Decision-making in asset management under regulatory constraints

Abstract

Asset management (AsM) policies are influenced by various factors (strategic, technical/technological, economic, organizational, regulatory/legal, safety, markets, competition, etc.). Therefore, the AsM decision-making process should take into account relevant factors for balancing risks, performance, costs, and benefits. Modern organizations use various quantitative models to assess related risks as well as performance, costs and benefits. The results of these models are important input for the overall AsM decision-making process. Decision-makers occasionally give an overwhelming importance to numerical results. Ignoring the limitations of the quantitative risk models used, this practice may be misleading and result in potentially inappropriate decisions. A holistic Risk-Informed Decision-Making (RIDM) process developed for AsM is described in this paper. This process is adapted in the presented case study to analyze possible modification strategies for a nuclear power plant’s emergency core cooling system (ECCS). During an operators’ training preparation, a design weakness has been discovered in the ECCS, which called for major modifications to the system. The Probabilistic Risk Assessment (PRA) technique has been used to calculate the risk levels of various analyzed options. Nevertheless, the results of the PRA alone were insufficient to demonstrate regulatory compliance. The RIDM process has been used to provide the fundamental insights necessary to obtain regulatory approval for the proposed modification strategy.