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Abstract

 
 
 Life extension has been an important and highly discussed issue in nuclear and aviation industries for a long time and it has recently attracted a considerable attention in subsea oil and gas industry. Decision regarding life extension is primarily based on the remaining useful life. The paper explains the technical health and the other factors that influence the remaining useful life. Degradation mechanisms and the lifetime models are discussed, highlighting the limitations of classical approach and the need for Bayesian approach. A model to predict remaining useful life needs to have a capability of handling heterogeneous combination of requirements like degradation modelling, uncertain sensor data handling, and incorporating expert opinion. The paper explores the suitability of using Bayesian Belief Network as a modelling tool for such prediction in subsea oil and gas industry.
 
 
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