Reliability Based Spare Parts Provision (Case Study: Jajarm Bauxite Mine)

Spare parts provision is a complex problem and requires an accurate model to analysis 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 performance. The reliability characteristics of an item are influenced by different factors such as the operational environment, maintenance policy, operator skill, etc. However, in the majority of reliability-based, spare parts provision (RSPP) studies, the effect of these influence factors has not been considered, and the only variable of interest is the operating time. 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 performance analysis that takes influence factors into account is the proportional hazard model (PHM), which has received less attention in the field of spare parts provisioning. This approach considers of reliability (RRMC) for time independent and dependent covariates. The aim of this paper is to demonstrate the application of the available reliability models with covariates in the field of spare part predictions by means of a case study. The proposed approach was evaluated with data from the system of fleet loading of Jajarm Bauxite mine, Iran consisting of 5 Crane shovels. The outputs represent a significant difference in the required spare parts forecasting and inventory management when considering and ignoring covariates.