capacity management in industrial engineering
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CAPACITY PLANNING
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Strategic Capacity Planning
Capacity is the ability to hold, receive, store, or
accommodate raw materials, finished products,customers, etc.
Strategic capacity planning is an approach fordetermining the overall capacity level of capital intensive
resources, including facilities, equipment, and overalllabour force size.
Capacity used is the rate of output actually achieved.
The best operating level is nominally the capacity for
which the process was designed.Capacity Used
Capacity Utilization RateBest Operating Level
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Capacityplanning
Capacityis the maximum output rate of a production or servicefacility
Capacity planning is the process of establishing the output ratethat may be needed at a facility:
Capacity is usually purchased in chunks
Strategic issues: how much and when to spend capital for
additional facility & equipment
Tactical issues: workforce & inventory levels, & day-to-day use of
equipment
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MeasuringCapacity Examples
There is no one best way to measure capacity
Output measures like cars per day are easier to understand
With multiple products, inputs measures work better
Type of BusinessInput Measures of
Capacity
Output Measures
of Capacity
Car manufacturer Labor hours Cars per shift
Hospital Available beds Patients per month
Pizza parlor Labor hours Pizzas per day
Retail storeFloor space in
square feetRevenue per foot
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BestOperating Level
Example:
Engineers design engines and assembly lines to operate at anideal or best operating level to maximize output and minimize
wear.
Under-utilization
Best Operating Level
Average
unit cost
of output
Volume
Over-utilization
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Best Operating Level for a Hotel
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How Much Capacity Is Best?
The Best Operating Level is the output that results in the
lowest average unit cost
Economies of Scale:
Where the cost per unit of output drops as volume ofoutput increases
Spread the fixed costs of buildings & equipment overmultiple units, allow bulk purchasing & handling ofmaterial
Diseconomies of Scale:
Where the cost per unit rises as volume increases Often caused by congestion (overwhelmingthe
process with too much work-in-process) andscheduling complexity
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Economies of Scale
100-unit
plant
200-unit
plant 300-unit
plant
400-unit
plant
Volume
Average
unit costof output
Economies of scale and operating level curves
Diseconomiesof scale start to take effect
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Experience (Learning) Curves
As plants produce more products, they gain experience in
the best production methods and reduce their costs per unit.
Total accumulated production of units
Cost/price
per unit
Yesterday
Today
Tomorrow
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Economiesof Scale
it costs less per unit to produce high levels of output
fixed costs can be spread over a larger number of units production or operating costs do not increase linearly
with output levels
quantity discounts are available for material purchases
operating efficiency increases as workers gainexperience
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Diseconomies of Scale
Occur above a certain level of output Diseconomies of Distribution
Diseconomies of Bureaucracy
Diseconomies of Confusion
Diseconomies of Vulnerability
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CapacityDecisions (cont.)
Capacity increase depends on
volume and certainty of anticipated demand
strategic objectives costs of expansion and operation
Best operating level
% of capacity utilization that minimizes unit
costs Capacity cushion
% of capacity held in reserve for unexpectedoccurrences
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Diseconomies of Confusion
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Capacity Utilization
Example:
During one week of production, a plant produced 83units of a product. Its historic best utilization was 120
units per week. What is this plants capacity utilization
rate?
Capacity UsedCapacity Utilization RateBest Operating Level
83 /0.69 69%
120 /
units week
units week
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Capacity Planning
Three important considerations in capacity planning:
Maintaining system balance In the ideal case, the output of one stage is the exact input
requirements for the next stage.
Frequency of capacity additions
There are costs in adding capacity too frequently as well as too
infrequently. External sources of capacity
It might be cheaper to outsource some production.
Determining capacity requirements
Forecast sales (within each individual product line)
Calculate equipment and labour requirements to meet forecasts
Project equipment and labour availability
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MakingCapacity Planning Decisions
The three-step procedure for making capacity planning
decisions is as follows:
Step 1: Identify Capacity Requirements
Step 2: Develop Capacity Alternatives
Step 3: Evaluate Capacity Alternatives
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Capacity Requirements Example
A manufacturer produces mustard in small and family-
sized plastic bottles, with the following demand forecasts.
Three 100,000 units-per-year machines are available for small
bottle production. 2 operators are required per machine.
Two 120,000 units-per-year machines are available for family-
sized bottle production. 3 operators are required per machine.
How much capacity is used and what are the machine
and labour requirements?
Year 1 Year 2 Year 3 Year 4
Small (000's) 150 170 200 240
Family (000's) 115 140 170 200
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Capacity Requirements Example (2)
Machine capacity: 300 000 small, 240 000 family size
Labour availability: 6 for small, 6 for family size
Year 1 Year 2 Year 3 Year 4
Small (000's) 150 170 200 240
Family (000's) 115 140 170 200
Year 1 Year 2 Year 3 Year 4
Small (000's) 150 170 200 240
Family (000's)115 140 170 200
Small
% capacity used 50.00%
machines req'd 1.50
labour req'd 3.00
Family Size% capacity used
machines req'd
labour req'd
150 0000.50
300 000
150 0001.5
100 000 per machine
21.5 3.0
operatorsmachines
machine
Year 1 Year 2 Year 3 Year 4
Small (000's) 150 170 200 240
Family (000's)115 140 170 200
Small
% capacity used 50.00%
machines req'd 1.50
labour req'd 3.00
Family Size% capacity used 47.92%
machines req'd 0.96
labour req'd 2.88
115 0000.4792
240 000
115 0000.96
120 000 per machine
30.96 2.88operatorsmachinesmachine
Year 1 Year 2 Year 3 Year 4
Small (000's) 150 170 200 240
Family (000's)115 140 170 200
Small
% capacity used 50.00% 56.67% 66.67% 80.00%
machines req'd 1.50 1.70 2.00 2.40
labour req'd 3.00 3.40 4.00 4.80
Family Size% capacity used 47.92% 58.33% 70.83% 83.33%
machines req'd 0.96 1.17 1.42 4.25
labour req'd 2.88 3.50 4.25 5.00
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Decision Trees as an aid
A decision tree is a schematic model of the steps in the
capacity planning problem.
Steps:
1. Draw the various decisions
2. Add the possible states of nature, probabilities, andpayoffs
3. Determine the expected value of each decision
4. Make decision (the one with maximum expected
value)
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Decision Trees Example
A glass factory specializing in crystal experiences substantial
backlog, and management is considering three courses of action:
A. Arrange for subcontracting
B. Construct new facilities
C. Do nothing (no change)
The correct choice depends largely upon demand, which may be low,
medium, or high. By consensus, management estimates therespective demand probabilities as 0.1, 0.5, and 0.4.
The management also estimates the profits when choosing from the
three alternatives under the differing probable levels of demand.
These profits, are as follows:
Low (p=0.1) Medium (p-0.5) High (p=0.4)A 10 000 50 000 90 000
B -120 000 25 000 200 000
C 20 000 40 000 60 000
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Decision Trees Example (2)
Medium demand (0.5) 50k
Medium demand (0.5) 25k
Medium demand (0.5) 40k
A
B
C
Decisions: States, probabilities, and payoffs:
High demand (0.4) 90k
Low demand (0.1) 10k
High demand (0.4) 200k
Low demand (0.1) - 120k
High demand (0.4) 60k
Low demand (0.1) 20k
Start
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Decision Trees Example (3)
Medium demand (0.5) 50k
Medium demand (0.5) 25k
Medium demand (0.5) 40k
A
B
C
Expected values of each decision:
High demand (0.4) 90k
Low demand (0.1) 10k
High demand (0.4) 200k
Low demand (0.1) - 120k
High demand (0.4) 60k
Low demand (0.1) 20k
0.4 90 0.5 50 0.1 10 $62kAEV
, ,A A i A i iEV P V
0.4 200 0.5 25 0.1 120 $80.5kBEV
0.4 60 0.5 40 0.1 20 $46kCEV
Choose decision B
(highest expected value)
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Capacity Information Needed
Design capacity: Maximum output rate under ideal conditions
A bakery can make 30 custom cakes per day when pushed atholiday time
Effective capacity: Maximum output rate under normal (realistic) conditions
On the average this bakery can make 20 custom cakes perday
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Implementing Capacity Decisions
Capacity flexibility Plant, process, workers, outsourcing
Amount of capacity cushion important in -to-order and services
Timing the capacity change Leading [proactive] Concurrent [neutral]
Lagging [reactive]
Size of the capacity increment
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Capacity Expansion Strategies
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Timing the Capacity Change
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Other Capacity Planning Concepts
The concept of the focused factory (also called capacity
focus) holds that production facilities work best whenthey focus on a fairly limited set of production objectives.
The plants within plants (PWP) concept extendscapacity focus ideas to an operational level.
Capacity flexibility allows rapid increase or decrease ofproduction levels, and can be achieved in three ways:
Flexible plants
Flexible processes
Flexible workers
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Other Issues
Focused factories:
Small, specialized facilities with limited objectives
Plant within a plant (PWP):
Segmenting larger operations into smaller operating
units with focused objectives
Subcontractor networks:
Outsource non-core items to free up capacity for
what you do well
Capacity cushions:
Plan to underutilize capacity to provide flexibility
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Service Capacity vs. Manufacturing Capacity
Capacity planning in services is different than in
manufacturing in three key ways: Time
Goods can not be stored for later use
Capacity must be available to provide a service
when it is needed Location
Service goods must be at the customer demand
point
Capacity must be located near the customer
Volatility of demand
Much greater in services than in manufacturing
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Capacity Decisions
Capacity
maximumcapability toproduce
ratedcapacity istheoretical
effectivecapacityincludesefficiencyand
utilization
Capacity utilization
percent of available time spend working
Capacity efficiency how well a machine or worker performs
compared to a standard output level
Capacity load
standard hours of work assigned to afacility
Capacity load percent ratio of load to capacity