Abstract

The mining industry commonly uses qualitative risk analysis methods to analyse hazards and business risks. These methods suffer from a number of limitations. The use of language required to describe risk events creates inherent subjectiveness. Assumptions, resultant model uncertainty and natural or statistical variability make scenario comparisons difficult. This thesis demonstrates how quantitative risk analysis, as an alternative can be successfully used to overcome these shortfalls. An industry survey confirmed the infrequent application of quantitative methods across the mining industry. Given the high risk/cost nature of the industry, adopting a more data focussed management approach would benefit many mine management functions. The value of quantitative risk analysis was successfully illustrated by an earthmover tyre management case study. A holistic summary of issues, considerations and variables around optimal tyre asset, technical and operational tyre management was developed. Tyre performance data was analysed using ‘grouped failure analysis’. Grouped failure analysis was found to provide more representative tyre data statistics as it does not assume that tyres enter service in ‘as good as new’ or equal condition when rotated across different vehicle positions throughout their lifecycle. This is a significant improvement as wear characteristics are now reflected more accurately for subsequent tyre life cycle modelling and decision making. Three decision making models simulating tyre rotation using Weibull analysis were developed. Rotation intervals optimising tyre operating cost, tyre demand and tyre wear were calculated. These are fundamental drivers of successful tyre management and the methods developed in this thesis have direct application to tyre management. There are no qualitative methods currently available capable of delivering such decision-making ability. Given the ongoing mining boom, quantitative risk analysis approaches to better manage the scarce and expensive earthmover tyre supply, or any other engineering asset will become increasingly important.

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