Shovel-Truck Haulage Analysis Using Stochastic Discrete Event Simulation

Raymond Ninnang Tiile, Felix Adaania Kaba, Nassib Aouad, Francis Arthur

Abstract: Detailed weekly mining plans are prepared by Perseus Mining Ghana Limited (PMGL) geared towards the accomplishment of monthly mining targets. Weekly and daily mining volumes are established primarily based on the excavator dig rates and excavator (shovel) availabilities and utilizations. A daily mining target of 15, 000 BCM of material is expected to be mined by two (2) shovels and as many as twenty (20) dump trucks over a period of one (1) month. Given the size of pit and the number of dump trucks, truck queuing and congestion in-pit and on roads with their downstream consequences is highly anticipated. This paper therefore seeks to address the above challenge by using an Arena-based stochastic discrete event simulation to derive an optimum shovel-truck combination that improves productivity, minimizes operation cost and maximizes overall profitability.

Keywords: Mine planning, Arena stochastic discrete simulation, Productivity, Optimization, Profitability