A Clustering Classification of Spare Parts for Improving Inventory Policies

Abstract

Inventory policies in a company may consist of storage, control, and replenishment policy. Since the result of common ABC inventory classification can only affect the replenishment policy, we are proposing a clustering based classification technique as a basis for developing inventory policy especially for storage and control policy. Hierarchical clustering procedure is used after clustering variables are defined. Since hierarchical clustering procedure requires metric variables only, therefore a step to convert non-metric variables to metric variables is performed. The clusters resulted from the clustering techniques are analyzed in order to define each cluster characteristics. Then, the inventory policies are determined for each group according to its characteristics. A real data, which consists of 612 items from a local manufacturer's spare part warehouse, are used in the research of this paper to show the applicability of the proposed methodology.