A System-Theoretic Fuzzy Analysis (STheFA) for systemic safety assessment

The interactions among distinct systems and components have attracted more attention recently due to safety concerns. Indeed, modern industrial plants could be regarded as complex socio-technical systems influenced by human, social, and organizational aspects. To model this level of complexity, System Theory (ST) and related frameworks, such as System-Theoretic Accident Model and Processes (STAMP) have been introduced. Despite their strengths and abilities, ST techniques are mainly qualitative and provide much information, eventually complicated to analyse and summarize. Fuzzy Set Theory (FST) and expert elicitation could be employed to cope with the former challenges. However, addressing the uncertainty arising from differences in expert opinions is necessary. To this end, this paper aims to develop a framework to conduct system safety assessments based on the integration of STAMP and FST. In this context, an improved version of the Similarity Aggregation Method is adopted to aggregate judgments. To demonstrate the application of the approach, a Natural Gas Regulating and Metering Station (NGRMS) is considered as the case study. The results show that the methodology is able to provide quantitative information by associating a level of criticality with each control action. Accordingly, managers could exploit the framework to identify priorities for directing efforts.