Up in the Cloud – Next Steps of Customer Support Enabled by Machine Learning for AviationGrace Hopper Stage
Facing up to the challenge of digitization in aviation, a micro-enterprise, a SME and a university evolved an innovative decision support system. The startup DATA|bility developed data-based diagnosis and prognosis analyses using machine learning in combination with conventional engineering. In cooperation with justaero, a predictive maintenance application for aircraft engines based on a cloud platform has been implemented. The application's outcome contains the prediction of future health and an indication of the forecast uncertainty. These results are now combined with the process management required for maintenance. Service processes can thus be controlled automatically, processed and run through in a traceable manner. With this, need for actions can be identified, recommendations can be given at an early stage and maintenance processes can be optimized. The presentation discusses technical and implementation-related aspects of an AI framework in industrial environment. Finally, operational cost benefits are lighted.
Cédric Villani, Mathematician - member of the Academy of Sciences - 1st vice-president of the Parliamentary Office For Scientific and Technological Assessment (OPECST) – Member of Parliament Fields Medal,