Predicting condition based on oil analysis – A case study

The paper presents and discusses a model for condition monitoring. Using data from the oil in the Diesel engines of a fleet of urban buses, it studies the evolution of degradation and develops a predictive maintenance policy for oil replacement. Based on the analysis of the oil condition, the intervals of oil replacement can be expanded, allowing increased availability. The paper links time series forecasting with the statistical behavior of some oil effluents, like soot. This exercise can be expanded to include other variables, and the model has the potential to be applied to other physical assets to achieve the best availability based on a condition monitoring policy.