Nowadays, the risk analysis of critical systems cannot be focused only on a technical dimension. Indeed, well-known accidents in nuclear or aerospace areas underlined initiating causes also related to technical and organizational viewpoints. This led to the development of methods for risk assessment considering three main aspects on the system resources: the technical process, the operator constraining the process, and the organization constraining human actions on the process. However, only few scientific works have tried to join these methods in a unique and global approach. Thus this paper focuses on a methodology that aims to achieve the integration of the different methods in order to assess the risks probabilistically. The integration is based on (a) system knowledge structuring and (b) its unified modelling by means of Bayesian networks also supporting quantification and simulation phases. The methodology is applied to an industrial case to show its feasibility and to draw conclusions regarding the model relevance for system risk analysis. The results of the methodology can be used by decision makers to prioritize their actions when faced with potential or real risks.
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