Modelling Non-Deterministic Causal Mechanisms involving Resilience in Risk Analysis. Issue 12 (2016)

• Record Type: Journal Article
• Authors: De Galizia, A.; Simon, C.; Weber, P.; Iung, B.; Duval, C.; Serdet, E
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 12(2016)
• Page Start: 325
• Page End: 330
• Publication Date: 2016
• Subjects: Resilience -- Canonical models -- Bayesian networks -- Risk analysis -- Sociotechnical systems; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.07.625
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In risk analysis, deterministic propagation of uncertainty as in fault trees models is not sufficient for sociotechnical systems. In recent years some approaches have been developed as Integrated Risk Analysis (IRA) to address different risks causalities linking human, organizational, technical and environmental factors in a unified framework. This framework relies on a Performance Shaping Factors (PSF) based model and constitutes an alternative approach different from that currently adopted at EDF for PSA (Probabilistic Safety Assessment) purposes. The IRA method is supported by Bayesian Networks (BNs) to model non-deterministic causal patterns among system variables. Thus, this paper aims to investigate on how to consider resilient influences in causal probabilistic modelling. In particular, it is focused on how to consider mitigation mechanisms in quantifying organizational influences on a human activity in sociotechnical systems. It leads to propose a formalism to represent a mitigation mechanism in causal interactions between pathogenic and resilient influences in a probabilistic model. Finally, the feasibility of our proposal is shown on an illustrative case declined in the framework of the IRA approach.