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Chapter 7S Capacity and Constraint ManagementOutline

- Capacity
- Design and Effective Capacity
- Capacity and Strategy
- Capacity Considerations
- Managing Demand
- Demand and Capacity Management in the Service Sector

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Outline – Continued

- Bottleneck Analysis and Theory of Constraints
- Process Times for Stations, Systems, and Cycles
- Theory of Constraints
- Bottleneck Management
- Break-Even Analysis
- Single-Product Case
- Multiproduct Case

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Outline – Continued

- Reducing Risk with Incremental Changes
- Applying Expected Monetary Value to Capacity Decisions
- Applying Investment Analysis to Strategy-Driven Investments
- Investment, Variable Cost, and Cash Flow
- Net Present Value

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Learning Objectives

Define capacity

Determine design capacity, effective capacity, and utilization

Perform bottleneck analysis

Compute break-even analysis

Determine the expected monetary value of a capacity decision

Compute net present value

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Process Strategies

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

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Options for Adjusting Capacity

*

Long-range planning

Add facilities

Add long lead time equipment

Intermediate-range planning

Subcontract Add personnel

Add equipment Build or use inventory

Add shifts

Schedule jobs

Schedule personnel

Allocate machinery

*

Short-range planning

Modify capacity

Use capacity

* Difficult to adjust capacity as limited options exist

Planning Over a Time HorizonFigure S7.1

© 2011 Pearson Education, Inc. publishing as Prentice Hall

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

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Utilization and Efficiency

Utilization is the percent of design capacity achieved

Utilization = Actual output/Design capacity

Efficiency is the percent of effective capacity achieved

Efficiency = Actual output/Effective capacity

© 2011 Pearson Education, Inc. publishing as Prentice Hall

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%

© 2011 Pearson Education, Inc. publishing as Prentice Hall

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

© 2011 Pearson Education, Inc. publishing as Prentice Hall

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

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Capacity Considerations

- Forecast demand accurately
- Understand the technology and capacity increments
- Find the optimum operating level (volume)
- Build for change

© 2011 Pearson Education, Inc. publishing as Prentice Hall

25 - room roadside motel

50 - room roadside motel

Average unit cost

(dollars per room per night)

Economies of scale

Diseconomies of scale

25

50

75

Number of Rooms

Economies and Diseconomies of ScaleFigure S7.2

© 2011 Pearson Education, Inc. publishing as Prentice Hall

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 complementary demand patterns

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Combining both demand patterns reduces the variation

4,000 –

3,000 –

2,000 –

1,000 –

Snowmobile motor sales

Sales in units

Jet ski engine sales

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

Time (months)

Complementary Demand PatternsFigure S7.3

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Demand and Capacity Management in the Service Sector

- Demand management
- Appointment, reservations, FCFS rule
- Capacity management
- Full time, temporary, part-time staff

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Bottleneck Analysis and Theory of Constraints

- Each work area can have its own unique capacity
- Capacity analysis determines the throughput capacity of workstations in a system
- A bottleneck is a limiting factor or constraint
- A bottleneck has the lowest effective capacity in a system

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Process Times for Stations, Systems, and Cycles

- The process time of a station is the time to produce a unit at that single workstation
- The process time of a system is the time of the longest process in the system … the bottleneck
- The process cycle time is the time it takes for a product to go through the production process with no waiting

© 2011 Pearson Education, Inc. publishing as Prentice Hall

B

C

2 min/unit

4 min/unit

3 min/unit

A Three-Station Assembly LineFigure S7.4

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Process Times for Stations, Systems, and Cycles

- The system process time is the process time of the bottleneck after dividing by the number of parallel operations
- The system capacity is the inverse of the system process time
- The process cycle time is the total time through the longest path in the system

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Bread

Fill

Toast

Wrap

30 sec/sandwich

15 sec/sandwich

20 sec/sandwich

40 sec/sandwich

37.5 sec/sandwich

Bread

Fill

Toast

15 sec/sandwich

40 sec/sandwich

20 sec/sandwich

Capacity Analysis- Two identical sandwich lines
- Lines have two workers and three operations
- All completed sandwiches are wrapped

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Fill

Toast

15 sec

20 sec

40 sec

Order

Wrap

30 sec

37.5 sec

Bread

Fill

Toast

15 sec

40 sec

20 sec

Capacity Analysis- Toast work station has the longest processing time – 40 seconds
- The two lines each deliver a sandwich every 40 seconds so the process time of the combined lines is 40/2 = 20 seconds
- At 37.5 seconds, wrapping and delivery has the longest processing time and is the bottleneck
- Capacity per hour is 3,600 seconds/37.5 seconds/sandwich = 96 sandwiches per hour
- Process cycle time is 30 + 15 + 20 + 40 + 37.5 = 142.5 seconds

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Theory of Constraints

- Five-step process for recognizing and managing limitations

Step 1: Identify the constraint

Step 2: Develop a plan for overcoming the constraints

Step 3: Focus resources on accomplishing Step 2

Step 4: Reduce the effects of constraints by offloading work or expanding capability

Step 5: Once overcome, go back to Step 1 and find new constraints

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Bottleneck Management

- Release work orders to the system at the pace of set by the bottleneck
- Lost time at the bottleneck represents lost time for the whole system
- Increasing the capacity of a non-bottleneck station is a mirage
- Increasing the capacity of a bottleneck increases the capacity of the whole system

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Break-Even Analysis

- Objective is to find the point in dollars and units at which cost equals revenue

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Break-Even Analysis

- Fixed costs are costs that continue even if no units are produced
- Variable costs are costs that vary with the volume of units produced

© 2011 Pearson Education, Inc. publishing as Prentice Hall

900 –

800 –

700 –

600 –

500 –

400 –

300 –

200 –

100 –

–

Total revenue line

Total cost line

Break-even point

Total cost = Total revenue

Profit corridor

Cost in dollars

Variable cost

Loss corridor

Fixed cost

| | | | | | | | | | | |

0 100 200 300 400 500 600 700 800 900 1000 1100

Volume (units per period)

Break-Even AnalysisFigure S7.5

© 2011 Pearson Education, Inc. publishing as Prentice Hall

BEPx = 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 cost per unit

TC = total costs = F + Vx

F

P - V

BEPx =

Break-Even AnalysisBreak-even point occurs when

TR = TC

or

Px = F + Vx

© 2011 Pearson Education, Inc. publishing as Prentice Hall

BEPx = 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 cost per unit

TC = total costs = F + Vx

BEP$ = BEPxP

= P

=

=

F

P - V

F

1 - V/P

F

(P - V)/P

Break-Even AnalysisProfit = TR - TC

= Px - (F + Vx)

= Px - F - Vx

= (P - V)x - F

© 2011 Pearson Education, Inc. publishing as Prentice Hall

F

1 - (V/P)

BEPx = =

F

P - V

Break-Even ExampleFixed costs = $10,000 Material = $.75/unit

Direct labor = $1.50/unit Selling price = $4.00 per unit

© 2011 Pearson Education, Inc. publishing as Prentice Hall

BEP$=

∑1 - x (Wi)

Vi

Pi

Break-Even ExampleMultiproduct 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

© 2011 Pearson Education, Inc. publishing as Prentice Hall

(a) Leading demand with incremental expansion

New capacity

Expected demand

Demand

(b) Capacity lags demand with incremental expansion

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

New capacity

New capacity

Expected demand

Expected demand

Demand

Demand

Reducing Risk with Incremental ChangesFigure S7.6

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Expected Monetary Value (EMV) and Capacity Decisions

- Determine states of nature
- Future demand
- Market favorability
- Analyzed using decision trees
- Hospital supply company
- Four alternatives

© 2011 Pearson Education, Inc. publishing as Prentice Hall

$100,000

Market unfavorable (.6)

-$90,000

Large plant

Market favorable (.4)

$60,000

Medium plant

Market unfavorable (.6)

-$10,000

Small plant

Market favorable (.4)

$40,000

Do nothing

Market unfavorable (.6)

-$5,000

$0

Expected Monetary Value (EMV) and Capacity Decisions© 2011 Pearson Education, Inc. publishing as Prentice Hall

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

© 2011 Pearson Education, Inc. publishing as Prentice Hall

(1 + i)N

P =

Net Present Value (NPV)In general:

F = P(1 + i)N

where F = future value

P = present value

i = interest rate

N = number of years

Solving for P:

© 2011 Pearson Education, Inc. publishing as Prentice Hall

Limitations

- Investments with the same NPV may have different projected lives and salvage values
- Investments with the same NPV may have different cash flows
- Assumes we know future interest rates
- Payments are not always made at the end of a period

© 2011 Pearson Education, Inc. publishing as Prentice Hall

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