Predictive Maintenance of Heavy Equipment in Indonesia Leading Heavy Equipment Company

Abstract

The use of heavy equipment in a production process, especially coal mining, is very dominant and is the main work tool. Therefore, the productivity of mining is very dependent on the performance of the heavy equipment used. In maintaining the performance of today's machines, it is not enough only with preventive and corrective maintenance, but also with predictive maintenance (PdM). Through PdM, it is expected that heavy equipment performance can be maintained properly because it can reduce the unscheduled breakdowns. PdM in this research aims to help prioritize heavy equipment routine service management, so that more urgent heavy equipment conditions will get priority for maintenance first so as to prevent unscheduled breakdowns compared to current service management which still uses time based as the only maintenance priority tool. PdM will focus on finding warnings and indicators that can be used to determine the remaining useful life (RUL) of engine components by using data from telemetry, oil analysis, historical component lifetime and other maintenance data. In this research, we get the predictive maintenance results in the form of 2 types of warnings and also the RUL prediction with a mean absolute error of 91 hours compared to the actual RUL.