Aircraft Maintenance Scheduling Using Engine Sensor Data
An aircraft maintenance scheduling optimization model using data-driven turbofan engine RUL prognostics
A.P. Reijns (TU Delft - Aerospace Engineering)
M. Mitici – Mentor (TU Delft - Air Transport & Operations)
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Abstract
This research is relevant to any airline that wants to innovate its maintenance scheduling process bymaking use of data-driven techniques. Shifting towards a data-driven organization holds the potential benefits of increased scheduling efficiency and profits, while decreasing the time required to schedule maintenance on a daily basis. Optimizing the airline maintenance process will lead to lower aircraft downtime and less wasted life of aircraft components. This will result in a higher passenger satisfactory, a more sustainable way of operation and a higher profit for the airline. All of these aspects stress the importance of optimizing the airline maintenance scheduling process, both from a economic and societal point of view.