A Bayesian network-based integrated risk analysis approach for industrial systems: application to heat sink system and prospects development

In less than a decade, the European context on industrial risk management has evolved in order to propose frameworks to improve knowledge of both hazardous events and systemic analysis. Some frameworks are addressing more precisely socio-technical systems, considered as complex systems, operating under environmental constraints and for which multiple risks exist. Indeed, the physical and regulatory environment strongly influence the different stakes of a socio-technical system, mainly its availability, but also its safety. Nevertheless as these systems cannot be studied as a set of independent sub-systems owing to complexity, the conventional risk analysis is not applicable to them. More integrated risk analysis development is required, globally covering all the risks in a same view, taking into account system models (e.g. functional and organizational), system life cycle phase, system environment, the potential role of maintenance, and the human actions. In relation to this context, Electricité De France (EDF), which is managing socio-technical systems dedicated to energy production, took the opportunity to contribute to this issue. Thus, this article is defending a ‘system thinking’-based integrated risk analysis approach. Integrated risk analysis covers different disciplines (i.e. dependability, human reliability, and organizational analysis) and is designed for developing methods and appropriate tools in order to support innovative risks analysis of such systems. This approach is justified with regard to other risk analysis approaches in order to highlight the benefits of an integrated approach compared with the usual studies that are specific (technical or environmental or human centred). These main concepts and principles, and the adequacy of Bayesian networks to integrated risk analysis models, are demonstrated by applying them to an industrial case that is a sub-set of an EDF energy power plant (a heat sink). Finally, based on the results of sensitivity studies performed to ensure the robustness of Bayesian network-based integrated risk analysis models, major prospects development and ways to tackle them are identified mainly related to the robustness of risk assessment, the modelling of the human barrier, and the resilient aspects of the organization.