IE 3265 Production

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IE 3265 Production Operations Management

• Slide Series 2

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Topics for discussion

• Product Mix and Product Lifecycle as they
  affect the Capacity Planning Problem
• The Make or Buy Decision
• Its more than and !
• Break Even Analysis, how we filter in costs
• Capacity Planning
• When, where and How Much

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Product Issues Related to Capacity Planning

• Typical Product Lifecycle help many companies
  make planning decisions
• Facility can be designed for Product Families and
  the organization tries to match lifecycle demands
  to keep capacity utilized

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The Product Life-Cycle Curve
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The Product/Process Matrix
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Product Mix (Families) Typically Demand Different
Production Capacity Design

• Is product Typically One-Off?
• These systems have little standardization and
  require high marketing investment per product
• Typically whatever can be made in house will be
  made in house
• Most designs are highly private and guarded as
  competitive advantages
• Multiple Products in Low Volume
• Standard components are made in volume or
  purchased
• Shops use a mixture of flow and fixed site
  manufacturing layouts

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Product Mix (Families) Typically Demand Different
Production Capacity Design

• Few Major (discrete) Products in Higher Volume
• Purchase most components (its worth standardizing
  nearly all components)
• Make what is highly specialized or provides a
  competitive advantage
• Make decisions are highly dependent of capacity
  issues
• High Volume Standardized Commodity Products
• Flow processing all feed products purchased
• Manufacturing practices are carefully guarded
  Trade Secrets

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Make-Buy Decisions

• A difficult problem address by the M-B matrix
• Typically requires an analysis of the issues
  related to People, Processes, and Capacity
• Ultimately the problem is addressed economically

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Make Buy Decision Process
Can Item be Purchased?
NO
YES
Can Item be Made?
NO
YES
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Make Buy Decision Process
Is it cheaper to make than buy?
NO
YES
Is Capital Available To Make?
NO
YES
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Break-even Curves for the Make or Buy Problem
Cost to Buy c1x
Cost to makeKc2x
K

Break-even quantity
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Example M-B Analysis

• Fixed Costs to Purchase consist of
• Vendor Service Costs
• Purchasing Agents Time
• Quality/QA Testing Equipment
• Overhead/Inventory Set Asides
• Fixed Costs to Make (Manufacture)
• Machine Overhead
• Invested s
• Machine Depreciation
• Maintenance Costs
• Order Related Costs (for materials purchase and
  storage issues)

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Example M-B Analysis

• BUY Variable Costs
• Simply the purchase price
• Make Variable Costs
• Labor/Machine time
• Material Consumed
• Tooling Costs (consumed)

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Example M-B Analysis

• Make or Buy a Machined Component
• Purchase
• Fixed Costs for Component 4000 annually (20000
  over 5 years)
• Purchase Price 38.00 each
• Make Using MFG Process A
• Fixed Costs 145,750 machine system
• Variable cost of labor/overhead is 4 minutes _at_
  36.50/hr 2.43
• Material Costs 5.05/piece
• Total Variable costs 7.48/each

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Example M-B Analysis

• Make on MFG. Process B
• Fixed Cost of Machine System 312,500
• Variable Labor/overhead cost is 36sec _at_ 45.00/hr
  0.45
• Material Costs 5.05
• Formula for Breakeven Fa VaX Fb VbX
• X is Break even quantityFi is Fixed cost of
  Option iVi is Variable cost of Option i

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Example M-B Analysis

• Buy vs MFG1 BE is (145750-20000)/(38-7.48)
  4120 units
• Buy vs MFG2 BE is (312500-20000)/(38-5.5)
  9000 units
• MFG1 vs MFG2 BE is (312500-145750)/(7.48-5.50)
  68620 units

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Capacity Strategy

• Fundamental issues
• Amount. When adding capacity, what is the optimal
  amount to add?
• Too little means that more capacity will have to
  be added shortly afterwards.
• Too much means that capital will be wasted.
• Timing. What is the optimal time between adding
  new capacity?
• Type. Level of flexibility, automation, layout,
  process, level of customization, outsourcing,
  etc.

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Three Approaches to Capacity Strategy

• Policy A Try not to run short. Here capacity
  must lead demand, so on average there will be
  excess capacity.
• Policy B Build to forecast. Capacity additions
  should be timed so that the firm has excess
  capacity half the time and is short half the
  time.
• Policy C Maximize capacity utilization. Capacity
  additions lag demand, so that average demand is
  never met.

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Capacity Leading and Lagging Demand
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Determinants of Capacity Strategy

• Highly competitive industries (commodities, large
  number of suppliers, limited functional
  difference in products, time sensitive customers)
  here shortages are very costly. Use Type A
  Policy.
• Monopolistic environment where manufacturer has
  power over the industry Use Type C Policy.
• (Intel, Lockheed/Martin).
• Products that become obsolete quickly, such as
  computer products. Want type C policy, but in
  competitive industry, such as computers, you will
  be gone if you cannot meet customer demand. Need
  best of both worlds Dell Computer. (tend toward
  A with B in mind!)

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Mathematical Model for Timing of Capacity
Additions

• Let D Annual Increase in Demand
• x Time interval between adding capacity
• r annual discount rate (compounded
  continuously)
• f(y) Cost of operating a plant of
  capacity y
• Let C(x) be the total discounted cost of all
  capacity additions over an infinite horizon if
  new plants are built every x units of time. Then

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Mathematical Model (continued)

• xD is a desired future capacity
• A typical form for the cost function f(y) is
• k is a constant of proportionality (Investment
  for Capacity), and a measures the ratio of
  incremental to average cost of a unit of plant
  capacity.
• A typical value is a 0.6
• Note that since a lt 1 we expect economies of
  scale in plant construction

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Economies of Scale

• a has been found to be 0.5 0.7 for most
  industries
• Looking at the Example above (a.6) we find that
  to double the production capacity it takes only
  2a times the investment, an increase of 52 over
  the smaller size to double capacity
• For a .5 doubling capacity takes only a 41
  greater investment while for a .7 doubling
  capacity takes 62 more investment

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Mathematical Model (continued)

• Hence,
• It can be shown that this function is minimized
  at the value of x that satisfies the equation
• This is a transcendental equation, with no
  algebraic solution. However, using the graph
  (Fig. 1-14), one can find the optimal value of x
  or any value of a (0 lt a lt 1) thru function u
  rx

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Lets Try one

• Cast Iron Production System
• a 0.55
• k (million/ton new capacity) 0.0119
• D is estimated to be 1000 ton/yr
• Set r 12 (.12) typical MARR
• Searching Fig 1-14 with a (.55) we find u is
  about 1.2
• Solving for design
• X 1.2/.12 10 years
• Capacity required Dx 100010 10000
• Investment 0.0119(10000).55 1.886 Million
  (every 10 years)

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Issues in Plant Location

• Size of the facility
• Product lines
• Process technology
• Labor requirements
• Utilities requirements
• Environmental issues
• International considerations
• Tax Incentives