DRILL BIT MONITORING AND REPLACEMENT OPTIMIZATION IN OPEN-PIT MINES

Abstract

Since 2012, low commodity prices have forced many mining companies to suspend or cease operations. To remain in business, some mine managers are exploring strategies to reduce operational costs. Given its importance as a cost element, increasing bench drilling efficiency and performance in open-pit mines has the potential to generate considerable savings. Efficiency and performance gains can be realized by monitoring the drilling operation, analyzing monitoring data with statistical tools and optimizing operational variables. Finding the best configuration of controllable drilling parameters would help to increase penetration rate and optimize drill bit replacement time so that fewer drill bits are consumed. In this paper, the optimal replacement time of a tricone drill bit is formulated as a cost minimization problem and solved by a genetic algorithm (GA). To demonstrate the proposed approach, the effects of controllable variables on drilling performance are experimentally quantified by statistical methods and used for optimization. Results show that the proposed approach can be used to determine the optimal replacement time for drill bits in open-pit mines.