An Advanced Heuristic for Multiple‐Option Spare Parts Procurement after End‐of‐Production. (1st May 2012)

• Record Type: Journal Article
• Authors: Inderfurth, Karl; Kleber, Rainer
• Is Part Of: Production and operations management. Volume 22:Number 1(2013:Jan./Feb.)
• Page Start: 54
• Page End: 70
• Publication Date: 2012-05-01
• Subjects: Production management -- Periodicals; 658.505
• DOI: 10.1111/j.1937-5956.2012.01358.x
• Languages: English
• ISSNs: 1059-1478

Abstract

<abstract abstract-type="main" id="poms1358-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>After‐sales service is a major source of profit for many original equipment manufacturers in industries with durable products. Successful engagement in after‐sales service improves customer loyalty and allows for competitive differentiation through superior service like an extended service period during which customers are guaranteed to be provided with service parts. Inventory management during this period is challenging due to the substantial uncertainty concerning demand over a long time horizon. The traditional mechanism of spare parts acquisition is to place a large final order at the end of regular production of the parent product, causing major holding costs and a high level of obsolescence risk. With an increasing length of the service period, more flexibility is needed and can be provided by adding options like extra production and remanufacturing. However, coordinating all three options yields a complicated stochastic dynamic decision problem. For that problem type, we show that a quite simple decision rule with order‐up‐to levels for extra production and remanufacturing is very effective. We propose a heuristic procedure for parameter determination which accounts for the main stochastic and dynamic interactions in decision making, but still consists of relatively simple calculations that can be applied to practical problem sizes. A numerical study reveals that the heuristic performs extremely well under a wide range of conditions, and therefore can be strongly recommended as a decision support tool for the multi‐option spare parts procurement problem. A comparison with decision rules adapted from practice demonstrates that our approach offers an opportunity for major cost reductions.</p> </abstract>