Survival time and reliability assessment of bulk solids carriers in the mining and logistics industry

Abstract

In complex industrial systems, the deterioration of equipment and production of defective products are important points that increase the costs inherent to the production function. In this context, the purpose of this article is to estimate the survival of a group of pieces of industrial port equipment known as solid bulk conveyors, thus contributing to decision-making in the maintenance process. To achieve this goal, the Kaplan-Meier method was used to estimate the probability of global survival, and the survival curves were compared using the Log-rank test. To this end, the effect of each covariate on the survival time of the conveyors was analyzed using the Cox regression model, for which an analysis of residuals and influential observations was conducted. The 75% probability of survival of solid bulk cargo is equivalent to an operational availability time of 444 h. It was found that, of the 95 conveyors that were evaluated, 38 (40%) failed and 57 (60%) were censored by the end of the study. The results indicate a significant reduction in the probability of survival of equipment during operation time, as well as a significant difference between the survival curves of the covariates of shift, types of minerals, the number of wagons and tons moved, indicating that these are important predictors in the Cox regression model.

Keywords

• Industrial maintenance
• Kaplan-Meier estimator
• Cox regression
• Equipment reliability