AI applied to production engineering

ATENEA is a project hosted by Airbus D&S with financial support from the CDTI Interconnecta program, whose aim is to introduce machine learning and natural language processing to streamline certain manufacturing processes in their production plants.
UCA Datalab is responsible for a work package within ATENEA whose goal is to develop predictive algorithms for potential problems (Non-Confirmity Sheets) in the Fan Cowls of Airbus A-320 produced at the Airbus-CBC factory (Bahía de Cádiz). The models use many features gathered from different sources (personnel databases, sensors, machine logs, etc.) whose ETL and preprocessing has been carried out as part of the project.
UCA Datalab has also designed computer vision models to automate the inspection of potentially defective areas in these Fan Cowls, by examining the images obtained from the Ultrasound Inspection performed by a robotic arm.

Contract art.83 between Airbus S.A & UCA
Team: 10 researchers
Duration: mar 2019 – mar 2020
Quantity: 90.000€
IP: D. Gómez-Ullate
Ref: CDTI Interconnecta (ATENEA)