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$5.00$3.009,000 Drink ,000 Baked potato ,000 Fixed costs = $3,000 per month

Multiproduct Example Annual Forecasted ItemPriceCostSales Units Sandwich$5.00$3.009,000 Drink ,000 Baked potato ,000 Fixed costs = $3,000 per month Sandwich$5.00$ $45, Drinks , Baked , potato $72, AnnualWeighted SellingVariableForecasted% ofContribution Item (i)Price (P)Cost (V)(V/P)1 - (V/P)Sales $Sales(col 5 x col 7)

Multiproduct Annual Forecasted ItemPriceCostSales Units Sandwich$5.00$3.009,000 Drink ,000 Baked potato ,000 Fixed costs = $3,000 per month Sandwich$5.00$ $45, Drinks , Baked , potato $72, 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 = = $76,759 $3,000 x Daily sales = = $ $76, days.621 x $ $5.00 = 30.6  31 sandwiches per day

Reducing Risk with Incremental Changes (a)Leading demand with incremental expansion Demand Expected demand New capacity (c)Attempts to have an average capacity with incremental expansion Demand New capacity Expected demand (b)Capacity lags demand with incremental expansion Demand New capacity Expected demand Figure S7.6

Expected Monetary Value (EMV) and Capacity Decisions  Determine states of nature  Future demand  Market favorability  Analyzed using decision trees  Hospital supply company  Four alternatives

Expected Monetary Value (EMV) and Capacity Decisions -$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

© 2011 Pearson Education, Inc. publishing as Prentice Hall Expected Monetary Value (EMV) and Capacity Decisions -$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

© 2011 Pearson Education, Inc. publishing as Prentice Hall Expected Monetary Value (EMV) and Capacity Decisions -$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 -$14,000 $13,000$18,000

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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 F = P(1 + i) N In general: Solving for P: While this works fine, it is cumbersome for larger values of N

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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 Portion of Table S7.1 Year6%8%10%12%14%

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

© 2011 Pearson Education, Inc. publishing as Prentice Hall Present Value of an Annuity Portion of Table S7.2 Year6%8%10%12%14%

© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

Limitations 1. Investments with the same NPV may have different projected lives and salvage values 2. Investments with the same NPV may have different cash flows 3. Assumes we know future interest rates 4. Payments are not always made at the end of a period