A simulation model for estimation of mine haulage fleet productivity

Abstract

A good estimation of haulage fleet productivity is a pivotal input to determine the mine fleet requirement. In open pit mining, the two major factors affecting the fleet productivity are the planned tonnage to be moved, that is based on the long-term production schedule, and the time it takes to move the dirt tonnage which depends on the mine road network. The haulage speed, haulage time and the truck load tonnages are all probabilistic values due to the uncertainty involved in real mining operations, and simulation technique is a powerful tool to capture this uncertainty. In this paper, a simulation framework is presented to estimate the productivity of haulage fleet for open pit mining operations with truck-and-shovel system. The Productivity KPI is the Tonne per Gross Operating Hour (TPGOH) for combinations of Dig and Dump locations. Historical data are used to fit probability distributions for haulage cycle components, and the mine road network and long-term production schedule are the main inputs to the model. The developed model is verified and validated through implementing it on a real case from Alberta oil sands open pit operations.