Capacity Planning

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Capacity<br/>Design and Effective Capacity<br/>Capacity and Strategy<br/>Capacity Considerations<br/>Managing Demand<br/>Capacity Planning<br/>

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

Outline : Outline Capacity Design and Effective Capacity Capacity and Strategy Capacity Considerations Managing Demand Capacity Planning

Outline – Continued : Outline – Continued Breakeven Analysis Single-Product Case Multiproduct Case Applying Decision Trees to Capacity Decisions

Outline – Continued : Outline – Continued Applying Investment Analysis to Strategy-Driven Investments Investment, Variable Cost, and Cash Flow Net Present Value

Learning Objectives : Learning Objectives When you complete this supplement, you should be able to: Identify or Define: Capacity Design capacity Effective capacity Utilization

Learning Objectives : Learning Objectives When you complete this supplement, you should be able to: Describe or Explain: Capacity considerations Net present value analysis Break-even analysis Financial considerations Strategy-driven investments

Capacity : 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

Planning Over a Time Horizon : Modify capacity Use capacity Planning Over a Time Horizon Intermediate-range planning Subcontract Add personnel Add equipment Build 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

Design and Effective Capacity : 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

Utilization and Efficiency : 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

Bakery Example : 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

Bakery Example : 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

Bakery Example : 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%

Bakery Example : 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%

Bakery Example : 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%

Bakery Example : 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%

Bakery Example : 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

Bakery Example : 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

Capacity and Strategy : 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

Managing Demand : 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 complimentary demand patterns

Economies and Diseconomies of Scale : 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 25 50 75 Average unit cost (dollars per room per night) Figure S7.2

Capacity Considerations : Capacity Considerations Forecast demand accurately Understanding the technology and capacity increments Find the optimal operating level (volume) Build for change

Tactics for Matching Capacity to Demand : Tactics for Matching Capacity to Demand Making staffing changes Adjusting equipment and processes Purchasing additional machinery Selling or leasing out existing equipment Improving methods to increase throughput Redesigning the product to facilitate more throughput

Complementary Demand Patterns : 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) By combining both, the variation is reduced Snowmobile sales Jet ski sales Figure S7.3

Approaches to Capacity Expansion : 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

Approaches to Capacity Expansion : Approaches to Capacity Expansion (a) Leading demand with incremental expansion Expected demand Figure S7.4 New capacity Demand Time (years) 1 2 3

Approaches to Capacity Expansion : Approaches to Capacity Expansion (b) Leading demand with one-step expansion New capacity Expected demand Figure S7.4 Demand Time (years) 1 2 3

Approaches to Capacity Expansion : Approaches to Capacity Expansion (c) Capacity lags demand with incremental expansion Expected demand Figure S7.4 Demand Time (years) 1 2 3 New capacity

Approaches to Capacity Expansion : Approaches to Capacity Expansion (d) Attempts to have an average capacity with incremental expansion Expected demand Figure S7.4 New capacity Demand Time (years) 1 2 3

Break-Even Analysis : 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 : 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 : 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

Break-Even Analysis : 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 – – | | | | | | | | | | | | 0 100 200 300 400 500 600 700 800 900 1000 1100 Cost in dollars Volume (units per period) Figure S7.5

Break-Even Analysis : 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

Break-Even Analysis : 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

Break-Even Example : 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 ) $10,000 1 - [(1.50 + .75)/(4.00)]

Break-Even Example : 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 ) $10,000 1 - [(1.50 + .75)/(4.00)] = = $22,857.14 $10,000 .4375 BEP x = = = 5,714 F P - V $10,000 4.00 - (1.50 + .75)

Break-Even Example : Break-Even Example 50,000 – 40,000 – 30,000 – 20,000 – 10,000 – – | | | | | | 0 2,000 4,000 6,000 8,000 10,000 Dollars Units Fixed costs Total costs Revenue Break-even point

Break-Even Example : Break-Even Example BEP $ = F ∑ 1 - x ( W i ) V i P i Multiproduct Case where V = 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 : Multiproduct Example 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 5,000 Tea .75 .25 5,000 Salad bar 2.85 1.00 3,000 Fixed costs = $3,500 per month

Multiproduct Example : Multiproduct Example 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 5,000 Tea .75 .25 5,000 Salad bar 2.85 1.00 3,000 Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259 Soft drink .80 .30 .38 .62 5,600 .121 .075 Baked 1.55 .47 .30 .70 7,750 .167 .117 potato Tea .75 .25 .33 .67 3,750 .081 .054 Salad bar 2.85 1.00 .35 .65 8,550 .185 .120 $46,300 1.000 .625 Annual Weighted Selling Variable Forecasted % of Contribution 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 : Multiproduct Example 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 5,000 Tea .75 .25 5,000 Salad bar 2.85 1.00 3,000 Fixed costs = $3,500 per month Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259 Soft drink .80 .30 .38 .62 5,600 .121 .075 Baked 1.55 .47 .30 .70 7,750 .167 .117 potato Tea .75 .25 .33 .67 3,750 .081 .054 Salad bar 2.85 1.00 .35 .65 8,550 .185 .120 $46,300 1.000 .625 Annual Weighted Selling Variable Forecasted % of Contribution Item ( i ) Price ( P ) Cost ( V ) ( V/P ) 1 - ( V/P ) Sales $ Sales ( col 5 x col 7 ) BEP $ = F ∑ 1 - x ( W i ) V i P i = = $67,200 $3,500 x 12 .625 Daily sales = = $215.38 $67,200 312 days .446 x $215.38 $2.95 = 32.6  33 sandwiches per day

Decision Trees and Capacity Decision : 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 : 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) : Net Present Value (NPV) where F = future value P = present value i = interest rate N = number of years P = F (1 + i ) N

NPV Using Factors : NPV Using Factors P = = FX F (1 + i ) N where X = a factor from Table S7.1 defined as = 1/(1 + i ) N and F = future value Year 5% 6% 7% … 10% 1 .952 .943 .935 .909 2 .907 .890 .873 .826 3 .864 .840 .816 .751 4 .823 .792 .763 .683 5 .784 .747 .713 .621 Portion of Table S7.1

Present Value of an Annuity : Present Value of an Annuity An annuity is an investment which generates uniform equal payments S = RX where 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

Present Value of an Annuity : Present Value of an Annuity Portion of Table S7.2 Year 5% 6% 7% … 10% 1 .952 .943 .935 .909 2 1.859 1.833 1.808 1.736 3 2.723 2.676 2.624 2.487 4 4.329 3.465 3.387 3.170 5 5.076 4.212 4.100 3.791

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