If it ain't broke, don't fix it: Optimizing the predictive aircraft maintenance schedule with Remaining Useful Life prognostics

Predictive aircraft maintenance is a maintenance strategy that aims to reduce the number of failures, the number of inspections, the number of maintenance tasks and the aircraft maintenance costs. Aircraft are equipped with health monitoring systems, where sensors continuously measure the condition of the aircraft components. In predictive maintenance, these sensor measurements are used to estimate the time left until the failure of these components, called the Remaining Useful Life (RUL). These RUL prognostics are subsequently used to optimize the aircraft maintenance schedule. There are several challenges that complicate the implementation of predictive aircraft maintenance in practice. In this thesis, the threemain challenges are addressed.