Risk measures constituting a risk metrics which enables improved decision making: Value-at-Risk

In this work, a novel approach is proposed for expressing the risks of process plants consisting of a large number of scenarios, in the form of a risk metrics of leading indicators to prevent potential high profile industry accidents. The methodology includes: 1) risk estimation of a portfolio by CPQRA (or QRA), 2) monetization of the tangible risks with the inclusion of the lost time of production, 3) estimation of the maximum portfolio loss using Value-at-Risk approach, 4) inclusion of intangible risks using FN-curve and, 5) generation of F$-curve of tangible risks. The proposed methodology can particularly help in understanding the stakes at risk by performing the overall cost-benefit analysis, for identifying the most risky scenarios and identifying critical equipments to enable better risk-informed decision making in order to adopt appropriate risk mitigation measures. This work establishes the groundwork for developing measures for understanding and comparing the large number of risk values derived from QRA studies for large portfolios. It will aid in less subjective decision making as it enables the decision maker to choose the most preferred portfolio option among alternatives. Decisions made with the accurate understanding of the consequences of risks can significantly reduce potential work-related fatalities, property losses and save millions of dollars.