An iterative method for the simultaneous optimization of repair decisions and spare parts stocks

Research output: Working paper

17 Downloads (Pure)

Abstract

In the development process of a capital good, it should be decided how to maintain it once it is in the field. The level of repair analysis (LORA) is used to answer the questions: 1) which components to repair upon failure, and which to discard, 2) at which locations in the repair network to perform the repairs, and 3) at which locations to deploy resources, such as repair equipment. Next, it should be decided what amount of spare parts to store at each location in the network in order to guarantee a certain availability of the product. Usually, the LORA and the spare parts stocking problem are solved sequentially. However, solving the LORA first can lead to high spare parts costs. Therefore, we propose an iterative approach to solve the two problems jointly. We find that the total costs are lowered with 3.2% on average and almost 35% at maximum in our experiments. A cost reduction of a few percent may be worth hundreds of thousands of euros over the life cycle of a capital good.
Original languageEnglish
Place of PublicationEnschede
PublisherUniversity of Twente, Research School for Operations Management and Logistics (BETA)
Number of pages21
ISBN (Print)9789038621135
Publication statusPublished - 2009

Publication series

NameBETA Working Paper
PublisherBeta Research School for Operations Management and Logistics, University of Twente
No.295

Keywords

  • IR-70208
  • Spare parts
  • METIS-259597
  • Inventories
  • Level of repair analysis
  • Service Logistics

Fingerprint Dive into the research topics of 'An iterative method for the simultaneous optimization of repair decisions and spare parts stocks'. Together they form a unique fingerprint.

  • Cite this

    Basten, R. J. I., van der Heijden, M. C., & Schutten, J. M. J. (2009). An iterative method for the simultaneous optimization of repair decisions and spare parts stocks. (BETA Working Paper; No. 295). Enschede: University of Twente, Research School for Operations Management and Logistics (BETA).