Tackling uncertainty in safety risk analysis in process systems: The case of gas pressure reduction stations

Abstract

Industrial plants are subjected to very dangerous events. Therefore, it is very essential to carry out an efficient risk and safety analysis. In classical applications, risk analysis treats event probabilities as certain data, while there is much penurious knowledge and uncertainty in generic failure data that will lead to biased and inconsistent alternative estimates. Then, in order to achieve a better fitting with systems condition, uncertainty needs to be considered. One of the most usual analytical methods that have been widely applied in the field of risk analysis is the technic of failure mode and effects analysis (FMEA). The usage of this method is in identifying and abolishing the multiple failure modes in various phases of system, from the product design to production of the industries system operation. To solve the shortcomings in the traditional FMEA method, we propose an innovative approach consisted of Dempster Shafer evidence theory (DST) and FMEA to provide a more efficient way for failure mode identification and prioritization. The proposed methodology in this study can well capture imprecise opinions and can prioritize failure modes considering uncertainties. City Gate Station (CGS) of Yazd Province was used to prove the practical application and validity of the proposed risk analysis methodology. Results showed that the proposed method is effective and practical for real engineering purposes.