Optimizing Inventory Carrying Cost Using Rank Order Clustering Approach for Small and Medium Enterprises (SMES)

Authors

Ganesh B.Narkhede,  Research Scholar
Department of Production Engineering, College of Engineering, Pune, India.
Ganesh B.Narkhede, Assistant Professor
Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, Pune, India.
Neela Rajhans, Professor
Department of Manufacturing and Industrial Engineering, College of Engineering, Pune, India.

Abstract

For any company, whether big enterprises or small and medium-sized enterprises (SMEs), inventory is one of the key assets. Therefore, inventory-related decisions directly influence the revenue generated by the firm. This work aims to find a sufficient degree of control over each inventory item and to mitigate the inventory management problems of SMEs. Rank Order Clustering (ROC) algorithm is used in this study for multi-item inventory item aggregation. The proposed framework is tested on a medium-sized gearmanufacturing firm that manufactures 40 different types of planetary and customized gear-boxes. The results demonstrate 47.64 % of cost-saving through the proposed methodology of cluster formation using ROC and quantity discounts. This approach helps to identify different assemblies to aggregate the component requirements and to formulate a particular inventory strategy to minimize inventory carrying costs for each component.