Reference : Predictive Maintenance of Technical Faults in Aircraft
Scientific congresses and symposiums : Unpublished conference/Abstract
Business & economic sciences : Quantitative methods in economics & management
http://hdl.handle.net/2268/244884
Predictive Maintenance of Technical Faults in Aircraft
English
Peters, Florian mailto [Université de Liège - ULiège > HEC Liège : UER > UER Opérations >]
Aerts, Stéphanie mailto [Université de Liège - ULiège > HEC Liège : UER > UER Opérations >]
Schyns, Michael mailto [Université de Liège - ULiège > HEC Liège : UER > UER Opérations : Informatique de gestion >]
30-Jan-2020
No
International
34th Annual Conference of the Belgian Operational Research Society
from 30-01-2020 to 31-01-2020
Lille
France
[en] predictive maintenance ; machine learning ; operational research
[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.
Researchers
http://hdl.handle.net/2268/244884

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