Long-Range
Capacity Planning
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The Hierarchy of Production Decisions
The logical sequence of operations in factory planning
corresponds to the sequence of chapters in a text-book with
title «Production and Operations Management».
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All planning starts with the demand forecast.
Demand forecasts are the basis for the top level long_range capacity,
and medium term aggregate planning.
The Master Production Schedule (MPS) is the result of disaggregating
aggregate plans down to the individual item level.
Based on the MPS, MRP is used to determine the size and timing of
component and subassembly production.
Detailed shop floor schedules are required to meet production plans
resulting from the MRP.
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Hierarchy of
Production Decisions
Long-range Capacity Planning
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Capacity Definitions
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Capacity is a statement of the rate of producing
output and is generally measured as the output of the
process per unit period of time. Capacity essentially
limits the rate of output possible.
The Load represents the work released and planned
for the process for a given period of time.
Think the load being the amount of water in a tank
and the capacity being the rate at which the water can
be drained from the tank.
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Capacity Planning
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Capacity planning is the process of reconciling the
difference between the capacity available for the
process and the capacity required to satisfy the
customer order which represents the load.
In capacity planning, it is important to adjust the
capacity to meet the load in order to maintain a high
level of customer service.
Critical elements of capacity to be planned include
labor, machine hours, facilities and warehouse
space.
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Capacity Planning
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1.
2.
3.
A major function of capacity planning is to match
the capacity of the machine or facility with the
demand for the products of the firm.
Capacity planning can be classified into three
planning horizons:
Long range
Medium range
Short range
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Long-Term Capacity Planning
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The long range planning generally considers
planning horizons of one year or longer. A time
period of one year or longer is needed to provide
sufficient time to build a new facility, to expand the
existing facility or to move to a new facility due to
forecasted changes in demand.
We determine long-term capacity needs by forecasting demand
over a time horizon and then converting those forecasts into
capacity requirements
Long-term considerations relate to overall level of capacity,
such as facility size (affected by trends and cycles)
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Medium-term capacity Planning
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Medium range capacity planning horizon ranges
approximately from one month to six months.
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At this level of planning, decisions or activities
include acquisition of a major piece of machinery
and subcontracting.
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Short-term Capacity Planning
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Short range planning horizon covers
capacity planning activities on a daily or
a weekly basis and are generated as a
result of disaggregation of the long or
medium range capacity plans. These
activities include machine loading and
detailed production scheduling.
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Short-term Capacity Planning
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Short-term considerations relate to probable
variations in capacity requirements created by
such things as seasonal, random, and
irregular fluctuations in demand
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When time intervals are too short to have a
seasonal variations in demand, a probability
distribution such as Normal, Uniform,
Poisson can be used to forecast the demand.
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Questions to be answered in Long-Range Capacity
Planning
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How much long-range production capacity is needed?
- adding too much capacity means the capacity will
be underutilized.
- adding too little capacity means that the comapany
will soon be faced with the problem of increasing
capacity again.
When additional capacity is needed?
- It is important to pay attention to changing
patterns of demand.
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Questions to be answered in Long-Range Capacity
Planning
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Where the production facilities should be located?
- Consideration of the logistics of material flows
suggests that new facilities be located near suppliers
of raw materials and market outlets.
How the production facilities are arranged?
Facility layout decisions affect the production rates.
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Importance of Capacity Decisions
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Capacity limits the rate of output possible.
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Poor capacity decisions which result in over and
under capacity increase the operating costs.
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Capacity decisons often require long-term
commitment of resources so that once they are
implemented, it may be difficult to modify those
decisions without incurring major costs.
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Importance of Capacity Decisions
Capacity decisons are major determinant of initial
costs.
Capacity decisons affect competitiveness. Companies
having appropriate capacity can deliver the products
faster than competitors (delivery speed).
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Importance of Capacity Decisions
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Capacity decisions are important to all
departments of the organization;
An accountant would be interested in
collecting cost accounting information in
order to ensure that correct capacity
expansion decision is reached.
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Importance of Capacity Decisions
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Similarly a financial manager
would be interested in performing the
financial analysis of whether the
investment decision is justified for a
plant or capacity increase.
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Importance of Capacity Decisions
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An Information Technology Manager
would end up preparing data bases that
would aid the organization to decide
about the capacity and last but not the
least an operations manager would
select strategies that would help the
organization achieve the optimum
capacity levels to meet the customer
demand.
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Steps in the Capacity Planning Process
1. Estimate the capacity of the present facilities.
2. Forecast the long-range future capacity needs by taking into
consideration demand patterns(i.e., trends, cycles).
3. Identify and analyze ways of changing long-range capacity
For Capacity Expansion: Subcontract, Acquire other
companies, Develop new sites, buy new equipment,
Expand current sites, Reactivate standby facilities
For Capacity Reduction: Sell off existing facilities, Sell
inventories and Lay off employees
4. Select from among the alternative sources of capacity changing
plans.
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Measurements of Capacity
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Output rate capacity - for a single product or a
few homogeneous products (TV sets per
month, number of cars per shift)
Aggregate capacity - using a common unit of
output if many different products are produced
( sales dollars per month, tons of steel per day)
Input rate capacity - for service operations
(hospitals use available beds per month,
airlines use available seats per day)
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Measurements of Capacity
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Design Capacity: Maximum output that can possibly be
attained under ideal conditions
Effective Capacity: It is usually less than design capacity (it
can not exceed design capacity) due to the realities of
changing product mix, scheduling difficulties, periodic
machine maintenance, lunch and coffee breaks
Actual output: The rate of output actually achieved. It can not
exceed effective capacity and is often less than effective
capacity due to breakdowns, absenteesim, defective output,
shortages of materials and so on. (These problems are outside
the control of the operations managers)
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Measurements of Capacity
These different measures of capacity are
useful in defining two measures of
system effectiveness:
---- efficiency
---- utilization
Efficiency=Actual Output / Effective Cap.
Utilization=Actual Output / Design Cap.
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Measurements of Capacity
It is common for managers to focus
exclusively on efficiency, but often this
might be misleading. This happens when
effective capacity is low compared with
design capacity. In those cases, high
efficiency would seem to indicate
effective use of resources when it does
not. The following example illustrates
this point.
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EXAMPLE
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Given the information below, compute the efficiency and
utilization of the vehicle repair department:
Design capacity = 50 trucks/day
Effective capacity= 40 trucks/day
Actual output = 36 trucks/day
Efficiency= 36/40=90% Utilization= 36/50=72%
When effective capacity is low compared with design capacity,
to focus exclusively on efficiency can be misleading. And you
should note that increasing utilization depends on being able to
increase effective capacity. This requires a knowledge of what
is constraing effective capacity.
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Determinants of Effective Capacity
A)
Facilities
- Location (transportation cost, distance, labor
supply)
- Design (room for expansion)
- Layout (material transfer, line balance)
B)
Product/service
- Design (similar products standardization)
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Determinants of Effective Capacity
C)
Process
- Quantitiy capabilities (productivity, using
automated machines)
- Quality capabilities (the more time spent for
inspection and rework the less capacity)
D)
Human Factors
- job content
- training and experience
- motivation
- absenteeism and labor turnover
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Determinants of Effective Capacity
E)
F)
Operational Factors
- scheduling
- materials management
- quality assurance
- maintenance policies
- equipment breakdowns
External Factors
- Pollution control standards
- Unions (limit the number of working hours)
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Factors which influence the frequency of capacity
decisions
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Stability of demand
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The rate of technological change in equipment
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The rate of technological change in product design
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The rate of technological change in competitive
factors
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A Strategy For Demand Management:
Capacity Cushion
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Capacity cushion is an additional amount of capacity
added onto the expected demand. Capacity cushion
Helps to meet excess demand during peak demand
seasons
Lowers production costs
Provides product and volume flexibility
Improves quality of products and services
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Developing Capacity Alternatives
1.
2.
3.
Design flexibility into systems by taking into
consideration of water lines, power hookups, waste
disposal lines for future expansion
Take a “big picture” approach to capacity changes
(increasing number of rooms will lead to increasing
demand for parking)
Prepare to deal with capacity “chunks.” Capacity
increases are often acquired in fairly large chunks
rather than smooth increments, making it difficult to
achieve a match between desired capacity and
feasible capacity.
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4. Attempt to smooth out capacity requirements
Unevenness in capacity requirements also can create certain problems.
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5. Take stage of life cycle into account
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6. Identify the optimal operating level
Average Unit
Cost of Output ($)
Economies
of Scale
Diseconomies
of Scale
Best Operating Level
Annual Volume (units)
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Economies of Scale
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Best operating level - least average unit cost
Economies of scale - If the output rate is less than the
optimal level, increasing output rate results in
decreasing average unit costs. Declining costs up to
the best operating level result from fixed costs, labor
cost being spread over more units
Average cost per unit decreases as the volume
increases.
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Diseconomies of scale
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Diseconomies of scale –
If the output rate is more than the optimal level,
increasing the output rate results in increasing
average unit costs.
Average cost per unit increases as the volume
increases due to scheduling problems, quality
problems, reduced morale, increased use of overtime
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Expanding capacity all at once or incrementally
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Another important issue in capacity
planning is:
Choosing between expanding capacity all
at once (better for mature products having
stable and predictable demand) or
incrementally (better for new products)
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Larger Plants Tend to Have
Higher Optimal Output Rates
Average cost per unit
Minimum cost & optimal operating rate are
functions of size of production unit.
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Small
plant
Medium
plant
Large
plant
Output rate
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Planning Service Capacity
Three important factors in planning servive capacity
are:
 Inability to store services
 Need to be near customers
Capacity and location are closely tied
Capacity must be matched with timing of demand
 Degree of volatility of demand
Peak demand periods
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Analyzing Capacity-Planning Decisions
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Decision Tree Analysis
Cost-Volume Analysis
Present-Value Analysis
Computer Simulation
Waiting Line Analysis
Linear Programming
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Decision Tree Analysis
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Structures complex, multiphase decisions
Allows objective evaluation of alternatives
Incorporates uncertainty
Develops expected values
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Example: Decision Tree Analysis
Good Eats Café is about to build a new
restaurant. An architect has developed three
building designs, each with a different seating
capacity. Good Eats estimates that the average
number of customers per hour will be 80, 100, or
120 with respective probabilities of 0.4, 0.2, and
0.4. The payoff table showing the profits for the
three designs is on the next slide.
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Example: Decision Tree Analysis
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Payoff Table
Average Number of Customers Per Hour
c1 = 80 c2 = 100 c3 = 120
Design A
Design B
Design C
$10,000
$ 8,000
$ 6,000
$15,000
$18,000
$16,000
$14,000
$12,000
$21,000
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Example: Decision Tree Analysis
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Expected Value Approach
Calculate the expected value for each decision.
The decision tree on the next slide can assist in this
calculation. Here d1, d2, d3 represent the decision
alternatives of designs A, B, C, and c1, c2, c3 represent
the different average customer volumes (80, 100, and
120) that might occur.
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Example: Decision Tree Analysis
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Decision Tree
Payoffs
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d1
1
c1
.4
c2
c3
.2
.4
10,000
15,000
14,000
d2
3
d3
c1
.4
c2
c3
.2
8,000
18,000
.4
12,000
4
c1
.4
c2
.2
c3
6,000
16,000
.4
21,000
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Example: Decision Tree Analysis
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Expected Value For Each Decision
d1
EV = .4(10,000) + .2(15,000) + .4(14,000)
= $12,600
2
Design A
1
Design B d2
EV = .4(8,000) + .2(18,000) + .4(12,000)
= $11,600
3
Design C
d3
EV = .4(6,000) + .2(16,000) + .4(21,000)
= $14,000
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Choose the design with largest EV -- Design C.
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Assumptions of Cost-Volume Analysis
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3.
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6.
One product is involved
Everything produced can be sold
Variable cost per unit is the same regardless of
volume
Fixed costs do not change with volume
Revenue per unit is constant
Revenue per unit exceeds variable cost per unit
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Example 1: Cost-Volume Analysis
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The owner of Old-Fashioned Berry Pies, S. Simon, is
contemplating adding a new line of pies, which will
require leasing new equipment for a monthly payment
of $6000. Variable cost would be $2 per pie and pies
would retail $7 each.
a) How many pies must be sold in order to break
even?
b) What would the profit(loss) be if 1000 pies are
made and sold in a month?
c) How many pies must be sold to realize a profit of
$4000?
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Example 1
a)
b)
c)
Q = FC/(p-v)=6000/(7-2)=1200 pies/month
Profit(or Loss)=7*1000-(6000+2*1000)
= -$1000 (Loss)
4000 = 7Q – (6000+2Q)
Q=2000 pies
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Example 2: Cost-Volume Analysis
A manager has the option of purchasing one, two, or
three machines.
# of mach.
Tot. Annual FC
Correspond. Output
1
$9600
0 – 300
2
15000
301 - 600
3
20000
601 – 900
Variable cost is $10, revenue is $40 per unit.
a)
Determine the break-even poinf for each range.
b)
If projected demand is between 580 and 660 units,
how many machines should the manager purchase?
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Example 2
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a) For one machine Q = 9600/(40-10)= 320 units
For two machines Q= 15000/(40-10)= 500 units
For three machines Q=20000/(40-10)=666.67 units
b) Manager should choose two machines. Because
even if demand is at low end of the range (i.e., 580),
it would be above the break-even point and thus yield
a profit. If three machines are purchased, even at the
top end of projected demand (i.e., 660), the volume
would still be less than the break-even point for that
range, so there would be no profit.
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A Capacity Planning Strategy:
Make or Buy
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Once capacity requirements have been determined, the
company must decide whether to produce the product
or buy (outsource) it from another company.
The company can purchase the product from an
outside source for c1 dollar per unit, but can produce
internally for a lower unit price , c2<c1. However in
order to produce the product internally, the company
invest $K to expand production capacity.
Which strategy should the company adopt?
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Make or Buy: Capacity Expansion Problem
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The factors which affect make or buy decisions are:
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Available capacity
Expertise
Quality considerations
Nature of demand
Cost
Risk
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Make or Buy?
Available capacity. If an organization has available the equipment, necessary skills, and time,
it often makes sense to produce an item or perform a service in-house.
Expertise. If a firm lacks the expertise to do a job satisfactorily, buying might be a reasonable
alternative.
Quality considerations. Firms that specialize can usually offer higher quality than an
organization can attain itself. Conversely, unique quality requirements or the desire to closely
monitor quality may cause an organization to perform a job itself.
The nature of demand. When demand for an item is high and steady, the organization is often
better off doing the work itself. However, wide fluctuations in demand or small orders are
usually better handled by specialists who are able to combine orders from multiple sources,
which results in higher volume and tends to offset individual buyer fluctuations.
Cost. Cost savings might come from the item itself or from transportation cost savings. If there
are fixed costs associated with making an item that cannot be reallocated if the service or
product is outsourced, that has to be recognized in the analysis. Conversely, outsourcing may
help a firm avoid incurring fixed costs.
Risk. Outsourcing may involve certain risks. One is loss of control over operations. Another is
the need to disclose proprietary information.
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Example
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A large international computer manufacturer is designing a
new model of personal computer and must decide whether to
produce the keyboards internally or to purchase them from an
outside supplier. The supplier is willing to sell the keyboards
for $50 each, but the manufacturer estimates that his firm can
produce the keyboards for $35 each. Management estimates
that expanding the current plant and purchasing the necessary
equipment to make the keyboards would cost $8 million.
Should they undertake the expansion?
The break-even quantity is:
X=8000 000/(50-35)= 533333
So the company would have to sell at least 533333 keyboards
in order to justify the $8 million investment required for
expansion.
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Waiting-Line Analysis
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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 costeffective by balancing the cost of having customers
wait in line with the cost of additional capacity
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