Prognostics of Remaining Useful Life for Aviation Structures Considering Imperfect Repairs

Maintenance plays an important role in fulfilling the goals ofthe Prognostics and Health Management (PHM) field. As ofnow, no publication has addressed the impact of imperfectrepair actions from the prognostics perspective. Imperfectrepairs introduce complexities, altering system degradationprocesses and increasing prediction uncertainties, thereby impactingthe accuracy of Remaining Useful Life (RUL) predictions.To fill this gap in the literature, the study proposes developinga robust prognostic model adaptable to post-repairoperations. The prognostic model that will be developed isstochastic since stochastic models have already proven theiradaptability to unseen test data. However, further developmentof such models is needed to deal with data on repairedsystems. In addition to that, the implementation of a BayesianExtension allows uncertainty interpretability to be consideredto account for the uncertainty coming from the repair actionitself but also from the different sources of uncertainties thathave not been studied in the field of prognostics.