Chapter 7
Transcript of Chapter 7
© 2006 Prentice Hall, Inc. S7 – 1
Operations ManagementOperations ManagementSupplement 7 – Capacity PlanningSupplement 7 – Capacity Planning
© 2006 Prentice Hall, Inc.
PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 6eOperations Management, 8e
© 2006 Prentice Hall, Inc. S7 – 2
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
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Modify capacity Use capacity
Planning Over a Time Horizon
Intermediate-range planning
Subcontract Add personnelAdd equipment Build or use inventory Add shifts
Short-range planning
Schedule jobsSchedule personnel Allocate machinery*
Long-range planning
Add facilitiesAdd long lead time equipment *
* Limited options exist
Figure S7.1
© 2006 Prentice Hall, Inc. S7 – 4
Design and Effective Capacity
Design capacity is the maximum theoretical output of a systemNormally expressed as a rate
Effective capacity is the capacity a firm expects to achieve given current operating constraintsOften lower than design capacity
© 2006 Prentice Hall, Inc. S7 – 5
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
© 2006 Prentice Hall, Inc. S7 – 6
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 – ‘8 hour shifts’
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
© 2006 Prentice Hall, Inc. S7 – 7
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 – ‘8 hour shifts’
Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls
© 2006 Prentice Hall, Inc. S7 – 8
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery 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%
© 2006 Prentice Hall, Inc. S7 – 9
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery 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%
© 2006 Prentice Hall, Inc. S7 – 10
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery 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%
© 2006 Prentice Hall, Inc. S7 – 11
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery 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%
© 2006 Prentice Hall, Inc. S7 – 12
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery 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
© 2006 Prentice Hall, Inc. S7 – 13
Bakery Example
Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, three- ‘8 hour shifts’Efficiency = 84.6%Efficiency of new line = 75%
Expected Output = (Effective Capacity)(Efficiency)
= (175,000)(.75) = 131,250 rolls
© 2006 Prentice Hall, Inc. S7 – 14
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
© 2006 Prentice Hall, Inc. S7 – 15
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 Rooms25 50 75
Av
era
ge
un
it c
os
t(d
olla
rs p
er
roo
m p
er n
igh
t)
Figure S7.2
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Capacity Considerations
Forecast demand accurately Understanding the technology
and capacity increments Find the optimal operating level
(volume) Build for change
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Approaches to Capacity Expansion
(a) Leading demand with incremental expansion
Dem
and
Expected demand
New capacity
(b) Leading demand with one-step expansion
Dem
and
New capacity
Expected demand
(d) Attempts to have an average capacity with incremental expansion
Dem
and
New capacity Expected
demand
(c) Capacity lags demand with incremental expansion
Dem
and
New capacity
Expected demand
Figure S7.4
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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
© 2006 Prentice Hall, Inc. S7 – 19
Break-Even Analysis
Fixed costs are costs that continue even if no units are producedDepreciation, taxes, debt, mortgage
payments
Variable costs are costs that vary with the volume of units producedLabor, materials, portion of utilitiesContribution is the difference between
selling price and variable cost
© 2006 Prentice Hall, Inc. S7 – 20
Break-Even Analysis
Costs and revenue are linear functionsGenerally not the case in the real
world
We actually know these costsVery difficult to accomplish
There is no time value of money
Assumptions
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Profit corri
dor
Loss
corridor
Break-Even AnalysisTotal revenue line
Total cost line
Variable cost
Fixed cost
Break-even pointTotal cost = Total revenue
–
900 –
800 –
700 –
600 –
500 –
400 –
300 –
200 –
100 –
–| | | | | | | | | | | |
0 100 200 300 400 500 600 700 800 900 10001100
Co
st in
do
llars
Volume (units per period)Figure S7.5
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Break-Even Analysis
BEPx =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 costsTC = Total costs = F + Vx
TR = TCor
Px = F + Vx
Break-even point occurs when
BEPx =F
P - V
© 2006 Prentice Hall, Inc. S7 – 23
Break-Even Analysis
BEPx =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 costsTC = 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
© 2006 Prentice Hall, Inc. S7 – 24
Break-Even Example
Fixed costs = $10,000 Material = $.75/unitDirect labor = $1.50/unit Selling price = $4.00 per unit
BEP$ = =F
1 - (V/P)$10,000
1 - [(1.50 + .75)/(4.00)]
© 2006 Prentice Hall, Inc. S7 – 25
Break-Even Example
Fixed costs = $10,000 Material = $.75/unitDirect 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
BEPx = = = 5,714F
P - V$10,000
4.00 - (1.50 + .75)
© 2006 Prentice Hall, Inc. S7 – 26
Break-Even Example
BEP$ =F
∑ 1 - x (Wi)Vi
Pi
Multiproduct Case
where V = variable cost per unitP = price per unitF = fixed costs
W = percent each product is of total dollar salesi = each product
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Multiproduct Case Derivation
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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
© 2006 Prentice Hall, Inc. S7 – 29
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
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
© 2006 Prentice Hall, Inc. S7 – 30
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
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)
BEP$ =F
∑ 1 - x (Wi)Vi
Pi
= = $67,200$3,500 x 12
.625
Daily sales = = $215.38
$67,200312 days
.446 x $215.38$2.95 = 32.6 33
sandwichesper day
© 2006 Prentice Hall, Inc. S7 – 31
Decision Trees and Capacity Decision
-$14,000
$13,000
$18,000
-$90,000Market 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
© 2006 Prentice Hall, Inc. S7 – 32
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
© 2006 Prentice Hall, Inc. S7 – 33
Net Present Value (NPV)
where F = future valueP = present valuei = interest rate
N = number of years
P =F
(1 + i)N
© 2006 Prentice Hall, Inc. S7 – 34
NPV Using Factors
P = = FXF
(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 .9092 .907 .890 .873 .8263 .864 .840 .816 .7514 .823 .792 .763 .6835 .784 .747 .713 .621
Portion of Table S7.1
© 2006 Prentice Hall, Inc. S7 – 35
Present Value of an Annuity
An annuity is an investment which generates uniform equal payments
S = RX
where X = factor from Table S7.2S = present value of a series of uniform annual receiptsR = receipts that are received every year of the life of the investment
© 2006 Prentice Hall, Inc. S7 – 36
Present Value of an Annuity
© 2006 Prentice Hall, Inc. S7 – 37
Present Value of an Annuity
Portion of Table S7.2
Year 5% 6% 7% … 10%
1 .952 .943 .935 .9092 1.859 1.833 1.808 1.7363 2.723 2.676 2.624 2.4874 4.329 3.465 3.387 3.1705 5.076 4.212 4.100 3.791
© 2006 Prentice Hall, Inc. S7 – 38
Process, Volume, and Variety
Process Focusprojects, job shops
(machine, print, carpentry)
Standard Register
Repetitive(autos, motorcycles)
Harley Davidson
Product Focus(commercial
baked goods, steel, glass)Nucor Steel
High Varietyone or few units per run, high variety(allows customization)
Changes in Modulesmodest runs, standardized modules
Changes in Attributes (such as grade, quality, size, thickness, etc.) long runs only
Mass Customization(difficult to achieve, but huge rewards)Dell Computer Co.
Poor Strategy (Both fixed and variable costs
are high)
Low Volume
Repetitive Process
High Volume
VolumeFigure 7.1