predictive maintenance; machine learning; operational research
Abstract :
[en] A key issue for handlers in the air cargo industry is arrival delays due to aircraft maintenance. This work focuses on a particular delay caused by technical faults called technical delays. Using real data from a cargo handler company, different classification models that can predict technical delay occurrence are compared. A new decision tree extension is also proposed based on a study by Hoffait & Schyns (2017). The final results present a good starting point for future research.
