“Make to order - Make to Stock Production Systems By: ÖNCÜ HAZIR

OUTLINE INTRODUCTION LITERATURE REVIEW PROPOSED MODEL INSIGHTS AND CONCLUSION

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.

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.

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.

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.

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.

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.

Literature Review Carr 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.

Literature Review Carr 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.

Literature Review Carr and Duenyas (2000)

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.

Proposed System Intermediate Stock MTS   t T-t MTO

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.

MODEL

NOTATION S 1 : Base stock level at intermediate stockpile S 2 : Base stock level for MTS items Y: Customer response time P(x/ T): probability of having a demand of x in the period T.  (S 1, S2): Expected number of backorders for MTS items.  : Effective lead-time  (S 1 ) Fill rate at the intermediate inventory stockpile

Insights about the Model Finding the fill rate at the intermediate inventory stockpile  (S 1 ) is crucial. Effective lead-time for the MTS item is a function of  (S 1 ), 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.

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.