This paper offers a comprehensive return of experience on the deployment of big data technologies enabling various descriptive and predictive analytics within the helicopter industry. It shows how these technologies can efficiently be employed to allow storing and processing the large quantity of flight data which are made available, and consequently how they offer additional analytics capabilities to the analysts. In order to demonstrate these benefits, the paper presents applications concerning statistical fleet data analysis and predictive maintenance. Concluding remarks are then given with particular attention to limitations of distributed big data technologies and challenges regarding their adoption within the industry.
Helicopter big data processing and predictive analytics: feedback and perspectives / Mechouche, Ammar; Daouayry, Nassia; Camerini, Valerio. - 2:(2019), pp. 1022-1028. (Intervento presentato al convegno 45th European rotorcraft forum 2019 (ERF) tenutosi a Warsaw, Polony).
Helicopter big data processing and predictive analytics: feedback and perspectives
Camerini, ValerioMembro del Collaboration Group
2019
Abstract
This paper offers a comprehensive return of experience on the deployment of big data technologies enabling various descriptive and predictive analytics within the helicopter industry. It shows how these technologies can efficiently be employed to allow storing and processing the large quantity of flight data which are made available, and consequently how they offer additional analytics capabilities to the analysts. In order to demonstrate these benefits, the paper presents applications concerning statistical fleet data analysis and predictive maintenance. Concluding remarks are then given with particular attention to limitations of distributed big data technologies and challenges regarding their adoption within the industry.File | Dimensione | Formato | |
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Mechouche_Helicopter-big-data_2019.pdf
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