A simulation-based algorithm for solving surface mines’ equipment selection and sizing problem under uncertainty
Shiv Prakash Upadhyay, M. Tabesh, Mohammad Mahdi Badiozamani, Ali Moradi Afrapoli, Hooman Askari-Nasab
Abstract
Delivering a robust long-term mine plan depends on the precise prediction of mining fleet productivity and the estimation of the required fleet’s size over the mine life. In open-pit mining, fleet productivity and the required fleet’s size are directly related to the tonnage of moved material and the time and distance it takes for the trucks to move the mined material. All the above-mentioned parameters are associated with inherent uncertainties. Thus, incorporating these uncertainties is required in the prediction and estimation procedure to predict fleet productivity and subsequently estimate the required fleet size. This article presents a new simulation-based algorithm to predict fleet productivity and estimate the required fleet size in open-pit mines. Implementation of the developed simulation-based algorithm at an operating open-pit mine provided a considerable improvement over the existing method, with a slight (negative 2%) deviation in predicting fleet productivity compared to historical data.