Uncertainty Analysis of Method-Based Operating Event Groups Ranking

Abstract

Safe operation and industrial improvements are coming from the technology development and operational experience (OE) feedback. A long life span for many industrial facilities makes OE very important. Proper assessment and understanding of OE remains a challenge because of organization system relations, complexity, and number of OE events acquired. One way to improve OE events understanding is to focus their investigation and analyze in detail the most important. The OE ranking method is developed to select the most important events based on the basic event parameters and the analytical hierarchy process applied at the level of event groups. This paper investigates further how uncertainty in the model affects ranking results. An analysis was performed on the set of the two databases from the 20 years of nuclear power plants in France and Germany. From all uncertainties the presented analysis selected ranking indexes as the most relevant for consideration. Here the presented analysis of uncertainty clearly shows that considering uncertainty is important for all results, especially for event groups ranked closely and next to the most important one. Together with the previously performed sensitivity analysis, uncertainty assessment provides additional insights and a better judgment of the event groups’ importance in further detailed investigation.