Multiple Criteria ABC Analysis with FCM Clustering. (18th December 2012)

• Record Type: Journal Article
• Authors: Aydin Keskin, Gulsen; Ozkan, Coskun
• Other Names: Mula Josefa Academic Editor.
• Is Part Of: Journal of industrial engineering. Volume 2013(2013)
• Publication Date: 2012-12-18
• Subjects: Industrial engineering -- Periodicals; Industrial engineering; Periodicals; 620
• DOI: 10.1155/2013/827274
• Languages: English
• ISSNs: 2314-4882

Abstract

Abstract : The number of stock keeping units (SKUs) possessed by organizations can easily reach quite a few. An inventory management policy for each individual SKU is not economical to design. ABC analysis is one of the conventionally used approaches to classify SKUs. In the classical method, the SKUs are ranked with respect to the descending order of the annual dollar usage, which is the product of unit price and annual demand. The few of the SKUs that have the highest annual dollar usage are in group A and should be taken into account mostly; the SKUs with the least annual dollar usage are in group C and should be taken into account least; the remaining SKUs are in group B. In this study, we proposed fuzzy c-means (FCM) clustering to a multicriteria ABC analysis problem to help managers to make better decision under fuzzy circumstancse. The obtained results show that the FCM is a quite simple and an easily adaptable method to inventory management.