Make to order Make to Stock Production Systems

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Make to order - Make to Stock Production Systems

• By ÖNCÜ HAZIR

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OUTLINE

• INTRODUCTION
• LITERATURE REVIEW
• PROPOSED MODEL
• INSIGHTS AND CONCLUSION

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Make to Stock(MTS) Systems

• Generally products are produced in batches.
• Finished goods inventories for most of the items
  are held.
• The advantage is that customer delivery times are
  minimized as expense of inventory holding costs.
• Typically, companies producing standard items
  with accurate demand forecasts prefer make to
  stock production systems.

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Make to Order(MTO) Systems

• Generally prefered when exact needs of customers
  are difficult to anticipate.
• There exists large number of product
  configurations.
• Typically no finished goods inventory are held,
  customer orders are backlogged and due dates for
  each item are negotiated with customers.

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HYBRID SYSTEMS

• The models mostly focus on determining which
  items should be made to order, or to stock
  establishing a good inventory policy for make to
  stock items and evaluating the performance of the
  system.
• System performance is usually measured with
  waiting time distributions, as well as average
  setup, holding and backlogging costs.
• The models in the literature can be roughly
  classified according to the assumptions related
  to setups and number of servers.

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Literature Review Williams(1984)

• Williams(1984) assumed lower demand items are MTO
  and higher demand items as MTS. However this is
  not a strong assumption and most of the current
  models do not have such an assumption.
• He assumes a (Q, r) policy for MTS items.
  Priority is given to order or batch with the
  largest waiting time.

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Literature Review Federgruen and Katalan (1999)

• They mainly focus whether to interrupt production
  of make to stock items when an order is faced.
• Under absolute priority rule, priority is given
  to MTO items. Preemption may or may not be
  allowed or not.
• Under postponable priority rules make to order
  items are inserted into the production schedule
  of the MTS items, but only when the facilities
  would switch between MTS items.

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Literature Review Rajagopolan (2002)

• Rajagopolan (2002) focuses to decide whether an
  item is MTS or MTO and what type of inventory
  policy to use for the items made to stock.
• He models the system as single server M/G/1
  queue, on first come first served base. When
  demand occurs for a MTO item, the demand is
  satisfied in that period.
• (Q, r) inventory model is used for MTS items.
  The congestion effect, negative effect of an item
  to other items is modeled.

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Literature ReviewCarr and Duenyas (2000)

• Carr and Duenyas (2000) focuses to model how a
  firm should accept or reject an additional order
  and which type of product to produce next .
• Unit profits of MTO items are assumed to be
  higher however large shortage penalties exist
  for MTS items.

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Literature ReviewCarr and Duenyas (2000)

• They model the system as a Markov decision
  process, where the states are number of MTS items
  in the stock (n1) and number of units of MTO
  items in process (n2).
• Then this analysis works to establish a dynamic
  decision mechanism to accept or reject the order
  by looking at the current state of the system.

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Literature ReviewCarr and Duenyas (2000)
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Proposed System

• A system of many MTO items and a single MTS item
  is considered.Up to time t, processes are the
  same for MTO and MTS items.
• At this time point t intermediate inventory of
  generic work in process is held.Finished goods
  inventory will be held for MTS items.
• Performance measures are expected number of
  backlogged units for MTS item and response time
  to all customer orders at a given time for MTO
  items.
• Objective is minimizing the inventory holding
  costs.

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Proposed System
t
Intermediate Stock
l1
l2
T-t
MTS
MTO
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Assumptions

• It is possible to delay production
  differentiation up to point t. Manufacturing lead
  time(T) is fixed.
• Demand for MTO and MTS items follows Poisson
  distribution with means ?1, ?2 respectively
• MTO items have absolute priority and preemption
  is also allowed.
• No fixed ordering cost exists.

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MODEL
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NOTATION

• S1 Base stock level at intermediate stockpile
• S2 Base stock level for MTS items
• Y Customer response time
• P(x/ ?T) probability of having a demand of x in
  the period ?T.
• ?(S1, S2) Expected number of backorders for MTS
  items.
• ? Effective lead-time
• ?(S1) Fill rate at the intermediate inventory
  stockpile

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Insights about the Model

• Finding the fill rate at the intermediate
  inventory stockpile ?(S1) is crucial.
• Effective lead-time for the MTS item is a
  function of ?(S1) , which is a function of the
  number of customer orders for the MTO items.
• So fill rate at MTS items is a function of stock
  level at the intermediate level stockpile, as
  well as number of customer orders for MTO items.

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Insights about the Proposed System

• The proposed system is a combination of a pull
  and push system.
• By the applied system customer respond times for
  MTO will decrease, since a generic inventory
  exists to be processed. The customer lead-time
  will be shortened.
• Inventory holding costs will be less for MTS
  items. Since unit holding cost of generic
  inventory stockpile will be less than finished
  goods inventory.