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Capacity
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OPERATIONS MANAGEMENT
CAPACITY PLANNING
CAPACITY
• No of beds in the hospital• Size of bus • No of counters in a bank• No of copies to be printed every hour by a
printer • Bandwidth of a communication network • No of cars to be produced per day
CAPACITY
• “ Maximum rate of output from a process” within a defined time
• Theoretical capacity vs. Effective capacity• 250 ml glass• Output of assembly line• Ground realities decide the effective capacity• Capacity choices influence financial performance• Can affect the Industry
CAPACITY
• Capacity can vary– Day-to-day uncertainties such as employee
absences, equipment breakdowns, and material-delivery delays
– Product Mix
MEASURES OF CAPACITY
• Output units are homogeneous : - Battery manufacturing unit
• Output units are diverse : - Restaurant - Jobbing machine shop
MEASUREMENTS OF CAPACITY
Input Rate Capacity – Commonly used for service operations where
output measures are particularly difficult• Hospitals : No of beds • Airlines : seat-miles per month• Movie theatres :No of seats
CAPACITY PLANNING PROCESS
• Estimate the capacity of the present facilities.• Forecast the long-range future capacity needs.• Identify and analyze sources of capacity to
meet these needs.• Select from among the alternative sources of
capacity.
ISSUES
• Accuracy of demand forecast• Market trends : market size & location• Technological innovation• New products• Process innovation to affect production
method• Extent of capacity enhancement : strategy
STRATEGIC CAPACITY PLANNING
• Capacity level of capital intensive resources : - Equipments - Facilities - Manpower• It impacts : - Response rate - Cost structure - Inventory policy - Management & staff support
CAPACITY STRATEGIESCAPACITY CUSHION
UNIT
CAPACITY
DEMAND
TIME
CAPACITY STRATEGIESCAPACITY CUSHION
UNITCAPACITY
DEMAND
TIME
CAPACITY STRATEGIES
DEMAND CUSHION
UNIT
CAPACITY
DEMAND
TIME
CAPACITY STRATEGIESBALANCED APPROACH
UNITCAPACITY
DEMAND
TIME
OPTIONS
• Overtime / Multiple shifts• Lost sales• Increase capacity in small steps • Increase capacity in large steps • Partially use alternate source• Establish new location for the additional
capacity• Relocate the entire operation
RETURNS TO SCALE
• Increasing returns to scale
• Law of diminishing returns
• Decreasing returns to scale
• Best operating level
Economies of Scale
• Declining costs result from:– Fixed costs being spread over more and more
units– Longer production runs result in a smaller
proportion of labor being allocated to setups– Proportionally less material scrap– … and other economies
Diseconomies of Scale
• Increasing costs result from increased congestion of workers and material, which contributes to:– Increasing inefficiency– Difficulty in scheduling– Damaged goods– Reduced morale– Increased use of overtime– … and other diseconomies
Economies and Diseconomies of ScaleAverage Unit
Cost of Output
Annual Volume (units)
Best Operating Level
Economiesof Scale
Diseconomiesof Scale
ECONOMIES OF SCALEVOL
VARIABLE COST FIXED COST
Rs /unit Rs
500 60 200000750 60 2000001000 60 2000001250 60 2000001500 60 2000001750 60 2000002000 60 2000002250 60 2000002500 60 2000002750 60 2000003000 60 2000003250 180 2000003500 180 2000003750 180 2000004000 180 2000004250 180 2000004500 180 2000004750 360 2000005000 360 2000005250 360 2000005500 360 200000
ECONOMIES OF SCALE
VOLVARIABLE
COST FIXED COSTVARIABLE
COSTTOTAL COST
AVERAGE FIXED COST
AVERAGE VARIABLE
COST
AVERAGE TOTAL COST
Rs /unit Rs Rs Rs Rs /unit Rs /unit Rs /unit
500 60 200000 30000 230000 400 60 460750 60 200000 45000 245000 267 60 3271000 60 200000 60000 260000 200 60 2601250 60 200000 75000 275000 160 60 2201500 60 200000 90000 290000 133 60 1931750 60 200000 105000 305000 114 60 1742000 60 200000 120000 320000 100 60 1602250 60 200000 135000 335000 89 60 1492500 60 200000 150000 350000 80 60 1402750 60 200000 165000 365000 73 60 1333000 60 200000 180000 380000 67 60 1273250 180 200000 225000 425000 62 69 1313500 180 200000 270000 470000 57 77 1343750 180 200000 315000 515000 53 84 1374000 180 200000 360000 560000 50 90 1404250 180 200000 405000 605000 47 95 1424500 180 200000 450000 650000 44 100 1444750 360 200000 540000 740000 42 114 1565000 360 200000 630000 830000 40 126 1665250 360 200000 720000 920000 38 137 1755500 360 200000 810000 1010000 36 147 184
ECONOMIES OF SCALE
0
50
100
150
200
250
300
350
400
450
500
750
1250
1750
2250
2750
3250
3750
4250
4750
5250
VOLUME
UNIT
CO
ST MARGINAL COST Rs /unit
AVERAGE FIXED COST Rs /unit
AVERAGE VARIABLE COST Rs /unit
AVERAGE TOTAL COST Rs /unit
CAPACITY-PLANNING DECISIONS
– Break-Even Analysis – Present-Value /Future value Analysis– Computer Simulation – Internal Rate of return Analysis – Linear Programming – Decision Tree Analysis
FACTORS• Forecast of future demand
• Mature products
• New products : Optimistic & pessimistic
MATURE PRODUCTS DEMAND VS. CAPACITY
2004 2006 2009 2014
DEMAND FORECAST 10000 12000 15000 20000
FACILITY ACAPACITY 11000 11000 11000 11000
SLACK 1000 (1000) (4000) (9000)
FACILITY BCAPACITY 10000 10000 10000 10000
SLACK 0 (2000) (5000) (10000)
FACILITY CCAPACITY 15000 15000 15000 15000
SLACK 5000 3000 0 (5000)
NEW PRODUCTPESSIMISTIC FORECAST
2004 2006 2009 2014
DEMAND FORECAST 10000 11000 12800 16000
FACILITY ACAPACITY 11000 11000 11000 11000
SLACK 1000 0 (1800) (5000)
FACILITY BCAPACITY 10000 10000 10000 10000
SLACK 0 (1000) (2800) (6000)
FACILITY CCAPACITY 15000 15000 15000 15000
SLACK 5000 4000 2200 (1000)
NEW PRODUCTOPTIMISTIC FORECAST
2004 2006 2009 2014
DEMAND FORECAST 10000 14500 25000 62000
FACILITY ACAPACITY 11000 11000 11000 11000
SLACK 1000 (3500) (14000) (51000)
FACILITY BCAPACITY 10000 10000 10000 10000
SLACK 0 (4500) (15000) (52000)
FACILITY CCAPACITY 15000 15000 15000 15000
SLACK 5000 500 (10000) (47000)
Break-Even AnalysisBEPx =break-even point in unitsBEP$ =break-even point in dollarsP = price per unit (after all discounts)
x = number of units producedTR = total revenue = PxF = fixed costsV = variable cost per unitTC = total costs = F + Vx
BEP$ = BEPx P
= P
=
=
F(P - V)/P
FP - V
F1 - V/P
Profit = TR - TC= Px - (F + Vx)= Px - F - Vx= (P - V)x - F
Break-Even AnalysisBEPx =break-even point in unitsBEP$ =break-even point in dollarsP = price per unit (after all discounts)
x = number of units producedTR = total revenue = PxF = fixed costsV = variable cost per unitTC = total costs = F + Vx
TR = TCor
Px = F + Vx
Break-even point occurs when
BEPx =F
P - V
Break-Even Multiproduct Case
Multiproduct Example
Annual ForecastedItem Price Cost Sales UnitsSandwich $2.95 $1.25 7,000Soft drink .80 .30 7,000Baked potato 1.55 .47 5,000Tea .75 .25 5,000Salad bar 2.85 1.00 3,000
Fixed costs = $3,500 per month
Multiproduct Example
Sandwich $2.95 $1.25 .42 .58 $20,650 .446 .259Soft drink .80 .30 .38 .62 5,600 .121 .075Baked 1.55 .47 .30 .70 7,750 .167 .117 potatoTea .75 .25 .33 .67 3,750 .081 .054Salad bar 2.85 1.00 .35 .65 8,550 .185 .120
$46,300 1.000 .625
Annual WeightedSelling 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
BREAK EVEN VALUE
DAILY SALES
Annual WeightedSelling Variable Forecasted % of Contribution
Item (i ) Price (P ) Cost (V ) (V/P ) 1 - (V/P ) Sales $ Sales (col 5 x col 7 )
Sandwich $2.95 $1.25 0.42 0.58 20,650 44.6 0.26Soft drink 0.8 0.3 0.38 0.63 5,600 12.1 0.08Baked 1.55 0.47 0.30 0.70 7,750 16.7 0.12 potatoTea 0.75 0.25 0.33 0.67 3,750 8.1 0.05Salad bar 2.85 1 0.35 0.65 8,550 18.5 0.12
46,300 100
DECISION TREEOPTIMISTIC
EXPECTEDPROPOSAL 1
PESSIMISTIC
OPTIMISTIC
EXPECTED
PROPOSAL 2 PESSIMISTIC
OPTIMISTICPROPOSAL 3
EXPECTED
PESSIMISTIC