Capacity planning

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• Capacity planning

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• Capacity is the maximum output rate of a
  production or service facility
• Capacity planning is the process of establishing
  the output rate that may be needed at a facility
• Strategic issues(long term) how much and when to
  spend capital for additional facility equipment
• Tactical issues(short term) workforce
  inventory levels, day-to-day use of equipment

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Measuring Capacity Examples

• There is no one best way to measure capacity
• Output measures are easier to understand
• With multiple products, inputs measures work
  better

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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 at holiday time
• Effective capacity
• Maximum output rate under normal (realistic)
  conditions
• On the average this bakery can make 20 custom
  cakes per day

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Calculating Capacity Utilization

• Measures how much of the available capacity is
  actually being used
• Measures effectiveness
• Use either effective or design capacity in
  denominator

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Example of Capacity Utilization
5-6

• During one week of production, a plant produced
  83 units of a product. Its historic highest or
  best utilization recorded was 120 units per week.
  What is this plants capacity utilization rate?

• Answer
• Capacity utilization rate Capacity
  used
• Best operating
  level
• 83/120
• 0.69 or 69

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Example of Computing Capacity Utilization In the
bakery example the design capacity is 30 custom
cakes per day. Currently the bakery is producing
28 cakes per day. What is the bakerys capacity
utilization relative to both design and effective
capacity?
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Example

• If operated around the clock under ideal
  conditions, the fabrication department of an
  engine manufacturer can make 100 engines per day.
  Management believes that a maximum output rate of
  only 45 engines per day can be sustained
  economical over a long period of time. Currently,
  the department is producing an average of 50
  engines per day. What is the utilization of the
  department relative to peak capacity? Effective
  capacity?

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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
  of output increases
• Spread the fixed costs of buildings equipment
  over multiple units, allow bulk purchasing
  handling of material
• Diseconomies of Scale
• Where the cost per unit rises as volume increases
• Often caused by congestion (overwhelming the
  process with too much work-in-process) and
  scheduling complexity

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Best Operating Level and Size

• Alternative 1 Purchase one large facility,
  requiring one large
• initial investment
• Alternative 2 Add capacity incrementally in
  smaller chunks as
• needed

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Economies Diseconomies of Scale
5-12
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Capacity strategies

• Sizing capacity cushions
• Timing and sizing expansion
• Operating decisions

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Capacity cushion

• The capacity cushion is the amount of reserve
  capacity that a firm maintains to handle sudden
  increases in demand or temporary losses of
  production capacity.
• It measures the amount by which the average
  utilization (in terms of effective capacity)
  falls below 100 percent.
• Capacity cushion 100 - Utilization rate ()

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When to expand and by how much?

• The timing and sizing of expansion are related.
  If demand is increasing and the time between
  increments increases, the size of the increments
  must also increase.
• Expansionist strategy
• which stays ahead of demand, minimizes the chance
  of sales lost to insufficient capacity.
• Wait-and-see strategy
• lags behind demand, relying on short-term options
  

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• Estimate capacity requirements(Single Machine)
• Processing hours required for years demand
• Hours available from one machine per year after
  deducting the desired cushion

• Estimate capacity requirements(Multiple M/c)
• Sum of Processing setup hours required for
  years demand for each product
• Hours available from one machine per year after
  deducting the desired cushion

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• Estimate capacity requirements (Single M/c)
• MD p /N1-C/100)
• Where
• M no of machines required for single process
• D number of units (customers) forecast per
  year
• p processing time (in hours per unit or
  customers)
• N total number of hours per year during which
  the process operates
• C desired capacity cushion

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Estimate capacity requirements

• MDp(D/Q)Sproduct1 Dp(D/Q)Sproduct2
  .. Dp(D/Q)Sproductn
• 
  N1-C/100)
• Where
• M no of machines required for multiple process
• D number of units (customers) forecast per
  year
• p processing time (in hours per unit or
  customers)
• N total number of hours per year during which
  the process operates
• C desired capacity cushion
• Q number of units in each lot
• s setup time (in hours) per lot

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Example

• A copy center in an office building prepares
  bound reports for two clients. The center makes
  multiple copies (the lot size) of each report.
  The processing time to run, collate, and bind
  each copy depends on, among other factors, the
  number of pages. The center operates 250 days per
  year, with an eight hours shift. Management
  believes that a capacity cushion of 15 is best.
  It currently has 3 copy machines. Based on the
  following table of information, determine how
  many machines are needed at the copy center.
• Item Client X Client Y
• Annual demand forecast (copies) 2000 6000
• Standard processing time (hour/copy) 0.5 0.7
  
• Average lot size (copies per report) 20
  30
• Standard setup time (hours) 0.25 0.40

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Identify Gaps

• A capacity gap is any difference (positive or
  negative) between projected demand and current
  capacity. Identifying gaps requires use of the
  correct capacity measure. Complications arise
  when multiple operations and several resource
  inputs are involved.
• In 1970 when airline executive states fly more
  seats to get more passengers many airlines
  responded by buying more jumbo jets, but
  competitors flying smaller planes were more
  successful. The correct measure of capacity was
  the number of departments rather than the number
  of seats.

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Step 2 Identify Gaps

• A restaurant is experiencing a boom in business.
  The owner expects to
• serve a total of 80,000 meals this year. Although
  the kitchen is operating
• at 100 percent capacity, the dining room can
  handle a total of 1,05,000
• dinners per year. Forecasted demand for the next
  five years is as
• follows
• Year 1 90,000 meals
• Year 2 1,00,000 meals
• Year 3 1,10,000 meals
• Year 4 1,20,000 meals
• Year 5 1,30,000 meals
• What are the capacity gaps in the restaurants
  kitchen and dining room
• through year 5?

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Develop alternatives

• The next step is to develop alternative plans
• to cope with projected gaps.
• One alternative is base case, which is do
  nothing and simply lose orders from any demand
  that exceeds current capacity.
• Other alternatives are various timing and sizing
  options for adding new capacity, including the
  expansionist and wait-and-see strategies.

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Tools for Capacity Planning

• Waiting Line Model
• Simulation
• Decision Tree

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Example
5-24
A glass factory specializing in crystal is
experiencing a substantial backlog, and the
firm's 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 the respective
demand probabilities as 0.1, 0.5, and 0.4.
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5-25
The management also estimates the profits when
choosing from the three alternatives (A, B, and
C) under the differing probable levels of demand.
These profits, in thousands of dollars are
presented in the table below
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Example Good Eats Café

• 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.

• Payoff Table
• Average Number of Customers Per Hour
• c1 80 c2
  100 c3 120
• Design A 10,000 15,000
  14,000
• Design B 8,000 18,000
  12,000
• Design C 6,000 16,000
  21,000