Economics at your fingertips  

Optimizing Machine Spare Parts Inventory Using Condition Monitoring Data

Sonja Dreyer (), Jens Passlick (), Daniel Olivotti (), Benedikt Lebek () and Michael Breitner ()
Additional contact information
Sonja Dreyer: Leibniz Universität Hannover
Jens Passlick: Leibniz Universität Hannover
Daniel Olivotti: Leibniz Universität Hannover
Benedikt Lebek: bhn Dienstleistungs GmbH & Co. KG

A chapter in Operations Research Proceedings 2016, 2018, pp 459-465 from Springer

Abstract: Abstract In the manufacturing industry, storing spare parts means capital commitment. The optimization of spare parts inventory is a real issue in the field and a precise forecast of the necessary spare parts is a major challenge. The complexity of determining the optimal number of spare parts increases when using the same type of component in different machines. To find the optimal number of spare parts, the right balance between provision costs and risk of machine downtimes has to be found. Several factors are influencing the optimum quantity of stored spare parts including the failure probability, provision costs and the number of installed components. Therefore, an optimization model addressing these requirements is developed. Determining the failure probability of a component or an entire machine is a key aspect when optimizing the spare parts inventory. Condition monitoring leads to a better assessment of the components failure probability. This results in a more precise forecast of the optimum spare parts inventory according to the actual condition of the respective component. Therefore, data from condition monitoring processes are considered when determining the optimal number of spare parts.

Date: 2018
References: Add references at CitEc
Citations: Track citations by RSS feed

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This item can be ordered from

DOI: 10.1007/978-3-319-55702-1_61

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2023-04-06
Handle: RePEc:spr:oprchp:978-3-319-55702-1_61