EconPapers    
Economics at your fingertips  
 

Inventory control of spare parts using a Bayesian approach: a case study

K-P. Aronis, Ioulia Magou, Rommert Dekker and George Tagaras

No EI 9950-/A, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: This paper presents a case study of applying a Bayesian approach to forecast demand and subsequently determine the appropriate parameter S of an (S-1,S) inventory system for controlling spare parts of electronic equipment. First, the problem and the current policy are described. Then, the basic elements of the Bayesian approach are introduced and the procedure for calculating the appropriate parameter S is illustrated. Finally, we present the results of applying the Bayesian approach in an innovative way to determine the stock levels of three types of circuit packs at several locations. According to the proposed method, a lower base stock than the one currently used is sufficient to achieve the desired service level.

Keywords: Bayesian analysis; case study; inventory control; spare parts (search for similar items in EconPapers)
Date: 1999-12-22
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://repub.eur.nl/pub/1622/feweco19991222095719.pdf (application/pdf)

Related works:
Journal Article: Inventory control of spare parts using a Bayesian approach: A case study (2004) Downloads
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: https://EconPapers.repec.org/RePEc:ems:eureir:1622

Access Statistics for this paper

More papers in Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute Contact information at EDIRC.
Bibliographic data for series maintained by RePub ( this e-mail address is bad, please contact ).

 
Page updated 2025-03-22
Handle: RePEc:ems:eureir:1622