1. Chapter 6 Managing Capacity

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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.
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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.
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Capacity
Examples of Capacity in Different Organizations
Table 6.1
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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
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7. 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.
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8. Three Common Capacity Strategies
When to Add Capacity: Lead, Lag, and Match Strategies
Figure 6.1
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9. Methods of Evaluating Capacity Alternatives
Cost
Demand Considerations
Expected Value
Decision Trees
Break-Even Analysis
Learning Curves
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10. Methods of Evaluating Capacity Alternatives
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 Cost
FC = Fixed Cost
VC = Variable cost per unit of business activity
X = amount of business activity
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11. Methods of Evaluating Capacity Alternatives
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.
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12. Methods of Evaluating Capacity Alternatives
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.
Draw the tree from left to right starting with a decision point or an outcome point and develop branches from there.
Represent decision points with squares.
Represent outcome points with circles.
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.
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13. Methods of Evaluating Capacity Alternatives
Break-even analysis
Break-even point – The volume level for a business at which total revenues cover total costs.
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14. Methods of Evaluating Capacity Alternatives
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.
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15. Methods of Evaluating Capacity Alternatives
Other Considerations:
The strategic importance of an activity to a firm.
The desired degree of managerial control.
The need for flexibility.
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16. 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.
Throughput of a “Pipeline” is
Determined by the Smallest “Pipe”
Figure 6.7
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17. Understanding and Analyzing Process Capacity
Throughput is Controlled by the Constraint, Process 3
Figure 6.7
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18. Understanding and Analyzing Process Capacity
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
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19. Understanding and Analyzing Process Capacity
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
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20. Understanding and Analyzing Process Capacity
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?
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21. Understanding and Analyzing Process Capacity
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 (m)
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22. Understanding and Analyzing Process Capacity
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:
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23. Understanding and Analyzing Process Capacity
The average time spent waiting is
The average time spent in the systems is:
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24. Understanding and Analyzing Process Capacity
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.
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