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
University of Alberta, Edmonton, Alberta, Canada
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.
Electric rope shovel (RS), Human factor, Performance monitoring, Simulation, Surface mining