Integrating multi criteria analysis and clustering techniques for the segmentation of after-sale spare part inventory

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dc.contributor.authorGüçdemir H.
dc.contributor.authorIlgin M.A.
dc.date.accessioned2024-07-22T08:16:35Z
dc.date.available2024-07-22T08:16:35Z
dc.date.issued2014
dc.description.abstractTimely and cost effective supply of spare parts is a vital issue in after sales service. If the demand for spare parts is overestimated, holding costs increase. Underestimation of demand results in lost goodwill of the customers. In order to manage the spare part inventories effectively, companies generally determine the importance level of each spare part and apply a suitable inventory control policy. In this study, we integrate clustering techniques and analytic hierarchy process (AHP) to determine the importance levels of spare parts kept by a television manufacturer. First, spare parts are grouped into 3 main categories using clustering algorithms. Then AHP is used to determine importance level of each group by considering several criteria including frequency, criticality, total monthly usage, lead time, availability, substitutability and tendency of obsolescence. Finally, suitable inventory policies are suggested for each spare part group.
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/16864
dc.language.isoEnglish
dc.publisherComputers and Industrial Engineering
dc.subjectAnalytic hierarchy process
dc.subjectCost effectiveness
dc.subjectHierarchical systems
dc.subjectInventory control
dc.subjectManufacture
dc.subjectObsolescence
dc.subjectAfter-sales services
dc.subjectAnalytic hierarchy process (ahp)
dc.subjectClustering
dc.subjectClustering techniques
dc.subjectInventory control policies
dc.subjectInventory policies
dc.subjectMulti Criteria Analysis
dc.subjectSpare parts
dc.subjectClustering algorithms
dc.titleIntegrating multi criteria analysis and clustering techniques for the segmentation of after-sale spare part inventory
dc.typeConference paper

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