Modelling the influence of electric shovel operator performance on mine productivity

CIM Journal Preprints, Vol. 11, No. 1, 2020

A. Yaghini, R. A. Hall, and D. Apel

Truck-shovel systems are commonly used for material handling during surface mining. Not only does the overall outcome of a mine rely heavily on haulage system performance, but it constitutes a significant portion of mine operational costs. Using detailed data from a shovel monitoring system, this study statistically analyzes variations among key performance activities by shovel operators. Based on the results, a novel operator relative score system is introduced. To quantify the extent to which different aspects of a mining operation could be influenced by shovel operator practices, an operator discrete event simulation sub-module was developed and verified. Results showed that operators could affect mine production, number of trucks, and queue times by up to 20, 16, and 41%, respectively. This simulation model can be used by mining companies to assess their current shovel performance and improve production by modifying shovel operator practices.

Keywords: Electric rope shovel (RS), Human factor, Performance monitoring, Simulation, Surface mining
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