Operation management presentation on how companies help determine the factory output and inventory.

1. CAPACITY
MANAGEMENT

2. Hello!
Luke D’Silva (5)
Yash Vardhan Lohia (9)
Madhurima Paul (10)

3. “
“The world has enough for every
one’s needs, but not enough for
everyone’s greed.”
-Mahatma Gandhi.

4. CAPACITY MANAGEMENT
 Capacity is a very relative term. In
operations, it is defined as the amount of
resource inputs available relative to output
requirement over a particular period of time.
 Strategic Capacity Planning is an approach
taken to determine the overall capacity level
of capital-intensive resources- facilities,
equipments and the labour force size- that
best supports the companies strategy.

5. CAPACITY PLANNING
Long Range
Greater than one
year. In this case,
the resources take
a long time to
acquire and
dipose.
e.g., building,
equipment, etc.
Intermediate
Range
Monthly or
quarterly planning.
Capacity may vary
due to hiring,
layoff, new tools
and changes, or
subcontracting.
Short Range
Less than a month.
This is tied into
weekly or daily
process and
involves making
adjustments to
decrease variance
between planned
and actual output.

6. CAPACITY UTILIZATION
 By capacity, we mean an attainable output,
e.g., 4 lakh tablets per day, but it does not
provide information that how long the rate
can be sustained. Therefore, we do not know
wether this rate is sustainable or not.
 To avoid such problems, the concept of Best
Operating Level is used.
 It is a level of capacity at which the output
level minimizes the average cost per unit.

7. CAPACITY UTILIZATION
 The important measure is the capacity utilization
rate. It reveals the best operating level.
𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑈𝑡𝑖𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 =
𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑈𝑠𝑒𝑑
𝐵𝑒𝑠𝑡 𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝐿𝑒𝑣𝑒𝑙
 For example, if a company’s best operating level is
4.5 lakh tablets per day, and it makes 4 lakh
tablets per day, the capacity utilization rate is
89%.
𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑈𝑡𝑖𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 =
400000
450000
= 89%

8. Market demand is
just the tip of the
iceberg.
The real problem lies
with managing the
resources and providing
a correct supply to the
demands in the market.

9. ECONOMIES OF SCALE
 Economics of scale is the basic idea that as
the plant gets larger and volume increases,
the average cost of unit drops.
 This happens due to lower costs of operation
and capital because the equipment with
twice the capacity does not cost twice as
much to purchase or operate.
 Plants also gain efficiency when they learn
how to utilize their dedicated resources-
people and equipment- for IT, material
handling and administrative support.

10. DISECONOMIES OF SCALE
 Sometimes, a size of a plant may become too
large and cause diseconomies of scale.
 Diseconomies may surface due to many
reasons. Maintaining the demand required
to keep the large facility busy requires
significant discounting of the product.
 E.g., M&M Mars has highly automated high
volume equipment to make M&Ms. A sinngle
equppment moves 2.6 million M&Ms a day.
Even if the labour required to operate is low,
the labour for maintainance is high.

11. LEARNING CURVE
 A line which displays the relationship between
unit production time and cumulative number
units produced.
 It is used to estimate the time for product
design and production, as well as costs.
 Integral part of planning corporate strategy
such as decisions concerning pricing, capital
investment and operating cost based on
experience curves.
 Applied to both individuals and organization.

12. TYPES OF LEARNING
 Individual Learning is the improvement that
the results when people repeat the process
and gain efficiency from their own experience.
“Practice makes Perfect”
 Organizational Learning results from practice
as well, but also comes from changes in
administration, equipment and product
design.

13. THEORY
Learning curve theory is based on three
assumptions:
 The amount of time given to complete a given
task or, the unit of a product will be less each
time a task is undertaken.
 The unit time will decrease at a decreasing rate.
 The reduction in time will follow a predictable
pattern

14. PROGRESS CURVE

15. INDUSTRIAL LEARNING

16. CAPACITY FOCUS
 Focus Factory is a facility designed around a
limited set of production objectives.
Typically, the focus relates to a specific
product or a product group.
 A focused factory can be operationalized
through the mechanism of Plant within a
Plant.
 A focus factory may have several PWPs, each
of which may perform separate tasks and
produce diferrentiated products.

17. PRODUCT LINE A
ASSEMBLY
B
MACHINE SHOP
PRODUCT LINE
B
ASSEMBLY
PLANT WITHIN A PLANT
Low Volume
High Variety
High Skill
High Volume
Low Variety
Low Skill

18. CAPACITY FLEXIBILITY
 The means of having the ability to rapidly
increase or decrease production levels, or to
shift production capacity quickly from one
product service to another.
 This is achieved through:
1. Flexible Plants
2. Flexible Processes
3. Flexible Workers

19. CAPACITY ANALYSIS
 Considerations in capacity change requires:
1. Maintaining System Balance- Balance between
output and input of different stages.
2. Frequency Of Capacity Additions- Frequent and
Infrequent.
3. Use of External Capacity- Sharing capacity or
no addition at all.

20. DETERMINING CAPACITY REQUIREMENTS
 Capacity requirement is essential for every
business.
 The determination of the units is done by:
1. Using forecasting techniques for predicting
Sales for individual product in a product
line.
2. Calculate equipment and labour
requirements to meet product line forecasts.
3. Project labour and equipment availabilities
according to planning.
Also, capacity in excess of demand is kept for
precaution- Capacity Cushion.

21. DETERMINING CAPACITY
REQUIREMENTS: Example.
Stewart company produces two type of salad
dressings. They are available in a plastic bottle
with a single serving bag. The brands are:
 PAUL’s
 NEWMAN’s
2010 2011 2012
PAUL’s
Bottles(000s)
Bags (000s)
60
100
100
200
150
300
NEWMAN’s
Bottles(000s)
Bags (000s)
75
200
85
400
95
600

22. DETERMINING CAPACITY
REQUIREMENTS: Example.
Total Forecast:
 If, capacity is 450000 per year, then 135,000
bottles will take 135/450= 0.9 machines.
 Similarly, for bags, 1,250,000 per capacity is
available, then for 300 bags it becomes 1.2
machines.
2010 2011 2012
Bottles (000s)
Bags (000s)
135
300
185
600
245
900

23. DETERMINING CAPACITY
REQUIREMENTS: Example.
 Now, if 2 operators are required for bottle
making and 3 operators for bags, the
equations comes as:
0.9 bottle machine x 2 operators = 1.8 op.
1.2 bag machines x 3 operators = 3.6 op.
 This is further balanced and operated in
excess, which is used as the cushion
capacity.

24. DECISION TREE
 A decision tree is a schematic representation
of the alternatives available to a decision
maker and their possible consequences.
 The term gets its name from the treelike
appearance of the diagram.
 They are particularly useful for analyzing
situations that involve sequential decisions.

25.  Square nodes denote decision points, and
circular nodes denote chance events.
 Branches leaving square nodes represent
alternatives; branches leaving circular
nodes represent chance events.

26.  After the tree has been drawn, it is analyzed
from right to left; that is, starting with the
last decision that might be made.
 For each decision, choose the alternative
that will yield the greatest return (or the
lowest cost).

27. DECISION TREE
 EXAMPLE:
A manager must decide on the size of a video
arcade to construct. The manager has narrowed
the choices to two: large or small. Information has
been collected on payoffs, and a decision tree has
been constructed.
 The decision tree is analyzed to find out which
initial alternative (build small or build large)
should be chosen in order to maximize
expected monetary value.

28. DECISION TREE

29. DECISION TREE
 The dollar amounts at the branch ends indicate the
estimated payoffs if the sequence of chance events and
decisions that is traced back to the initial decision occurs.
 For example, if the initial decision is to build a small facility
and it turns out that demand is low, the payoff will be $40
(thousand).
 Similarly, if a small facility is built, demand turns out high,
and a later decision is made to expand, the payoff will be
$55 (thousand).
 The figures in parentheses on branches leaving the chance
nodes indicate the probabilities of those states of nature.
 Hence, the probability of low demand is .4, and the
probability of high demand is .6. Payoffs in parentheses
indicate losses.

30. DECISION TREE
 Analyze the decisions from right to left:
1. Determine which alternative would be selected for
each possible second decision. For a small facility with
high demand, there are three choices: do nothing,
work overtime, and expand. Because expand has the
highest payoff, you would choose it. Indicate this by
placing a double slash through each of the other
alternatives.
Similarly, for a large facility with low demand, there are
two choices: do nothing and reduce prices. You would
choose reduce prices because it has the higher expected
value, so a double slash is placed on the other branch.

31. DECISION TREE
2. Determine the product of the chance probabilities and
their respective payoffs for the remaining branches:
Build small
Low demand = .4 ($40) = $16
High demand = .6 ($55) = $33
Build large
Low demand = .4 ($50) = $20
High demand = .6 ($70) = $42
3. Determine the expected value of each initial alternative:
Build small $16 + $33 = $49
Build large $20 + $42 = $62
Hence, the choice should be to build the large facility
because it has a larger expected value than the small facility.

32. SERVICE CAPACITY PLANNING
 Service capacity is different to manufacturing
capacity planning and facility sizing.
 The variables which are critical in service are:
1. Time
2. Location
3. Volatality of Demand.

33. TIME
 Unlike goods,services cannot be stored for
later use.
 Managers must consider time as one of their
supplies.
 The capacity must be available to produce a
service when it is needed.

34. LOCATION
 The service capacity must be located near
the customer.
 The capacity to deliver a service must first be
distributed to the customer(either physically
or through some communications medium),
then the service must be delivered.

35. VOLATALITY OF DEMAND
 Volatility of demand on a delivery system is
much higher than on a manufacturing
production system.
1. Services cannot be strored
2. Customers interact directly with the
production system
3. Directly affected by consumer behavior

36. CAPACITY UTILIZATION
AND SERVICE QUALITY
 Planning capacity levels for services must
consider day-to-day relationship between
service utilization and service quality.

37. CAPACITY UTILIZATION AND QUALITY
Relationship between Rate of Service Utilization (ρ) and
Service Quality.

38. HOSPITAL EMERGENCY ROOMS AND FIRE
DEPARTMENTS

39. COMMUTER TRAINS

40. STADIUM AND PERFORMANCE SELLOUTS

41. Thanks!
Have a nice evening ahead!