Improving productivity in mine loading and hauling operations through OEE analysis

Abstract

The Overall Equipment Effectiveness (OEE) index is a crucial metric for assessing equipment performance across various industries, particularly in the mining sector. However, the traditional method of calculating OEE assumes equal weighting for its constituent parameters, which limits its accuracy. This study proposes an enhanced approach based on the Analytical Hierarchy Process (AHP) to improve the accuracy of OEE assessments for fleets of loading and hauling machinery in open-pit mines. This method assigns optimal weightings to OEE parameters, enabling more precise identification of critical bottlenecks within the fleet. A case study conducted at an iron ore mine demonstrates that the proposed approach can effectively improve fleet productivity and reduce production costs. This study introduces a prototype OEE-based analytical framework that integrates AHP-derived, strategy driven weighting of effectiveness components with fleet-level aggregation and importance measure analysis, thereby extending conventional OEE from a descriptive operational metric to a decision-support tool for strategic mine planning. The results identify availability as the most influential component of effectiveness and reveal critical bottleneck machines whose improvement can significantly enhance overall fleet productivity.