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Functional safety fault tree analysis of a model autonomous haulage system
Miller, Benjamin H.
Miller, Benjamin H.
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2020
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2021-10-15
Abstract
Autonomous Haulage Systems (AHS) in mining began trials in the 1990’s but have only become widely accepted in the last five years. Mine operators with AHS deployments are reporting greater than 20% increases in utilization of trucks and reductions of hourly operating costs as compared to manned fleets. Future deployments of AHS could be improved through the implementation of a more complex and systematic approach to safety risk assessment than is currently utilized within the mining industry. This dissertation describes the development of a methodology for the safe selection and/or reconfiguration of an AHS’s Safety Instrumented Systems, which follows the process prescribed by IEC 61508 but was adapted to the specific situation of mining. The derived new methodology is accomplished by developing a generic fault tree to define exposures and failure modes of an AHS. Representative scenarios simulating various mining environments and situations are utilized to define the typical exposures in an AHS deployment. Through the implementation of a systematic safety risk analysis specifically tailored for AHS, acceptable levels of risk can be achieved while reducing undue process interruption associated with safety systems. This novel analysis includes determination of the maximum tolerable risk, likelihood of an event, and the required safety systems to mitigate those risks. A theoretical determination of the safety ratings of the systems utilized in the commercial deployments was undertaken by comparing the AHS deployments to autonomous automobiles. Final analysis presents an idealized autonomous haul truck safety system to meet the demands of the model mine presented in the functional safety analysis of an AHS.
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