Bayesian statistics and production reliability assessments for mining operations

This article presents a novel application of structural reliability concepts to assess the reliability of mining operations. 'Limit-states' are defined to obtain the probability that the total productivity - measured in production time or economic gain - exceeds user-selected thresholds. Focus is on the impact of equipment downtime and other non-operating instances on the productivity and the economic costs of the operation. A comprehensive set of data gathered at a real-world mining facility is utilised to calibrate the probabilistic models. In particular, the utilisation of Bayesian inference facilitates the inclusion of data - and subsequent updating of the production probabilities - as more data become available. The article includes a description of the Bayesian approach, as well as the limit-state-based reliability methodology. A comprehensive numerical example demonstrates the methodology and the interpretation of the probabilistic results.