Bayesian statistics and production reliability assessments for mining operations

Abstract

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.

Keywords:

• mining operations
• reliability analysis
• Bayesian statistics

Acknowledgements

The authors would like to acknowledge the funding and support from Highland Valley Copper Mine. The financial support was also obtained from the Natural Sciences and Engineering Research Council of Canada Grant number NSERC-CRD: 314409-04.