A demand classification scheme for spare part inventory model subject to stochastic demand and lead time

Abstract

In this study, we aim to develop a demand classification methodology for classifying and controlling inventory spare parts subject to stochastic demand and lead time. Using real data, the developed models were tested and their performances were evaluated and compared. The results show that the Laplace model provided superior performance in terms of service level, fill rate (FR) and inventory cost. Compared with the current system based on normal distribution, the proposed Laplace model yielded significant savings and good results in terms of the service level and the FR. The Laplace and Gamma optimisation models resulted in savings of 82 and 81%, respectively.

Keywords:

• inventory control
• spare parts
• MRO – maintenance, repair and operating items
• steel industry

Acknowledgements

We are grateful to AcelorMittal that provided the data for this study. We also acknowledge the financial support provided by Universidade Federal de Minas Gerais – Brazil. Finally, we thank the anonymous reviewers for their constructive comments, which helped us to improve the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.