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 paper we first remind the reader of the EDF three-level methodology for asset management. As introduced in PVP 2003 and PVP 2004, this methodology addresses the component/technical level (how to safely operate daily and invest for the future), the plant level (how to translate technical decisions into plant-wide consequences including economic performance) and the fleet level (how to manage a large number of similar assets). We then focus on the software tool that implements this methodology in order to allow decision makers to define, evaluate and analyze long term plant operation and maintenance policies. Lastly we show how the methodology and the software tool were used on a pilot case study. The technical and economic results obtained at the plant level are described as well as the conclusions one can draw from them in order to help decision makers evaluate and analyze long term asset management strategies.

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 (until the end of the life of the asset) which take into account multiple criteria including safety (which is paramount) and performance. In this paper we describe the French context where EDF (Electricite´ de France) is both Plant Owner and Operator of a fleet of 58 PWRs. We introduce a three-level methodology for asset management: the component / technical level (how to safely operate daily and invest for the future), the plant level (how to translate technical decisions into plant-wide consequences including economic performance) and the fleet level (how to manage a large number of similar assets). We then focus on the theoretical and practical links one can draw between the component level and the plant level. We describe several plant-wide indicators that are used to assess the value of the asset and we show how they can be inferred from the component-level technical and economic assessment (long-term equipment reliability, maintenance strategies, ...) by « rolling up » component level plans into a plant-wide decision process while taking into account the various sources of uncertainty associated with this assessment. We finally exemplify how this process could be applied to the life management of nuclear assets. To conclude, it appears asset management can be a major means for assessing and enhancing the long term value of a production unit while meeting everyday constraints.

Exceptional maintenance tasks are maintenance tasks that are unlikely to be carried out more than once or twice over the life of a Nuclear Power Plant. Such a task may be preventive or corrective toward a wearing mechanism that may lead to a failure with a low probability and high potential consequences. Exceptional maintenance tasks are often characterized by a long lead-time and a high cost, that’s why in addition to the classic maintenance issue on choosing between preventive or corrective tasks, it is very important for exceptional maintenance to evaluate the best stock level. This paper describes the methodology and tools that are being developed at EDF and presents a case study that has been carried out.

The life management of a nuclear power plant raises several major issues amongst which ranks the aging management of the key components of the plant, both from a technical and an economic point of view. Decision-makers are thus faced with the need to define the best strategy in order to achieve the best possible performance which requires both a very precise modeling of the plant and a detailed analysis of all risks potentially incurred.In this paper, we wish to provide the reader with an overview of how advanced expert elicitation techniques can help identify, structure, quantify and feed sensitive data into a risk-based information system which can then be used for risk-based asset management evaluation.First we focus on the way knowledge management techniques allow EDF to structure and collect life-cycle management data into knowledge-based information systems. The elicitation of component experts is key, particularly in order to get technical information on the future behavior of the component ("anticipation" of whatever events may occur on the plant).We then detail how expert elicitations allow to quantify the probabilities of occurrence of the events: whether there is feedback data, models or not, expert opinion has to be taken into account and mixed, for instance with Bayesian procedures, to this information.Lastly we describe how the information elicited from experts can help top level decision makers get a transverse, long term view on how life management investment strategy translates into plant availability, avoided costs and improved component durability. INTRODUCTIONThe management of a production asset, especially with a long-term goal to achieving an optimum lifetime, 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 (until the end of the life of the asset), which take into account multiple criteria including safety (which is paramount) and performance.In this paper, we first remind the reader of the EDF three-level methodology for nuclear asset management, as introduced in PVP 2003 [1] and PVP 2004 [2]. The knowledge management techniques used to support the expert elicitation process (in order to anticipate whatever could occur to the plant) and which facilitate the structuring and the processing of the acquired knowledge are then presented. Emphasis is given to the methodology developed for the quantification of the events (i.e. their probabilities of occurrence, their consequences in terms of availability) and of the mitigation actions (i.e. their cost, duration and impacts on events' occurrences). Lastly, we describe how the methodology, the information elicited from experts and their implementation in a software tool can be used in order to process technical and economic indicators obtained at the plant level as well as the conclusions top level decision makers can draw from them in order to evaluate and analyz...

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) that take into account multiple criteria including safety (which is paramount) and performance. In this paper we first remind the reader of the EDF three-level methodology for asset management. As introduced in PVP 2003 and PVP 2004, this methodology addresses the component/technical level (how to safely operate daily and invest for the future), the plant level (how to translate technical decisions into plant-wide consequences including economic performance), and the fleet level (how to manage a large number of similar assets). We then focus on the software tool that implements this methodology in order to allow decision makers to define, evaluate, and analyze long term plant operation and maintenance policies. Lastly we show how the methodology and the software tool were used on a pilot case study. The technical and economic results obtained at the plant level are described as well as the conclusions one can draw from them in order to help decision makers evaluate and analyze long term asset management strategies.