Abstract

The long term management of a production asset raises several major issues among which rank the technical management of the plant, its economics and the fleet level perspective one has to adopt. Decision makers are therefore faced with the need to define long term policies (up to the end of asset operation) which take into account multiple criteria including safety (which is paramount) and performance. In this context, EDF “PWR Durability I & II” research projects have consecutively been launched, since 2001, at EDF – Research & Development in order to develop methods and tools for EDF fleet. The aim of this paper is: • to summarize and analyze the research work that has been performed by EDF – R&D in the field of decision making for nuclear power plant maintenance and operation during the past seven year; • to highlight the strong and weak points of the developed methodology and tools and to identify the research work needed in order to ensure their use by EDF decision makers; • to introduce and illustrate our last development based on the use of an “adaptative” man/machine user interface in order to allows technical/strategic experts and decision makers to consult the useful pieces of knowledge in a context dependent way and, thus, facilitate the validation of the knowledge-base content and the analysis of the processed results. As a result, in this paper, we first remind the reader of the EDF overall methodology for asset management and its adaptations to plant-level life cycle management and to fleet-level component major replacement or capital investment management. We then focus on the three software tools that implement this methodology in order to allow decision makers, in several different contexts to define, evaluate and analyze long term plant operation and maintenance policies, major component replacement policies and capital investment strategies. We also show how the methodology and the software tools were used, from 2003 to 2007, on several pilot case studies. Examples of technical and economic results obtained for plant level pilot case study is quickly described as well as the kinds of conclusions one can draw from them in order to help decision makers evaluate and analyze long term asset management strategies or compare different plants. We then present the opinion of EDF’s decision makers about the developedmethodology and tools — and their use — and our understanding of their feedback. Lastly, we illustrate, using examples of technical and economic knowledge, data and results obtained from our previous pilot case studies, how the concept of an “adaptative” man/machine user interface could be used in order to facilitate the mastering of the methodology and tools’ complexity and to support decision makers’ evaluation and analysis of long term asset management strategies.

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