Application of Quantitative Probabilistic Risk Assessment in the Minerals Industry

Abstract

Probabilistic risk assessment has advantages over qualitative risk ranking for cases where choices need to be made that require consideration of variable inputs, where model sensitivities to variable inputs and their effects are to be studied, and where more detailed output is required to form the basis of sound and informed decision making. Monte Carlo Simulation and probability of failure prediction using First Order Reliability Methods (FORM) both provide this functionality and are used to both demonstrate the effects of variability on risk assessments for heat induced tyre failure, and to highlight the advantages of such a probabilistic approach. OPSOMMINGDie probabilistiese assessering van risiko beskik oor bepaalde voordele vir gevalle waar keuses uitgeoefen moet word met onderliggende veranderlike insette, waar modelsensitiwiteit bepaal moet word vir inseteienskappe en die model gesonde en ingeligde besluitvorming moet ondersteun. Monte Carlo simulasie en eerste orde betroubaarheidsmetodes is daartoe instaat om die resultate te demonstreer oor hoe veranderlikheid risikoassessering beïnvloed by hittegeïnduseerde mislukkings van voertuigbande.

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