Transcript Capacity Factors that Affect 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:
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 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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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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Three Common
Capacity Strategies
When to Add Capacity: Lead, Lag, and Match Strategies
Figure 6.1
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Methods of Evaluating
Capacity Alternatives
 Cost
 Demand Considerations
 Expected Value
 Decision Trees
 Break-Even Analysis
 Learning Curves
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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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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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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.
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.
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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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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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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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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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Understanding and Analyzing
Process Capacity
Throughput is Controlled by the
Constraint, Process 3
Figure 6.7
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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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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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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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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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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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Understanding and Analyzing
Process Capacity
 The average time spent waiting is
 The average time spent in the systems is:
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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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