Abstract

Pro-active investment into process risk mitigation can impact organizational business performance positively by allowing avoidance of future accidents. While several approaches have been reported in the literature, there is a need for a plant-wide safety investment optimization (SIO) framework in order to mitigate all identified, credible accident scenarios. The present work includes both individual and societal risk as metrics simultaneously for decision-making for optimal risk reduction. The overall framework satisfies three requirements: ensuring compliance with national process risk acceptance regulations; procurement of insurance cover for specific risks, and investment in selective residual risks, not attended to in the previous phases, so as to secure financial benefits of reduced asset and human losses from possible future accidents. An example case study based on a process plant is presented in way of illustrating the application of the SIO framework. The first layer of quantitative risk analysis computations indicates the public IR exceeds the tolerable limit, but societal risk (SR) compliance exists. The algorithm to enable compliance for SR by mitigating the maximum cumulative accident frequency and/or fatality is presented. Next, based on expected annualized loss, we illustrate the choice of an insurance cover for mitigating the residual risks that may cause significant property losses. Thereafter, based on the availability of additional safety budget, a cost-benefit analysis for safeguards for mitigating the still remaining risks is exemplified. This leads to the identification of the combination of safeguards that secure the maximum possible benefit to the organization. This step, in effect, allows the organization to progress beyond the minimal requirement of regulatory conformity. The cost-benefit analysis demonstrated can potentially constitute a viable business decision as it may allow an organization to secure the best return on focused investments on safeguards.

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