Bayesian nets for life cycle cost forecasting

Plant and system operators are looking for reliable products meeting high technical requirements while providing maximum economic benefit throughout the life cycle. Calculating life cycle costs different operating conditions have to be considered to provide reliable decision making assistance. If data for a direct probability measurement may not be available, expert knowledge needs to be considered. The model present enables a combination of expert knowledge and collected lifetime data to be used for estimating product operational costs. Modelling costs this way, the plausibility of a given statement can be updated in the light of new information to produce a more accurate cost estimation.