S7 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall S7 Capacity and Constraint Management PowerPoint presentation to accompany Heizer and Render Operations Management, 10e Principles of Operations Management, 8e PowerPoint slides by Jeff Heyl

2 Capacity Planning Capacity is the upper limit or ceiling on the load that an operating unit can handle. The basic questions in capacity handling are: –What kind of capacity is needed? –How much is needed? –When is it needed?

3 Impacts ability to meet future demands Affects operating costs Major determinant of initial costs Involves long-term commitment Affects competitiveness Affects ease of management Importance of Capacity Decisions

S7 - 4 When to increase capacity? Should we expand capacity before the demand is there or wait until demand is more certain? © 2011 Pearson Education, Inc. publishing as Prentice Hall

S7 - 5© 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

© Wiley Measuring Capacity Examples There is no one best way to measure capacity Output measures like kegs per day are easier to understand With multiple products, inputs measures work better

7 Various Capacities Design capacity –Maximum obtainable output Effective capacity, expected variations –Maximum capacity subject to planned and expected variations such as maintenance, coffee breaks, scheduling conflicts. Actual output, unexpected variations and demand –Rate of output actually achieved--cannot exceed effective capacity. It is subject to random disruptions: machine break down, absenteeism, material shortages and most importantly the demand.

S7 - 8© 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

9 Major Determinants of Effective Capacity/Output Facilities, layout Products or services, product mixes/setups Processes, quality Human considerations, motivation Operations, scheduling and synchronization problems Supply Chain factors, material shortages

S7 - 10© 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

S7 - 11© 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

S7 - 12© 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%

S7 - 13© 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%

S7 - 14© 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%

S7 - 15© 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%

S7 - 16© 2011 Pearson Education, Inc. publishing as Prentice Hall Bakery Example: Estimating Output of a New Facility They are considering adding a second production line and they plan to hire new employees and train them to operate this new line Effective capacity on this new line = 175,000 rolls which is the same on the first line However, due to new hires they expect that efficiency of this new line will be 75% rather than 84.6% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

S7 - 17© 2011 Pearson Education, Inc. publishing as Prentice Hall Capacity Considerations 1.Forecast demand accurately 2.Understand the technology and capacity increments (restaurants Vs car manufacturing) 3.Find the optimum operating level (volume) 4.Build for change (build flexibility into the facility )

© Wiley Best Operating Level The Best Operating Level is the output that results in the lowest average unit cost Economies of Scale: Where the cost per unit of output drops as volume of output increases Spread the fixed costs of buildings & equipment over multiple units Diseconomies of Scale: Where the cost per unit rises as volume increases Often caused by congestion (overwhelming the process with too much work-in-process) and scheduling complexity

© Wiley Best Operating Level and Size Alternative 1: Purchase one large facility, requiring one large initial investment Alternative 2: Add capacity incrementally in smaller chunks as needed

S7 - 20© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

S7 - 21© 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) Jet ski engine sales Figure S7.3

S7 - 22© 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) Snowmobile motor sales Jet ski engine sales Figure S7.3

S7 - 23© 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

S Demand and Capacity Management in the Service Sector Pressures are: Inability to store services - Capacity must me matched with the timing of demand Degree of volatility of demand - Peak demand periods © 2011 Pearson Education, Inc. publishing as Prentice Hall

S7 - 25© 2011 Pearson Education, Inc. publishing as Prentice Hall Demand and Capacity Management in the Service Sector  Demand management (scheduling customers)  Appointment, reservations, FCFS rule  Capacity management (scheduling workforce)  Full time, temporary, part-time staff

S7 - 26© 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

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S7 - 28© 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

S7 - 29© 2011 Pearson Education, Inc. publishing as Prentice Hall A Three-Station Assembly Line Process time of stations: 2, 4 and 3 min/unit Process time for the system: 4 min/unit Process Cycle Time= = 9 min/unit System Capacity = ¼*60(min)= 15 units/hour Figure S7.4 2 min/unit4 min/unit3 min/unit ABC

S7 - 30© 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

S7 - 31© 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  It seems that the toast work station has the longest processing time – 40 seconds, but the two lines work in parallel and each deliver a sandwich every 40 seconds so the process time of the toast work station is 40/2 = 20 seconds per sandwich.  Order: 30 seconds, Combined Assembly:20 seconds, Wrapping:37.5 seconds  With 37.5 seconds, wrapping station has the longest processing time and it is the bottleneck. So process time of the system is 37.5 sec.  System capacity per hour is (1/37.5)*3,600 seconds = 96 sandwiches per hour  Process cycle time is = seconds

S7 - 32© 2011 Pearson Education, Inc. publishing as Prentice Hall Capacity Analysis Example S4, pg.322  Standard process for cleaning teeth  Cleaning and examining X-rays can happen simultaneously Customer pays 6 min/unit Customer Checks in 2 min/unit A Lab Ass Develops X-ray 4 min/unit8 min/unit Dentist re-processes A Lab Ass. Takes X-ray 2 min/unit 5 min/unit Dentist Examines X-ray and processes Hygienist Cleans the teeth 24 min/unit

S7 - 33© 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, so the process cycle time is 46 min. The patient will be out of door after 46 min.  Bottleneck is the hygienist at 24 minutes which is the process time of the system  System capacity is (1/24)*60 min = 2.5 patients/per hour 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

S7 - 34© 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

S7 - 35© 2011 Pearson Education, Inc. publishing as Prentice Hall 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

S7 - 36© 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

S7 - 37© 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

S7 - 38© 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

S7 - 39© 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

S7 - 40© 2011 Pearson Education, Inc. publishing as Prentice Hall 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)]

S7 - 41© 2011 Pearson Education, Inc. publishing as Prentice Hall 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, ( )

S7 - 42© 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

S7 - 43© 2011 Pearson Education, Inc. publishing as Prentice Hall Multiproduct Break-Even Analysis BEP $ = F ∑ 1 - x (W i ) ViPiViPi Each product’s contribution is weighted by its proportion of sales whereV i = variable cost per unit P i = price per unit F= fixed costs W i = percent each product is of total dollar sales i= each product

S Multiproduct Example Fixed costs = $3,000 per month ITEMPRICECOSTANNUAL FORECASTED SALES UNITS Sandwich$5.00$3.009,000 Drink ,000 Baked potato , ITEM ( i ) SELLING PRICE ( P ) VARIABLE COST ( V )(V/P)(V/P)1 - ( V / P ) ANNUAL FORECASTED SALES $ % OF SALES WEIGHTED CONTRIBUTION (COL 5 X COL 7) Sandwich$5.00$ $45, Drinks , Baked potato , $72,

S7 - 45© 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 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

S Reducing Risk with Incremental Changes (a)Leading demand with incremental expansion Demand Expected demand New capacity (d)Attempts to have an average capacity with incremental expansion Demand New capacity Expected demand (c)Lagging demand with incremental expansion Demand New capacity Expected demand Figure S7.6 (b)Leading demand with a one-step expansion Demand Expected demand New capacity

S7 - 47© 2011 Pearson Education, Inc. publishing as Prentice Hall Reducing Risk with Incremental Changes (a)Leading demand with incremental expansion Expected demand Figure S7.6 New capacity Demand Time (years) 123

S Reducing Risk with Incremental Changes (Demand growth is usually in small units, while capacity additions are likely to be both instantaneous and in large units) (b)Leading demand with a one-step expansion Expected demand Figure S7.6 New capacity Demand Time (years) 123

S7 - 49© 2011 Pearson Education, Inc. publishing as Prentice Hall Reducing Risk with Incremental Changes (c)Capacity lags demand with incremental expansion Expected demand Figure S7.6 Demand Time (years) 123 New capacity

S7 - 50© 2011 Pearson Education, Inc. publishing as Prentice Hall Reducing Risk with Incremental Changes (d)Attempts to have an average capacity with incremental expansion Expected demand Figure S7.6 New capacity Demand Time (years) 123

S7 - 51© 2011 Pearson Education, Inc. publishing as Prentice Hall Expected Monetary Value (EMV) and Capacity Decisions  Determine states of nature  Future demand  Market favorability  Analyzed using decision trees  Hospital supply company  Four alternatives

S7 - 52© 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

S7 - 53© 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

S7 - 54© 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

S EMV Applied to Capacity Decision ▶ Southern Hospital Supplies capacity expansion EMV (large plant)= (.4)($100,000) + (.6)(–$90,000) = –$14,000 EMV (medium plant)= (.4)($60,000) + (.6)(–$10,000) = +$18,000 EMV (small plant)= (.4)($40,000) + (.6)(–$5,000) = +$13,000 EMV (do nothing)= $0