Predicting the overall equipment efficiency of core drill rigs in mining using ANN and improving it using MCDM

In this manuscript, an attempt has been made to predict and improve the overall equipment effectiveness of core drill rigs. A combined Box–Jenkins artificial neural network model was used develop a three parameter (drill pushing pressure, penetration rate & average pillar pit cycle time) for predicting effectiveness. efficiency The values mean percentage error, root square normalized men bias biased error coefficient determination were found be 9.462%, 17.378%, 0.194, 0.96%, 0.0014 0.923. Empirical relationships developed between input output parameters its evaluated using analysis variance. For attaining 74.9% effectiveness, optimized time predicted 101.7 bar, 0.94 m/min 272 min, which validated. Interactions, perturbations sensitivity conducted.