Table of Contents
Journal of Industrial Engineering
Volume 2013 (2013), Article ID 827274, 7 pages
http://dx.doi.org/10.1155/2013/827274
Research Article

Multiple Criteria ABC Analysis with FCM Clustering

1Department of Industrial Engineering, Faculty of Engineering, Kocaeli University, Umuttepe Campus, 41380 Kocaeli, Turkey
2Department of Industrial Engineering, Faculty of Engineering, Yildiz Technical University, 34349 Istanbul, Turkey

Received 13 August 2012; Revised 29 October 2012; Accepted 12 November 2012

Academic Editor: Josefa Mula

Copyright © 2013 Gulsen Aydin Keskin and Coskun Ozkan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.