Capacity Planning
For Products and
Services
Learning Objectives





Explain the importance of capacity planning.
Discuss ways of defining and measuring
capacity.
Describe the determinants of effective
capacity.
Discuss the major considerations related to
developing capacity alternatives.
Briefly describe approaches that are useful for
evaluating capacity alternatives
Capacity Planning
 Capacity is the upper limit or ceiling on the
load that an operating unit can handle.
 Capacity also includes



Equipment
Space
Employee skills
 The basic questions in capacity handling
are:



What kind of capacity is needed?
How much is needed?
When is it needed?
Importance of Capacity Decisions
1. Impacts ability to meet future demands
2. Affects operating costs
3. Major determinant of initial costs
4. Involves long-term commitment
5. Affects competitiveness
6. Affects ease of management
7. Globalization adds complexity
8. Impacts long range planning
Capacity
 Design capacity

maximum output rate or service capacity an
operation, process, or facility is designed for
 Effective capacity

Design capacity minus allowances such as
personal time, maintenance, and scrap
 Actual output

Rate of output actually achieved--cannot
exceed effective capacity.
Efficiency and Utilization
Actual output
Efficiency =
Effective capacity
Actual output
Utilization =
Design capacity
Both measures expressed as percentages (%)
Efficiency/Utilization Example
Design capacity = 50 trucks/day
Effective capacity = 40 trucks/day
Actual output = 36 units/day
Actual output
=
36 units/day
Efficiency =
= 90%
Effective capacity
Utilization =
Actual output
Design capacity
40 units/ day
=
36 units/day
50 units/day
= 72%
Determinants of Effective
Capacity




Facilities (design, location, layout, environment)
Product and service factors (design, product mix)
Process factors (quantity capacity, quality capacity)
Human factors (job content, job design, training & experience,
motivation, compensation, learning rate, absenteeism and turnover)
 Policy factors
 Operational factors (scheduling, materials management, QA,
maintenance, breakdown)
 Supply chain factors
 External factors (standard, safety regulation, unions, pollution
control standard)
Strategy Formulation
Capacity strategy for long-term demand
patterns involve;
 Growth rate and variability of demand
 Cost of building and operating facilities of
various size
 Rate and direction of technology changes
 Behavior of competitors
 Availability of capital and other inputs
Key Decisions of Capacity
Planning
1. Amount of capacity needed
•
Capacity cushion (100% - Utilization)
2. Timing of changes
3. Need to maintain balance of the system
4. Extent of flexibility of facilities and
workforce
Capacity cushion – extra demand intended to offset
uncertainty
Steps for Capacity Planning
1. Forecast future capacity requirements
2. Evaluate existing capacity
3. Identify alternatives
4. Conduct financial analysis
5. Assess key qualitative issues
6. Select one alternative
7. Implement alternative chosen
8. Monitor results
Forecasting Capacity
Requirements
 Long-term vs. short-term capacity needs
 Long-term relates to overall level of capacity
such as facility size, trends, and cycles
 Short-term relates to variations from
seasonal, random, and irregular fluctuations
in demand
Calculating Processing
Requirements
Standard
processing time
per unit (hr.)
Product
Annual
Demand
Processing time
needed (hr.)
#1
400
5.0
2,000
#2
300
8.0
2,400
#3
700
2.0
1,400
5,800
Working 8-hour shift, 250 day/year
Annual capacity = 2000 hours
Machine required to handle these job = 5,800 /2,000 = 2.90
Machine required to handle these job = 3 machines
Planning Service Capacity
 Need to be near customers
 Capacity and location are closely tied
 Inability to store services
 Capacity must be matched with timing of
demand
 Degree of volatility of demand
 Peak demand periods
In-House or Outsourcing
(Make or Buy)
1.
2.
3.
4.
5.
6.
Available capacity
Expertise
Quality considerations
Nature of demand
Cost
Risk
Developing Capacity Alternatives
1.Design flexibility into systems
2.Take stage of life cycle into account
3.Take a “big picture” approach to capacity
changes (to focus bottleneck)
4.Prepare to deal with capacity “chunks”
5.Attempt to smooth out capacity
requirements
6.Identify the optimal operating level
(economy of scale)
Product Life Cycle
Company Strategy/Issues
Introduction
Growth
Maturity
Best period to
increase market
share
Practical to change
price or quality
image
Poor time to
change image,
price, or quality
R&D engineering is
critical
Strengthen niche
Competitive costs
become critical
Defend market
position
CD-ROM
Internet
Sales
Decline
Cost control
critical
Fax machines
Drive-through
restaurants
Color printers
Flat-screen
monitors
DVD
3 1/2”
Floppy
disks
Product Life Cycle
OM Strategy/Issues
Introduction
Product design
and
development
critical
Frequent
product and
process design
changes
Growth
Forecasting
critical
Product and
process
reliability
Maturity
Standardization
Less rapid
product changes
– more minor
changes
Competitive
product
improvements
and options
Optimum
capacity
High production
costs
Shift toward
product focus
Long production
runs
Limited models
Enhance
distribution
Product
improvement
and cost cutting
Short production
runs
Attention to
quality
Increasing
stability of
Increase capacity process
Decline
Little product
differentiation
Cost
minimization
Overcapacity
in the
industry
Prune line to
eliminate
items not
returning
good margin
Reduce
capacity
Bottleneck Operation
Machine #1
Machine #2
Bottleneck operation: An operation
in a sequence of operations whose
capacity is lower than that of the
other operations
10/hr
30/hr
10/hr
Machine #3
Bottleneck
Operation
10/hr
Machine #4
10/hr
30/hr
Bottleneck Operation
Bottleneck
Operation 1
20/hr.
Operation 2
10/hr.
Operation 3
15/hr.
Maximum output rate
limited by bottleneck
10/hr.
Optimal Rate of Output
Average cost per unit
Production units have an optimal rate of output for minimal cost.
Minimum average cost per unit
Minimum
cost
0
Rate of output
Economies of Scale
 Economies of scale
 If the output rate is less than the optimal
level, increasing output rate results in
decreasing average unit costs
 Diseconomies of scale
 If the output rate is more than the optimal
level, increasing the output rate results in
increasing average unit costs
Economies of Scale
Average cost per unit
Minimum cost & optimal operating rate are
functions of size of production unit.
0
Small
plant
Medium
plant
Large
plant
Output rate
Evaluating Alternatives
 Cost-volume analysis
 Break-even point
 Financial analysis
 Cash flow
 Present value
 Decision theory
 Waiting-line analysis
Amount ($)
Cost-Volume Relationships
Fixed cost (FC)
0
Q (volume in units)
Amount ($)
Cost-Volume Relationships
0
Q (volume in units)
Amount ($)
Cost-Volume Relationships
0
BEP units
Q (volume in units)
BEP = Break Even Point
Break-Even Problem with Step
Fixed Costs
3 machines
2 machines
1 machine
Quantity
Step fixed costs and variable costs.
Break-Even Problem with Step
Fixed Costs
$
BEP3
BEP2
TC
TC
3
TC
2
1
Quantity
Multiple break-even points
Assumptions of Cost-Volume
Analysis
1.One product is involved
2.Everything produced can be sold
3.Variable cost per unit is the same
regardless of volume
4.Fixed costs do not change with volume
5.Revenue per unit constant with volume
6.Revenue per unit exceeds variable cost
per unit
Financial Analysis
 Cash Flow - the difference between
cash received from sales and other
sources, and cash outflow for labor,
material, overhead, and taxes.
 Present Value - the sum, in current
value, of all future cash flows of an
investment proposal.
Decision Theory
 Helpful tool for financial comparison of
alternatives under conditions of risk or
uncertainty
 Suited to capacity decisions
Waiting-Line Analysis
 Useful for designing or modifying service
systems
 Waiting-lines occur across a wide variety of
service systems
 Waiting-lines are caused by bottlenecks in
the process
 Helps managers plan capacity level that will
be cost-effective by balancing the cost of
having customers wait in line with the cost of
additional capacity
Decision Theory
Decision Theory represents a general
approach to decision making which is suitable for a
wide range of operations management decisions,
including:
Capacity
planning
Product and
service design
Location
planning
Equipment
selection
Decision Theory Elements
 A set of possible future conditions exists
that will have a bearing on the results of
the decision
 A list of alternatives for the manager to
choose from
 A known payoff for each alternative
under each possible future condition
Decision Theory Process
 Identify possible future conditions called states of
nature
 Develop a list of possible alternatives, one of which
may be to do nothing
 Determine the payoff associated with each
alternative for every future condition
 If possible, determine the likelihood of each
possible future condition
 Evaluate alternatives according to some decision
criterion and select the best alternative
Causes of Poor Decisions
Bounded Rationality
The limitations on decision
making caused by costs,
human abilities, time,
technology, and availability of
information
Causes of Poor Decisions (Cont’d)
Suboptimization
The result of different
departments each
attempting to reach a
solution that is
optimum for that
department
Decision Process
1.
2.
3.
4.
5.
6.
7.
Identify the problem
Specify objectives and criteria for a solution
Develop suitable alternatives
Analyze and compare alternatives
Select the best alternative
Implement the solution
Monitor to see that the desired result is
achieved
Decision Environments
 Certainty - Environment in which
relevant parameters have
known values
 Risk - Environment in which
certain future events have
probable outcomes
 Uncertainty - Environment in
which it is impossible to assess
the likelihood of various future
events
Decision Making under Uncertainty
Maximin - Choose the alternative with
the best of the worst possible payoffs
Maximax - Choose the alternative with
the best possible payoff
Laplace - Choose the alternative with
the best average payoff of any of the
alternatives
Minimax Regret - Choose the alternative
that has the least of the worst regrets
Decision Making Under Risk
 Risk: The probability of occurrence for each
state of nature is known
 Risk lies between the extremes of
uncertainty and certainty
 Expected monetary value (EMV) criterion:
 The best expected value among alternatives
 Determine the expected payoff of each
alternative, and choose the alternative with the
best expected payoff
Decision Trees
 Decision tree: a Schematic representation
of the available alternatives and their
possible consequences.
 Useful for analyzing situations that involve
sequential decisions
Format of a Decision Tree
Payoff 1
Decision Point
Chance Event
Payoff 2
2
Payoff 3
1
B
Payoff 4
2
Payoff 5
Payoff 6
Example of a Decision Tree
40M
Decision Point
Chance Event
40M
2
Overtime
50M
55M
1
B
10M
2
50M
70M
Expected Value of Perfect Information
Expected value of perfect information: the
difference between the expected payoff under
certainty and the expected payoff under risk
Expected value of
Expected payoff
perfect information = under certainty
-
Expected payoff
under risk
Sensitivity Analysis
 Sensitivity Analysis: Determining the range
of probability for which an alternative has the
best expected payoff
 Useful for decision makers to have some
indication of how sensitive the choice of an
alternative is to changes in one or more of
these values
Example
ตารางแสดง Payoff ของแต่ละทางเลือก
State of nature
#1
#2
Alternative
A
B
C
จงเขียนภาพแสดง Sensitivity
4
16
12
12
2
8
Sensitivity Analysis
#1 Payoff
16
14
12
10
8
6
4
2
0
#2 Payoff
B
A
C
B best
C best
A best
Sensitivity analysis: determine the range of
probability for which an alternative has the best
expected payoff
16
14
12
10
8
6
4
2
0