Heizer om10 ch07_s-capacity

10/16/2010

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S7S7 Capacity and Constraint Management

Capacity and Constraint Management

S7 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall

PowerPoint presentation to accompany PowerPoint presentation to accompany Heizer and Render Heizer and Render Operations Management, 10e Operations Management, 10e Principles of Operations Management, 8ePrinciples of Operations Management, 8e

PowerPoint slides by Jeff Heyl

OutlineOutline

CapacityDesign and Effective CapacityCapacity and Strategy


Capacity ConsiderationsManaging DemandDemand and Capacity Management in the Service Sector

Outline Outline –– ContinuedContinuedBottleneck Analysis and Theory of Constraints

Process Times for Stations, Systems, and Cycles


Theory of ConstraintsBottleneck Management

Break-Even AnalysisSingle-Product CaseMultiproduct Case

Outline Outline –– ContinuedContinuedReducing Risk with Incremental ChangesApplying Expected Monetary Value to Capacity Decisions


Applying Investment Analysis to Strategy-Driven Investments

Investment, Variable Cost, and Cash FlowNet Present Value

Learning ObjectivesLearning ObjectivesWhen you complete this supplement, When you complete this supplement, you should be able to:you should be able to:

1. Define capacity


2. Determine design capacity, effective capacity, and utilization

3. Perform bottleneck analysis4. Compute break-even analysis

Learning ObjectivesLearning ObjectivesWhen you complete this supplement, When you complete this supplement, you should be able to:you should be able to:

5. Determine the expected monetary value of a capacity decision


value of a capacity decision6. Compute net present value

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Process StrategiesProcess Strategies

The objective of a process strategy is The objective of a process strategy is to build a production process that to build a production process that meets customer requirements and meets customer requirements and product specifications within costproduct specifications within cost


product specifications within cost product specifications within cost and other managerial constraintsand other managerial constraints

CapacityCapacityThe throughput, or the number of units a facility can hold, receive, store, or produce in a period of timeDetermines


ete esfixed costsDetermines if demand will be satisfiedThree time horizons

Planning Over a Time Planning Over a Time HorizonHorizon

Intermediate- Subcontract Add personnel

Long-range planning

Add facilitiesAdd long lead time equipment *

Options for Adjusting Capacity


Figure S7.1

Modify capacity Use capacity

Intermediate-range planning

Subcontract Add personnelAdd equipment Build or use inventory Add shifts

Short-range planning

Schedule jobsSchedule personnel Allocate machinery*

* Difficult to adjust capacity as limited options exist

Design and Effective Design and Effective CapacityCapacity

Design capacity is the maximum theoretical output of a system

N ll d t


Normally expressed as a rateEffective capacity is the capacity a firm expects to achieve given current operating constraints

Often lower than design capacity

Utilization and EfficiencyUtilization and Efficiency

Utilization is the percent of design capacity Utilization is the percent of design capacity achievedachieved

Utilization = Actual output/Design capacity


Efficiency is the percent of effective capacity Efficiency is the percent of effective capacity achievedachieved

p g p y

Efficiency = Actual output/Effective capacity

Bakery ExampleBakery 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

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Utilization = 148,000/201,600 = 73.4%





Utilization = 148,000/201,600 = 73.4%





Utilization = 148,000/201,600 = 73.4%

Efficiency = 148,000/175,000 = 84.6%





Utilization = 148,000/201,600 = 73.4%

Efficiency = 148,000/175,000 = 84.6%


Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shiftsEffi i 84 6%


Efficiency = 84.6%Efficiency of new line = 75%

Expected Output = (Effective Capacity)(Efficiency)

= (175,000)(.75) = 131,250 rolls

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Actual production last week = 148,000 rollsEffective capacity = 175,000 rollsDesign capacity = 1,200 rolls per hourBakery operates 7 days/week, 3 - 8 hour shiftsEffi i 84 6%


Efficiency = 84.6%Efficiency of new line = 75%

Expected Output = (Effective Capacity)(Efficiency)

= (175,000)(.75) = 131,250 rolls

Capacity and StrategyCapacity and Strategy

Capacity decisions impact all 10 decisions of operations management as well as other f ti l f th i ti


functional areas of the organizationCapacity decisions must be integrated into the organization’s mission and strategy

Capacity ConsiderationsCapacity Considerations

1. Forecast demand accurately2. Understand the technology and

capacity increments


p y3. Find the optimum

operating level (volume)

4. Build for change

Economies and Economies and Diseconomies of ScaleDiseconomies of Scale

25 - room roadside motel

75 - room roadside motelit

cost

m p

er n

ight

)


Economies of scale

Diseconomies of scale

roadside motel 50 - room roadside motel

roadside motel

Number of Rooms25 50 75

Aver

age

uni

(dol

lars

per

room

Figure S7.2

Managing DemandManaging DemandDemand exceeds capacity

Curtail demand by raising prices, scheduling longer lead timeLong term solution is to increase capacity


Capacity exceeds demandStimulate marketProduct changes

Adjusting to seasonal demandsProduce products with complementary demand patterns

Complementary Demand Complementary Demand PatternsPatterns

4,000 –

ts


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

Sale

s in

uni

Time (months)

Jet ski engine sales

Figure S7.3

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4,000 –

ts S bil


3,000 –

2,000 –

1,000 –


Sale

s in

uni

Time (months)

Snowmobile motor sales


Figure S7.3


4,000 –

ts

Combining both demand patterns reduces the variation

S bil


3,000 –

2,000 –

1,000 –


Sale

s in

uni

Time (months)

Snowmobile motor sales


Figure S7.3

Tactics for Matching Tactics for Matching Capacity to DemandCapacity to Demand

1. Making staffing changes2. Adjusting equipment

Purchasing additional machinerySelling or leasing out existing equipment


Selling or leasing out existing equipment3. Improving processes to increase throughput4. Redesigning products to facilitate more

throughput5. Adding process flexibility to meet changing

product preferences6. Closing facilities

Demand and Capacity Demand and Capacity Management in the Management in the

Service SectorService SectorDemand management

Appointment, reservations, FCFS rule


Capacity management

Full time, temporary, part-time staff

Bottleneck Analysis and Bottleneck Analysis and Theory of ConstraintsTheory of Constraints

Each work area can have its own unique capacityCapacity analysis determines the


throughput capacity of workstations in a systemA bottleneck is a limiting factor or constraintA bottleneck has the lowest effective capacity in a system

Process Times for Stations, Process Times for Stations, Systems, and CyclesSystems, and CyclesThe process time of a stationprocess time of a station is the time to produce a unit at that single workstation


The process time of a systemprocess time of a system is the time of the longest process in the system … the bottleneckThe process cycle timeprocess cycle time is the time it takes for a product to go through the production process with no waiting

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A ThreeA Three--Station Station Assembly LineAssembly Line

QuickTime™ and a decompressor

are needed to see this picture.


Figure S7.4

2 min/unit 4 min/unit 3 min/unit

A B C

Process Times for Stations, Process Times for Stations, Systems, and CyclesSystems, and CyclesThe system process timesystem process time is the process time of the bottleneck after dividing by the number of parallel operations


operationsThe system capacitysystem capacity is the inverse of the system process timeThe process cycle timeprocess cycle time is the total time through the longest path in the system

Capacity AnalysisCapacity AnalysisTwo identical sandwich linesLines have two workers and three operations All completed sandwiches are wrapped


Wrap

37.5 sec/sandwich

Order

30 sec/sandwich

Bread Fill Toast

15 sec/sandwich 20 sec/sandwich 40 sec/sandwich

Bread Fill Toast

15 sec/sandwich 20 sec/sandwich 40 sec/sandwich

Capacity Capacity AnalysisAnalysis Wrap

37.5 sec

Order

30 sec

Bread Fill Toast

15 sec 20 sec 40 sec

Bread Fill Toast

15 sec 20 sec 40 sec

Toast work station has the longest processing time – 40 secondsThe two lines each deliver a sandwich every 40 seconds so the process time of the combined


plines is 40/2 = 20 secondsAt 37.5 seconds, wrapping and delivery has the longest processing time and is the bottleneckCapacity per hour is 3,600 seconds/37.5 seconds/sandwich = 96 sandwiches per hourProcess cycle time is 30 + 15 + 20 + 40 + 37.5 = 142.5 seconds

Capacity AnalysisCapacity AnalysisStandard process for cleaning teethCleaning and examining X-rays can happen simultaneously


Checkout

6 min/unit

Check in

2 min/unit

DevelopsX-ray

4 min/unit 8 min/unit

DentistTakesX-ray

2 min/unit

5 min/unit

X-rayexam

Cleaning

24 min/unit

Capacity Capacity AnalysisAnalysis

All possible paths must be comparedCleaning path is 2 + 2 + 4 + 24 + 8 + 6 = 46 minutesX-ray exam path is 2 + 2 + 4 + 5 + 8 + 6 = 27

Checkout

6 min/unit

Checkin

2 min/unit

DevelopsX-ray

4 min/unit 8 min/unit

DentistTakesX-ray

2 min/unit

5 min/unit

X-rayexam

Cleaning

24 min/unit


X-ray exam path is 2 + 2 + 4 + 5 + 8 + 6 = 27 minutesLongest path involves the hygienist cleaning the teethBottleneck is the hygienist at 24 minutesHourly capacity is 60/24 = 2.5 patientsPatient should be complete in 46 minutes

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Theory of ConstraintsTheory of ConstraintsFive-step process for recognizing and managing limitationsStep 1:Step 1: Identify the constraintStep 2:Step 2: Develop a plan for overcoming the


pp p p gconstraints

Step 3:Step 3: Focus resources on accomplishing Step 2Step 4:Step 4: Reduce the effects of constraints by

offloading work or expanding capabilityStep 5:Step 5: Once overcome, go back to Step 1 and find

new constraints

Bottleneck ManagementBottleneck 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


y3. Increasing the capacity of a non-

bottleneck station is a mirage4. Increasing the capacity of a bottleneck

increases the capacity of the whole system

BreakBreak--Even AnalysisEven Analysis

Technique for evaluating process and equipment alternativesObjective is to find the point in


dollars and units at which cost equals revenueRequires estimation of fixed costs, variable costs, and revenue

BreakBreak--Even AnalysisEven AnalysisFixed 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 utilitiesContribution is the difference between selling price and variable cost

BreakBreak--Even AnalysisEven Analysis

Costs and revenue are linear functions

Generally not the case in the

AssumptionsAssumptions


yreal world

We actually know these costsVery difficult to verify

Time value of money is often ignored

BreakBreak--Even AnalysisEven AnalysisTotal revenue line

Total cost lineBreak-even pointTotal cost = Total revenue

–

900 –

800 –

700 –

600 –

500dolla

rs


Variable cost

Fixed cost

500 –

400 –

300 –

200 –

100 –

–| | | | | | | | | | | |

0 100 200 300 400 500 600 700 800 900 10001100

Cos

t in

d

Volume (units per period)Figure S7.5

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BreakBreak--Even AnalysisEven AnalysisBEPx = break-even point in

unitsBEP$ = break-even point in

dollarsP = price per unit (after

all discounts)

x = number of units produced

TR = total revenue = PxF = fixed costsV = variable cost per unit

TC = total costs = F + Vx


TR = TCor

Px = F + Vx

BreakBreak--even point occurs wheneven point occurs when

BEPx = FP - V

BreakBreak--Even AnalysisEven AnalysisBEPx = break-even point in

unitsBEP$ = break-even point in

dollarsP = price per unit (after

all discounts)

x = number of units produced

TR = total revenue = PxF = fixed costsV = variable cost per unit

TC = 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

BreakBreak--Even ExampleEven Example

Fixed costs = $10,000 Material = $.75/unitDirect labor = $1.50/unit Selling price = $4.00 per unit

BEP = =F $10,000


BEP$ = =1 - (V/P) 1 - [(1.50 + .75)/(4.00)]


Fixed costs = $10,000 Material = $.75/unitDirect labor = $1.50/unit Selling price = $4.00 per unit

BEP = =F $10,000


BEP$ = =1 - (V/P) 1 - [(1.50 + .75)/(4.00)]

= = $22,857.14$10,000.4375

BEPx = = = 5,714FP - V

$10,0004.00 - (1.50 + .75)

BreakBreak--Even ExampleEven Example50,000 –

40,000 –

30,000 –s Total t

Revenue

Break-even point


20,000 –

10,000 –

–| | | | | |0 2,000 4,000 6,000 8,000 10,000

Dol

lars

Units

Fixed costs

costs


BEP$ = F

∑ 1 (W )Vi

Multiproduct CaseMultiproduct Case


∑ 1 - x (Wi)i

Pi

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 ExampleMultiproduct Example

Annual ForecastedItem Price Cost Sales UnitsSandwich $5.00 $3.00 9,000Drink 1.50 .50 9,000Baked potato 2 00 1 00 7 000

Fixed costs = $3,000 per month


Baked potato 2.00 1.00 7,000





Baked potato 2.00 1.00 7,000

Sandwich $5.00 $3.00 .60 .40 $45,000 .621 .248Drinks 1.50 .50 .33 .67 13,500 .186 .125Baked 2.00 1.00 .50 .50 14,000 .193 .096

potato$72,500 1.000 .469

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)ViPi

= = $76,759$3,000 x 12.469

Daily = = $246 02$76,759


Baked potato 2.00 1.00 7,000

Sandwich $5.00 $3.00 .60 .40 $45,000 .621 .248Drinks 1.50 .50 .33 .67 13,500 .186 .125Baked 2.00 1.00 .50 .50 14,000 .193 .096

potato$72,500 1.000 .469

Annual WeightedSelling Variable Forecasted % of Contribution

Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7)

sales = = $246.02312 days

.621 x $246.02$5.00 = 30.6 ≈ 31

sandwichesper day

Reducing Risk with Reducing Risk with Incremental ChangesIncremental Changes

(a) Leading demand with incremental expansion

Dem

and

Expected demand

New capacity

(b) Capacity lags demand with incremental expansion

Dem

and

New capacity

Expected demand


(c) Attempts to have an average capacity with incremental expansion

Dem

and New

capacity Expected demand

Figure S7.6


(a) Leading demand with incremental expansion

New capacity


Expected demand

Figure S7.6

Dem

and

Time (years)1 2 3


(b) Capacity lags demand with incremental expansion

New capacity


Expected demand

Figure S7.6

Dem

and

Time (years)1 2 3

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Reducing Risk with Reducing Risk with Incremental ChangesIncremental Changes(c) Attempts to have an average capacity

with incremental expansion

New capacity


Expected demand

Figure S7.6

Dem

and

Time (years)1 2 3

Expected Monetary Value Expected Monetary Value (EMV) and Capacity Decisions(EMV) and Capacity Decisions

Determine states of natureFuture demand


Market favorabilityAnalyzed using decision trees

Hospital supply companyFour alternatives


-$90,000Market unfavorable (.6)

Market favorable (.4) $100,000

Market favorable ( 4)


Market favorable (.4)

Market unfavorable (.6)

$60,000

-$10,000

Medium plant



$40,000

-$5,000

$0








$60,000

-$10,000

Medium plant



$40,000

-$5,000

$0

EMV = (.4)($100,000) + (.6)(-$90,000)

Large Plant

EMV = -$14,000





-$14,000

$18,000




$60,000

-$10,000

Medium plant



$40,000

-$5,000

$0

$13,000

StrategyStrategy--Driven InvestmentDriven 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

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Net Present Value (NPV)Net Present Value (NPV)

where F = future valueP t l

F = P(1 + i)N

In general:


P = present valuei = interest rate

N = number of years

P = F(1 + i)N

Solving for P:

Net Present Value (NPV)Net Present Value (NPV)

where F = future valueP t l

F = P(1 + i)N

In general:

While this works


P = present valuei = interest rate

N = number of years

P = F(1 + i)N

Solving for P:

While this works fine, it is

cumbersome for larger values of N

NPV Using FactorsNPV 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

Portion of Table S7.1

Year 6% 8% 10% 12% 14%1 .943 .926 .909 .893 .8772 .890 .857 .826 .797 .7693 .840 .794 .751 .712 .6754 .792 .735 .683 .636 .5925 .747 .681 .621 .567 .519

Present Value of an AnnuityPresent Value of an AnnuityAn 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

Present Value of an AnnuityPresent Value of an AnnuityPortion of Table S7.2

Year 6% 8% 10% 12% 14%1 .943 .926 .909 .893 .8772 1 833 1 783 1 736 1 690 1 647


2 1.833 1.783 1.736 1.690 1.6473 2.676 2.577 2.487 2.402 2.3224 3.465 3.312 3.170 3.037 2.9145 4.212 3.993 3.791 3.605 3.433

Present Value of an AnnuityPresent Value of an Annuity

$7,000 in receipts per for 5 yearsInterest rate = 6%

From Table S7.2


X = 4.212

S = RXS = $7,000(4.212) = $29,484

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LimitationsLimitations1. Investments with the same NPV may

have different projected lives and salvage values

2. Investments with the same NPV may


2. Investments with the same NPV may have different cash flows

3. Assumes we know future interest rates4. Payments are not always made at the

end of a period


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