Assessment of Spare Parts Requirement by Reliability: A Case Study

Abstract

Spare parts provision is a complex problem and requires an accurate model to analyze all factors that may affect the required number of spare parts. The number of spare parts required for an item can be effectively estimated based on its reliability. The reliability characteristics of an item are influenced by different factors such as the operational environment, maintenance policy, operator skill, etc. However, in most reliability-based spare parts provision (RSPP) studies, the effect of these influence factors has not been considered. Hence, the statistical approach selected for reliability performance analysis must be able to handle the effect of these factors. One of the important models for reliability analysis by considering risk factors is the proportional hazard model (PHM), which has received less attention in the field of spare parts provisioning. Thus, this paper aims to demonstrate the application of the available reliability models with covariates in the field of spare part predictions using a case study. The proposed approach was evaluated with data from the system of fleet loading of the Jajarm Bauxite mine in Iran. The outputs represent a significant difference in spare parts forecasting and inventory management when considering covariates.