Improving the Maintenance System of Tippers A Case Study

Abstract

A mine having five quarries needs at least 10 tippers out of 17 to be in running condition for a particular shift. However, with the poor availability of the tippers, the production was hampered. Substantial improvement of availability and utilisation of tippers under the existing infrastructure of the system was of primary concern to the plant management. Performance of all the tippers was evaluated through Mean Time-to-Failure (MTTF) and Mean Down Time (MDT) including the overall system performance. Based on Weibull(b, c) and Exponential(λ) distributions, the reliability of all the tippers (component reliability) along with the overall system reliability with respect to 10-out-of-17 structure was computed. Next, tippers were clustered, using k-means clustering algorithm, and the group reliabilities were obtained which led to different options for improving the overall system's reliability. The Pareto Principle was adopted to identify dominant failure modes. Using the matrix of interrelationship, five failure modes were found to be self-inducing in nature. The minimum number of repairmen required to keep the desired number of tippers running with a certain probability was determined, through simulation technique, using the classical repairmen model. The net effect of implementation of suitable preventive maintenance activities along with overhauling, training, ordering strategy of spare parts and maintenance crew restructuring was an increase in average utilisation of tippers from 66.8% to the level of 75%, whereas the system availability has improved to 85.75% from the earlier level of 78.34%.