A comparative study of truck cycle time prediction methods in open‐pit mining

Purpose – The purpose of this paper is to compare the predictive capability of three methods of truck cycle time estimation in open‐pit mining: computer simulation, artificial neural networks (NNs), and multiple regressions (MRs). The aim is to determine the best method. The most common method currently used is computer simulation.Design/methodology/approach – Truck cycle times at a large open pit mine are estimated using computer simulation, artificial NNs, and MRs. The estimated cycle times by each method are in turn compared to the actual cycle times recorded by a computerized mine monitoring system at the same mine. The errors associated with each method relative to the actual cycle times are documented and form the basis for comparing the three methods.Findings – The paper clearly indicates that computer simulation methods used in predicting truck cycle times in open‐pit mining underestimate and overestimate the results for short and long hauls, respectively. It appears that both NN and regression mo...