Could you please answer questions 2, 5, 6, and 7? Thank you.
2. The new manager of the electric utility notes that recent summers have been warmer than
average. Consequently, for next year she revises upward the probability that actual demand will
exceed average demand; this is estimated to occur 8 percent of the year or roughly 29 summer
days. She estimates that each power incident can cost far less than her predecessor had spent.
Using different management techniques to deal with brownouts, she hopes to reduce the cost per
incident to $10,000. Because the previous manager had not invested in additional capacity to
cover maximum peakload requirements, that option is still available. She faces the prospect that
it will cost an extra $3,000,000 to increase capacity from average to peak. This amount is spread
out over 10 years, or $300,000 per year.
Should peakload capacity be installed?
5. Company capacity is 1 million units per year for a new food product. The sales force can sell 5
million units over a 5year period, but only 100,000 in the first year. The breakeven volume is
VBEP = 50,000 units with p = 3, vc = 2, and FC = 50,000. What is the situation? What
recommendations do you support?
Using the QMpom module called Capacity Management Models (Breakeven) will facilitate
solving the three (3) problems that are numbered 5 through 7.
6. The Global Company has engaged a management consultant to analyze and improve its
operations. His major recommendation is to "conveyorize" the production floor. This would
represent a sizable investment for Global.
In order to determine whether or not the idea is feasible, a breakeven analysis will be
The situation is as follows: The cost of the conveyor will be $200,000 to be depreciated
on a straightline basis over 10 years. The conveyor will reduce operating costs by $0.25
per unit. Each unit sells for $2.00. The sales manager estimates that, on the basis of
previous years, Global can expect a sales volume of 100,000 units. This represents 100
percent utilization of capacity. Current yearly contribution to fixed costs is $100,000.
Current vc rate is $0.50 per unit.
Should Global install this conveyor?
7. Zeta Corporation is considering the advantages of automating a part of its production
line. The company's financial statement follows:
The report is based on the production and sale of 100,000 units. The operations manager
believes that an additional investment of $5 million can reduce the variable costs by 30
percent. The same output quantity and qualities would be maintained. Using 5year
straightline depreciation of $1,000,000 per year, construct a breakeven chart. Based on
the breakeven analysis, should Zeta introduce the automation?
Just in case you want it here is Chapter 10. Some of the charts
would not copy and paste correctly though.
Supply Chain Capacity Planning
10-1: Definitions of Supply Chain Capacity
Actual capacity of the supply chain is the greatest throughput rate that can be achieved with the
existing configuration of resources and the accepted product or service mix plans. Altering the
product or service mix can (and usually will) change actual realizable capacity. Modifying the
existing configuration of resources, equipment, and people in the supply chain workforce alters
real capacity. The systems point of view includes cash as part of the resources because cash can
be converted into new machines, which alter real deliverable throughput capacity. The systems
viewpoint includes good ideas, which can increase supply chain capacity with minimum
The formula for actual measured capacity of the supply chain is
C = actual measured capacity (in units converted to standard hours)
T = real time available
E = efficiency
U = utilization
Supply Chain Capacity Planning
10-1a: Standard Hours
T is determined by calculating the amount of time that is available when fully utilizing the
resources that are already in place to make and deliver product throughput. Doubling the
number of machines, trucks, etc., doubles the amount of available time, T.
E is the efficiency with which time T can be utilized to make and deliver different kinds
of product. Then, T × E is equivalent to standard hours available to make and deliver the
U is how much of the available throughput capacity can be (or is) utilized. Lack of orders
or breakdowns of productive systems diminish U. When T and E and U are multiplied,
the product is C, the actual supply chain capacity that is being (or has been) utilized.
Table 101 illustrates the calculations. Table 10-1 Capacity Utilized (C) in Standard Hours of
Assume that the supply chain is rated with a maximum capacity of 150 standard hours of
throughput. It never achieves the maximum, but comes closest to doing so on Wednesday.
There are a variety of reasons why the system does not achieve maximum throughput.
Two factors embodied in E and U are explained later. Another reason could be that the
system has bottlenecks and flow disruptions.
E, the efficiency, is a proportional factor used to convert units of throughput to standard
times. Systems of machines and people that work slower have lower efficiency than those
that have a higher productive output. Often, the best in the class is given an efficiency of
one. It is to be expected that variations in efficiency will occur. Sometimes the source of
the variation can be traced. If it is significant variation, then it should be corrected.
Unexplained fluctuations in capacity are unpleasant and unprofitable.
If a supply chain is operating at 90 percent of the standard time because a supplier
(somewhere along the supply chain line) has delivered defective product, remedial action
must be taken with supplies on hand and the problem must be corrected with future
U, the utilization, is applied as a proportional correction to standard time when there are
supply chain disruptions. Even when everything is running as planned, the value of U is
usually less than 100 percent. If the system is operating even faster, the value of U can
exceed 100 percent. There are pros and cons related to running supply chains above
maximum rated capacity. How long maximum capacity is exceeded also counts.
U is a measure to be wary of when it becomes an objective of management to keep it as
close to 100 percent as possible. There are sound economic reasons not to operate supply
chains above capacity. For example, stop production when the planned output quota has
been met and safety stock is sufficient. Shutting down the production system for 2 hours
of an 8hour day means that the U measure goes to 75 percent. Actual measured supply
chain capacity is going to be reduced by a fourth.
Management must establish the fact that supply chains are composed of complex
subsystems some of which cannot function above capacity for very long. The costs of
unsold throughput must be analyzed. How long will stored output remain as inventory?
Are there fluctuations in demand that they will buffer or is the buffer in place already?
The costs of arbitrary utilization of supply chain capacity to eliminate less than one
hundred percent utilization should be recognized for what it is—waste of time and money
due to fear of seeming to waste (unutilized) capacity. An appropriate decision model can
be constructed to set proper supply chain throughput.
As an example, assume that U is 0.963. This is likely to be viewed as a more reasonable
utilization factor than 0.750. P/OM, in general, will not tolerate a permanent situation
where utilization factors are below 0.900. Still, the target numbers will be dependent on
the situation. For example, in service organizations, a value of U might be accepted to
keep queues short. Cyclical supply chain demand systems can be expected to cycle
between utilization factors in the 0.700 range and then up to more than 100 percent
capacity. Cyclical industry companies prefer having excess capacity in reserve and expect
to operate effectively below the misleading ideal of 100 percent utilization.
Using data in Table 101, the value of 130 actual standard hours of throughput, might
have been obtained as follows:
C = T x E x U = 150 x 0.9 x 0.963 = 130 actual standard
The ratio of actual standard hours to maximum standard hours is equal to 130/150 = 0.87
or 87 percent.
Supply Chain Capacity Planning
A critical supply chain definition of capacity is related to containment. In fact, maximum
capacity may be directly related to what can be maximally stored or contained somewhere
along the supply chain route. Containment capacity takes many forms (i.e., the
auditorium has a seating capacity of 360, the gas tank will hold 16 gallons, the restaurant
freezer can store up to 40 meals in standard units).
Maximum supply chain capacity can also be defined as maximum sustained throughput
of goods or services. Both meanings are regularly used by P/OM. The capacity to contain
or store inventory is a wellreceived measure of capacity. Operations capacity describes
how many units can be supplied per unit of time. For services, a bank might compare the
maximum number of people the bank teller can process per hour with the maximum
number of people the ATM can process per hour. This is a supply chain service capacity
For a manufacturing supply chain example, compare the maximum number of hot dogs
Oscar Meyer can make and ship per hour with the maximum number of hot dogs Hebrew
10-1b: Maximum Rated Supply Chain Capacities
National can make and ship per hour. In this supply chain the ingredients required to
make the products have a flow through rate that must match the producers' rates.
This comparison is one that both companies would like to make to compare their PMCs
(productivities at maximum capacity). PMC makes an excellent benchmarking measure.
In supply chain terms, benchmarking is a systematic comparison of fundamental
measures with those of contestants performing similar supply chain functions.
Consider using maximum containments within the supply chain as a benchmarking
measure. Generally, the larger the storage facility, the more material sitting around
without having value added, and the poorer the performance measure. However, if a
company built substantial petroleum storage facilities early in 1973, it would have been in
the catbird seat when the oil embargo in the fall of 1973 created severe petroleum
shortages. The harsh effects of the oil crisis lasted through the end of March 1974.
The utilization of supply chain containment capacity is an important factor for P/OM to
consider. Having extra capacity would not have been a boon to Mobil Oil unless the tanks
were filled with crudes and fuels. On the other hand, high utilization of containment
capacity runs counter to the desire for low inventory levels, justintime deliveries, and
constant value adding.
These two kinds of capacity situations have a tradeoff relationship. Extracapacity and
undercapacity within the supply chain are shown in Figure 101. When market demand
falls below maximum supply capacity (MD < MSC), the production system can feed
storage and build up inventories. When market demand exceeds maximum supply
capacity (MD > MSC), the inventory can be used to help meet that demand.
The diagonal line in Figure 101 represents the maximum capacity to supply product. It is
a rate of throughput that at the end of period T has the capability of producing S units.
Realistically, the curved line is sometimes below the diagonal and sometimes above it.
For convenience, the market demand rate over the entire period T accumulates total
demand of S. Figure 10-1 Relationship of Variable Supply and Demand to Maximum Supply
Difficult to Store Service Capacity
The concept developed here and shown in Figure 101 does not apply to services as
readily as to goods being manufactured. This is because most services cannot be stored.
The extracapacity on the left side of Figure 101 is wasted idle time for service personnel.
For goods it can represent building stock onhand that can be drawn down when the
undercapacity, right side of Figure 101, occurs.
Backordering Augments Service Capacity
If the customer is willing, backorders can be used to satisfy demand when there is no
inventory available. This applies to services that cannot be stored. It applies as well to the
manufacturer who is out of stock. The overloaded system does not have to turn away
orders if the customer agrees to wait until other customers' jobs are finished.
Supply Chain Capacity Planning
Another question about planning supply chain capacity is: "Should the maximum output
capacity be great enough to handle peak load?" This is equivalent to providing enough
electrical generating power to supply all needs for airconditioning demand on extremely
hot business days. Alternatively, should telephone companies have enough capacity to
take care of all phone calls without any delays for Valentine's Day and Mother's Day?
These holidays are known as the heaviest traffic days for phone companies.
The rule for putting peak versus nonpeak capacity into place is
Buy peak capacity when: Cp < Cnp
Cp is the extra investment required to assure peak capacity. In other words, it is the
investment for peak capacity less that required to meet average demand, depreciated over
the life of the system. Say it takes an extra $5,000,000 to increase capacity from average
to peak. This amount is spread out over 10 years, or $500,000 per year.
Cnp is the cost of not having capacity to meet demands that are greater than the average
demand. It is determined by the costs of such events as brownouts, power failures, loss of
goodwill in the community, and there are lost revenues as well. Say that the total cost
averages $30,000 per incident.
Figure 102 provides an illustration of the difference between peak and offpeak average
demand, as well as the level of normal supply, which is above offpeak average in this
case. Figure 10-2 Peak Supply Cannot Always Meet Supply Chain Demand
10-2: Peak and Off-Peak Supply Chain Demand
To illustrate with a case, assume that the probability that actual supply chain demand
exceeds average demand is estimated to be 5 percent of the year or roughly 18 summer
days. Total cost associated with Cnp is
365 x 0.05 x $30,000 = $547,500
This is more than the investment to prevent any brownouts, so the best advice, based on
these figures, is to buy the equipment to generate sufficient power to meet peak demands.
Supply Chain Capacity Planning
10-2a: Qualitative Aspects of Supply Chain Capacity
"As is our confidence, so is our
If our confidence is high, so is our capacity. But this is a different definition of the word.
Usually, when capacity is treated in a P/OM context, the quantitative point of view
prevails. There are, however, qualitative aspects that are important to cite.
It is not unusual to hear "he or she has the capacity to be a fine ballplayer, chef, manager,
…, etc." This invokes mental ability or physical skills. Organizations have capacities to
deal with problems and opportunities. It is like an inventory of capabilities. Oftentimes,
only when tested does the capacity to outperform the normal emerge.
Motorola developed the capacity to meet quality standards that are far superior to most
other companies. Robert Galvin, former chairman of Motorola, challenged the company
to develop peak capability for quality production.
The company had been embarrassed by the Japanese company Quasar's purchase of its
TV division, which had a history of severe defectives—reporting between 150 and 180
defects per 100 sets. Within three years, traditional Japanese quality had asserted itself.
The defect rate had dropped to 3 or 4 per 100 sets. Service calls dropped from $22
million to less than $4 million. Inplant repair staff went from 120 to 15. Quality people
liked to tell the story. Galvin did not like to hear the story and threw down the gauntlet.
Motorola has since become a world leader in the production of quality products. Motorola
set for itself a difficult quality goal of 3.4 defects per million parts. This is associated
with (modified) sixsigma limits as compared to threesigma limits in quality control (see
Spotlight 72). Motorola was the first company to win the Baldrige Award for quality
Skillful management can increase the level of capacity that is achieved. Managing
installed physical capacity properly means obtaining the maximum available capacity.
This goal is particularly relevant when dealing with management of peak demand. If the
maximum capacity of the process is less than the peak demand, knowing how to assign
priorities will influence real capacity levels achieved.
Supply Chain Capacity Planning
Capacity as measured by maximum output volume per unit time, or throughput rate,
comes closest to capturing the P/OM concept. That does not make it easy to measure. It is
possible to produce at more than 100 percent of capacity for a period of time. Maximum
capacity depends on who is doing the work and what is being made or serviced. Although
100 percent and maximum capacity are illusive concepts, they are useful standards to go
by as long as the users are aware of their arbitrary nature.
When people are part of the process, some of the qualitative aspects of capacity cannot be
ignored. Some people work faster than others. Most people fluctuate in their rates of
output. There is a learning curve at work. People learn from practice how to do a better
job. Some people can learn faster than others. Individuality allows some people to do
certain jobs better than others. In this regard, all people are not alike. Ambiguity,
opportunity, and challenge abound in this arena.
10-2b: Maximum Supply Chain Capacity—100 Percent Rating
Machines work at different speeds. NASCAR drivers illustrate that point. Different
velocities are best for optimal fuel consumption, minimum tire wear, and life of the car.
Machines can be set for certain speeds that engineers would say are equivalent to 100
percent of their capacities. Ask the engineer what will happen if the machine is set to
work faster. A typical answer will be that the machine will wear out sooner.
Figure 103 shows two patterns that are typical of wearout life and failure as a function
of accumulated usage and age. Pattern A illustrates the diminishing output lumens of a
lightbulb before final failure. Pattern B shows a Weibulltype distribution, which reflects
the high initial mortality of certain products (such as lightbulbs). Then there is a period
of low product mortality until it reaches the expected time of failure. Timeoffailure
distributions must be understood if capacity is to be managed properly. Figure 10-3
Wearout and Failure Patterns as a Function of Accumulated Usage and Age—The Failure
Distribution (Pattern B) Is the Weibull Distribution
Setting standards for maximum output capacity creates an interesting comparison
between what people and machines can do. For highly repetitive jobs, most machines can
be set to work faster than people. For heavy and difficult work, especially in
environments that are very hot, noisy, and even life threatening, machines win without
question. Thus, robots are the best choice for nuclear experimentation. Also affecting the
determination of capacity is the fact that machines can break down and people can be
absent. Maximum capacity is usually determined with all the systems on go.
On the other hand, automated voice mail systems are tedious, although improving. They
can require listening to endless options. It is not unusual to have to listen to seven or eight
alternatives before getting to the one that applies. It is generally faster, and more
gratifying, for the customer to speak to an operator but it is more costly.
Capabilities and capacities of automated systems are improving. The bank teller can
perform transactions that ATMs cannot handle but for routine requests ATMs are faster
and cost less. Especially with services, capacity measures are a function of the kinds of
demands on the systems. Excess demand tends to deteriorate the performance of service
systems. Requirements for special services that are common in many systems such as
health care and education also make it difficult to establish maximum capacity figures.
Capacity planning is one of the most important business activities. It is filled with
opportunity to manage to advantage and fraught with difficulties. This is especially true if
demand is capricious and tough to forecast correctly. Capacity planning is done to reach
optimal supply decisions that, it is hoped, will match future demand patterns. This means
that capacity planning does not have to be a single frozen value but can be a dynamic
trajectory with fluctuations and oscillations. Hackers enjoy swamping server capacity and
succeed in bringing systems down. Innocently, the first weekend that the iPhone was sold
resulted in so many requests for service that Skype was out of service for many hours.
Supply Chain Capacity Planning
There are two aspects to capacity requirements planning (CRP) . The strategic issues
related to longterm planning including breakeven concepts and breakeven points and
optimal allocation of resources are being treated in this chapter. The shorterterm, tactical
issues are operating issues that properly belong to a discussion of material requirements
planning. The ability to alter supply chain capacity in steps or stages, as shown in Figure
104, is valuable for strategic plans to meet a longerterm goal. Figure 10-4 Dynamic
10-2c: Capacity Requirements Planning (CRP)
Adjustment of Maximum Supply Chain Capacity
It takes planning to keep as flexible as possible with respect to supply chain capacity.
Combinations of negotiations (as in a power grid) and technology can be brought to bear
on a temporary basis. Consider the use of leases and rentals:
Parttime employees are a familiar means for making capacity adjustments, up or down.
They do not require either severance pay or fringe benefits. Parttime employees relieve
the firm of many other obligations associated with fulltime employees. Rentals are an
equivalent method for making capacity adjustments with equipment and space without
taking on longterm commitments that lock the company into higher capacity than it is
likely to need over the long term.
Coproducers and copackers are firms used to increase supply by subcontracting with
them on a short, medium, or longterm basis. For example, a company that sells
margarine might make enough to supply 60 percent of its market. The rest of its market
demand is supplied by the output of a coproducer that has excess capacity. The product of
the coproducer is packed in the subcontracting company's familiar package.
upply Chain Capacity Planning
Capacity planning for important elements within the total supply chain is often
constrained to an optimal size by the engineering requirements of the process. Many
chemical processes must be designed and built to a specific size in order to operate
properly. Glass windshields require production steps requiring exact amounts of time.
10-3: Upscaling and Downsizing Supply Chain Capacity
Capacity decisions concern how to meet peak demand and yet not have too much in reserve for
off-peak times. The capacity of the dam and the transmission lines carried by the towers all play a
part in this energy supply chain.
© 2008 Jupiterimages Corporation
Serialized flow shop processes also are constrained by engineering factors, although to a
lesser extent than continuous chemical flow process. Job shop and batch processes are far
more flexible with regard to optimal production volume sizes.
To increase maximum capacities, processes can sometimes be operated above their rated
capacities by using overtime and faster conveyor speeds. There are quality repercussions
and the equipment is seldom designed for sustained overloads.
To meet greater demand, it may be advisable to subcontract with coproducers until suc...
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