chapter 6 managing capacity

Chapter 6

Managing Capacity

Chapter Objectives

Be able to:Explain what capacity is, how firms measure capacity, and the difference between theoretical and rated capacity. Describe the pros and cons associated with three different capacity strategies: lead, lag, and match. Apply a wide variety of analytical tools for choosing between capacity alternatives, including expected value and break-even analysis, decision trees, and learning curves.Apply the Theory of Constraints, waiting line theory, and Little’s Law to analyze and understand capacity issues in a business process environment.

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Capacity

Capacity – The capability of a worker, a machine, a workcenter, a plant, or an organization to produce output in a time period.

Capacity decisions that managers face: How capacity is measured? Which factors affect capacity? The impact of the supply chain on the organization’s effective capacity.

© 2013 APICS Dictionary


Capacity

Measures of Capacity Theoretical capacity – The maximum output capability, allowing for no

adjustments for preventive maintenance, unplanned downtime, or the like.

Rated capacity – The long-term, expected output capability of a resource or system. © 2013 APICS Dictionary


Capacity

Table 6.1

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Examples of Capacity in Different Organizations

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Capacity Factors that Affect Capacity

Many factors affect capacity and many assumptions must be made:

• Number of lines used

• Number of shifts operating

• Number of temporary workers used

• Number of public storage facilities used

• Product variations on line

• Conformance quality

• Quality improvement


Three Common Capacity Strategies

Lead capacity strategy – A capacity strategy in which capacity is added in anticipation of demand.

Lag capacity strategy – A capacity strategy in which capacity is added only after demand has materialized.

Match capacity strategy – A capacity strategy that strikes a balance between the lead and lag capacity strategies by avoiding periods of high under or overutilization.


Three Common Capacity Strategies

Figure 6.1


When to Add Capacity: Lead, Lag, and Match Strategies

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Methods of Evaluating Capacity Alternatives

Cost Demand Considerations Expected Value Decision Trees Break-Even Analysis Learning Curves



Cost Fixed costs – The expenses an organization incurs regardless of the level of

business activity. Variable costs – Expenses directly tied to the level of business activity.


TC = FC + VC * X

TC = Total CostFC = Fixed Cost

VC = Variable cost per unit of business activityX = amount of business activity

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Expected value – A calculation that summarizes the expected costs, revenues, or profits of a capacity alternative, based on several demand levels, each of which has a different probability.



Decision tree – A visual tool that decision makers use to evaluate capacity decisions and to enable users to see the interrelationships between decisions and possible outcomes.

1. Draw the tree from left to right starting with a decision point or an outcome point and develop branches from there.

2. Represent decision points with squares. 3. Represent outcome points with circles.4. For expected value problems, calculate the financial results for each of the

smaller branches and move backward by calculating weighted averages for the branches based on their probabilities.



Break-even analysis Break-even point – The volume level for a business at which total revenues

cover total costs.



Learning curve theory – A body of theory based on applied statistics which suggests that productivity levels can improve at a predictable rate as people and even systems “learn” to do tasks more efficiently.

For every doubling of cumulative output, there is a set percentage reduction in the amount of inputs required.



Other Considerations:

The strategic importance of an activity to a firm.

The desired degree of managerial control.

The need for flexibility.


Understanding and Analyzing Process Capacity

Theory of Constraints – An approach to visualizing and managing capacity which recognizes that nearly all products and services are created through a series of linked processes, and in every case, there is at least one process step that limits throughput for the entire chain.

Figure 6.7


Throughput of a “Pipeline” is Determined by the Smallest “Pipe”

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Figure 6.7

Throughput is Controlled by the Constraint, Process 3

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Theory of Constraints Identify the Constraint

Exploit the Constraint

Subordinate everything to the Constraint

Elevate the Constraint

Find the new Constraints and repeat the steps



Waiting Line Theory – A body of theory based on applied statistics that helps managers evaluate the relationship between capacity decisions and important performance issues such as waiting times and line lengths.

Figure 6.12



Waiting Line Concerns at a Drive-up Window: What percentage of the time will the server be busy? On average, how long will a customer have to wait in line? How long will the

customer be in the system (i.e. waiting and being served) ? On average, how many customers will be in line? How will these averages be affected by the arrival rate of customers and the

service rate of the drive-up window personnel?



Arrivals: The probability of n arrivals in T time periods is calculated as follows:

Service Times: Assume that they will be constant or vary. When varying they use the exponential distribution ()



The average utilization of the system is:

The average number of customers waiting (CW) is:

The average number of customers in the systems (CS) is:



The average time spent waiting is

The average time spent in the systems is:



Little’s Law – A law that holds for any system that has reached a steady state and enables the understanding of the relationship between inventory, arrival time, and throughput time.


chapter 6 managing capacity

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