Decision support for spare parts acquisition in post product life cycle

Decision support for spare parts acquisition in post product life cycle

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Article ID: iaor20091013
Country: Germany
Volume: 16
Issue: 1
Start Page Number: 17
End Page Number: 42
Publication Date: Mar 2008
Journal: Central European Journal of Operations Research
Authors: ,
Keywords: decision theory, artificial intelligence: decision support, programming: dynamic
Abstract:

A major task in service management is the timely and cost efficient provision of spare parts for durable products. This especially holds good, when the regular production of the product, its components and parts has been discontinued, but customer service still has to be guaranteed for quite a long time. In such post product life cycle period, three options are available to organize the spare parts acquisition, namely (i) setting up a single large order within the final lot of regular production, (ii) performing extra production runs until the end of service and (iii) using remanufacturing to gain spare parts from used products. These three options are characterized by different cost and flexibility properties. Due to the time-variability and uncertainty of demands for spare parts and also that of the returns of used products, it is a challenging task to find out the optimal combination of these three options. In this paper we show how this problem can be modeled and solved by Decision Tree and stochastic Dynamic Programming procedure. Based on the Dynamic Programming approach a heuristic method is proposed, which can be employed to come up with a simple solution procedure for real-world spare parts acquisition problems during the post product life cycle. A numerical example is presented to demonstrate the application of the solution methods described in the paper.

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