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, in order to characterize the issues that have been or could be addressed with the developed methodology and tools. 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 (life-cycle management, plant level operation and maintenance optimization, major component replacement ...) 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 two pilot case studies (one at the plant level, the other at the fleet level) are 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 also analyze the added value of probabilistic evaluations and of our “rolling-up” process that allows to take into account interactions between the components of the plant or between the plants. Finally, we propose a classification of issues that can be addressed with our methodology and tools and introduce some perspectives for our future work.

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