Fuzzy Logic for Process Safety Analysis

摘要

Fuzzy logic deals with uncertainty and imprecision, and is an efficient tool for problems where knowledge uncertainty may occur. Such situations arise frequently in a quantitative fault and event tree analysis in safety and risk assessment of different processes. The lack of detailed data on failure rates, uncertainties in available data, imprecision and vagueness may lead to uncertainty in results, thus producing an underestimated or overestimated process risk level. This paper explores the application of the fuzzy sets theory for basic tools used in process safety analysis like fault and event tree which can be further used in the "bow-tie approach" for accident scenario risk assessment. In the conventional approach of fault and event tree, the input variables are treated as exact values and exact outcome data are received by an appropriate mathematical approach. In the fuzzy sets approach, all variables are replaced by fuzzy sets in the process of fuzzification and subsequently using fuzzy arithmetic, fuzzy probability of the top event for fault tree, and fuzzy outcome frequency for event tree are calculated. A single value for each of the outcome event result is obtained using one of the defuzzification methods. A typical case study comprising a fault tree for rupture of the isobutane storage tank and the event tree for its consequence is performed and a comparison between the classical approach and fuzzy approach is made.