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Multi‐item service constrained (s, S) policies for spare parts logistics systems

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  • Morris A. Cohen
  • Paul R. Kleindorfer
  • Hau L. Lee
  • David F. Pyke

Abstract

Many organizations providing service support for products or families of products must allocate inventory investment among the parts (or, identically, items) that make up those products or families. The allocation decision is crucial in today's competitive environment in which rapid response and low levels of inventory are both required for providing competitive levels of customer service in marketing a firm's products. This is particularly important in high‐tech industries, such as computers, military equipment, and consumer appliances. Such rapid response typically implies regional and local distribution points for final products and for spare parts for repairs. In this article we fix attention on a given product or product family at a single location. This single‐location problem is the basic building block of multi‐echelon inventory systems based on level‐by‐level decomposition, and our modeling approach is developed with this application in mind. The product consists of field‐replaceable units (i.e., parts), which are to be stocked as spares for field service repair. We assume that each part will be stocked at each location according to an (s, S) stocking policy. Moreover, we distinguish two classes of demand at each location: customer (or emergency) demand and normal replenishment demand from lower levels in the multiechelon system. The basic problem of interest is to determine the appropriate policies (si Si) for each part i in the product under consideration. We formulate an approximate cost function and service level constraint, and we present a greedy heuristic algorithm for solving the resulting approximate constrained optimization problem. We present experimental results showing that the heuristics developed have good cost performance relative to optimal. We also discuss extensions to the multiproduct component commonality problem.

Suggested Citation

  • Morris A. Cohen & Paul R. Kleindorfer & Hau L. Lee & David F. Pyke, 1992. "Multi‐item service constrained (s, S) policies for spare parts logistics systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 39(4), pages 561-577, June.
  • Handle: RePEc:wly:navres:v:39:y:1992:i:4:p:561-577
    DOI: 10.1002/1520-6750(199206)39:43.0.CO;2-5
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    References listed on IDEAS

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    1. Morris A. Cohen & Paul R. Kleindorfer & Hau L. Lee, 1988. "Service Constrained (s, S) Inventory Systems with Priority Demand Classes and Lost Sales," Management Science, INFORMS, vol. 34(4), pages 482-499, April.
    2. FISHER, Marshall L. & WOLSEY, Laurence A., 1982. "On the greedy heuristic for continuous covering and packing problems," LIDAM Reprints CORE 505, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Yigal Gerchak & Mordechai Henig, 1989. "Component commonality in assemble‐to‐order systems: Models and properties," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(1), pages 61-68, February.
    4. Kenneth R. Baker & Michael J. Magazine & Henry L. W. Nuttle, 1986. "The Effect of Commonality on Safety Stock in a Simple Inventory Model," Management Science, INFORMS, vol. 32(8), pages 982-988, August.
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    Cited by:

    1. Ulrich W. Thonemann & Alex O. Brown & Warren H. Hausman, 2002. "Easy Quantification of Improved Spare Parts Inventory Policies," Management Science, INFORMS, vol. 48(9), pages 1213-1225, September.
    2. Jing-Sheng Song & Yue Zhang, 2020. "Stock or Print? Impact of 3-D Printing on Spare Parts Logistics," Management Science, INFORMS, vol. 66(9), pages 3860-3878, September.

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