Optimum Shovel performance, the underlying role of operators loading practices


Ali Yaghini, University of Alberta; Robert Hall, University of Alberta

Material loading and handling are considered critical tasks in a mining operation. They are collectively responsible for a large portion of operation and maintenance costs, yet it is the mine production which relies on them. During the  past two decades, the main focus for improvement has been on optimizing haulage by implementing autonomous systems and eliminating human factors. Whilst automation helps haulage units to reach their peak performance, loading units still need to perform optimally  in order to maximize production. This study aims to search for the best practices based on analyzing the performance of several operators at a mine site. Data analysis is performed on a shovel monitoring system database, and results are used in a discrete event simulation modeling to investigate the role of shovels and their operators in a mine operation. The extent to which production can be improved by modifying  shovel operators’ training will be demonstrated and best practices are highlighted. The results of this study can be used by mine companies to asses their current shovel performance and to make changes to improve production.