A case study of condition based maintenance modelling based upon the oil analysis data of marine diesel engines using stochastic filtering

This paper presents a case study of condition based maintenance modelling based on measured metal concentrations observed in oil samples of a fleet of marine diesel engines. The decision model for optimising the replacement time of the diesel engines conditional on observed measurements is derived and applied to the case discussed. We described the datasets, which were cleaned and re-organised according to the need of the research. The residual time distribution required in the decision model was formulated using a technique called stochastic filtering. Procedures for model parameter estimation are constructed and discussed in detail. The residual life model presented has been fitted to the case data, and the modelling outputs are discussed.

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