Assessing the technical condition and remaining useful life of aging equipment is crucial for the life extension of O&G facilities. In order to perform a reliable assessment, models describing the degradation of the equipment are necessary. However, the use of accurate physical models for this purpose may be challenging. Some reasons are that the equipment can be exposed to various degradation mechanisms, which may be influenced by different operating conditions, and that the operational data may be scarce. This paper presents a systematic approach for modelling different degradation mechanisms, assessing the technical condition of a component, and quantifying the expected remaining useful life. The quantification is performed using a Bayesian network. Finally, the application of the proposed model is illustrated with the analysis of a fire water pump.

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