Predictive modelling for airline technical operations

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Published Sep 4, 2023
Dimitri Reiswich

Abstract

The digital platform AVIATAR leverages aircraft and maintenance data as well as advanced algorithms to optimize technical operations. Optimization is achieved by utilizing predictive maintenance algorithms which lead to a reduction of costs and operational incidences. The rise of AI algorithms combined with an increase of the available data to feed those algorithms provides both an opportunity as well as challenge to the traditional approaches which were in use in the aviation industry for decades. We demonstrate how AVIATAR’s data science team develops state of the art predictive maintenance models by combining advanced statistical models and AI with the unique engineering know how of Lufthansa Technik. We will show the immense value of full flight data in order to achieve this and provide an outlook into the potential future role of algorithms in the aviation industry.    
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Keywords

airline operations, agile software development, decision support, Predictive health analytics, health management

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Section
Special Session Papers