Development of a weighted probabilistic risk assessment method for offshore engineering systems using fuzzy rule-based Bayesian reasoning approach

Abstract

This study presents a new safety methodology that is capable of transforming qualitative expert judgement into probabilistic risk outcomes for offshore engineering systems. In the framework, fuzzy set theory is applied to describe variables. Fuzzy data of each input is expressed in terms of the belief degree format representing the extent to which the fuzzy data belongs to the associated fuzzy set. Such data is subsequently combined to derive appropriate consequents using a fuzzy rule approach considering the weights of each input. The information generated in the antecedent and consequent of each rule are then synthesized to reach the fuzzy conclusions using the Bayesian reasoning approach. Such fuzzy conclusions are defuzzified and consequently transformed into the probabilistic nature. The framework is validated using two axioms and demonstrated by a risk study of the propulsion malfunction of an offshore Floating Production, Storage and Offloading (FPSO) during tandem offloading operations. The results are consistent with the axioms since the outcomes are sensitive to the minor alterations of input data and weights. It is concluded that the new approach produces reasonable results considering input weights and the logicality between inputs and outputs without losing too much useful information in the inference process.