Controlling inventory by combining ABC analysis and fuzzy classification Ching-Wu Chu * , Gin-Shuh Liang, Chien-Tseng Liao Department of Shipping and Transportation Management, National Taiwan Ocean University, Pei Ning Road, Keelung 202, Taiwan, ROC article info Article history: Received 7 October 2005 Received in revised form 20 February 2008 Accepted 7 March 2008 Available online 20 March 2008 Keywords: ABC classification Multi-criteria inventory control Fuzzy classification abstract The objective of inventory management is to make decisions regarding the appropriate level of inventory. In practice, all inventories cannot be controlled with equal attention. The most widespread used inventory system is the ABC classification system, but the lim- itation of the ABC control system is that only one criterion is considered. The purpose of this paper is to propose a new inventory control approach called ABC–fuzzy classification (ABC–FC), which can handle variables with either nominal or non-nominal attribute, incorporate manager’s experience, judgment into inventory classification, and can be implemented easily. Our ABC–FC approach is implemented based on the data of the Keelung Port. The results of our study show that 59 items are identified as very important group, 69 items as important group, and the remaining 64 items as unimportant group. By comparing the results of ABC– FC with the original data, we find that our ABC–FC analysis shows a high accuracy of clas- sification. Some concluding remarks and suggestions for inventory control are also provided. Ó 2008 Elsevier Ltd. All rights reserved. 1. Introduction The inventory control has been a very classical OR problem. An extremely large number of models have been developed to solve inventory problems. Each model uses a particular set of hypotheses. In practice, organizations have hundreds of differ- ent types of materials and spare parts, so it is easy to loss sight of effectively managing materials. ABC analysis is one of the most widely used techniques in organizations. ABC classification allows an organization to separate stock keeping units into three groups: A – very important, B – important, and C – least important. The amount of time, effort, and resources spent on inventory control should be in the relative importance of each item. The classification of items into A, B, C groups has generally been based on just one criterion. For inventory items, the cri- terion is often the annual dollar usage of the item. However, there may be other criteria that represent other important con- siderations for management. The criticality of a stock-out of the item, the rate of obsolescence, the scarcity, substitutability, and order size requirement of the item and the lead time of supply, are all examples of such considerations. Thus, it has been generally recognized that the traditional ABC analysis may not be able to provide a good classification of inventory items in practice (Guvenir & Erel, 1998; Huiskonen, 2001; Partovi & Anandarajan, 2002). There are many instances when other criteria become important in deciding the importance of an inventory item. This problem becomes a multi-criteria inventory classification that has been studied by some researchers in the past. In general, complex computational tools or procedures are needed for multi-criteria ABC classification. The concept of fuzzy theory has received considerable attention recently and it is often used in handling the fuzziness and uncertainty of data or information. Fuzzy classification is a technique that uses the available information in a set of independent attributes to predict the value 0360-8352/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.cie.2008.03.006 * Corresponding author. Tel.: +886 2 24622192x3407; fax: +886 2 24631903. E-mail address: cwchu@mail.ntou.edu.tw (C.-W. Chu). Computers & Industrial Engineering 55 (2008) 841–851 Contents lists available at ScienceDirect Computers & Industrial Engineering journal homepage: www.elsevier.com/locate/caie