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