Reliability-based preventive maintainability analysis of shovel-dumper system in surface coal mine using ANN and isograph reliability workbench

Abstract

Shovel-Dumper system is utilized as a loading and transporting machines for intermediate mechanization in surface mining. For survival in the exceptional competition in the global business environment in recent years, it is basic that the Shovel - Dumper system should be reliable and maintained adequately and effectively. This paper seeks to study the reliability, availability, and preventive maintenance of one shovel and four dumpers in a surface coal mine with failure and repair data by Isograph Reliability Workbench (RWB) in the case of a non-parametric statistical method such as K-S test. The constraints and reasons for machine unavailability are outlined. The reliability and availability of the shovel-dumper system are evaluated and also evaluated the maintenance time interval to improve the 80% of reliability for each system. The reliability, availability and preventive maintenance have been validated with the artificial neural network (ANN). ANN model is then connected to a reliability method, K-S test to predict the failure probability of shovel and dumper.