Project number
19030
Organization
L3Harris
Academic year
2019-2020
Team 19030
Predictive Maintenance Trend Monitoring for Avionics Equipment
Project goal
Evaluate historical fault information recorded for NXT transponders, and apply Artificial Intelligence (AI) on the fault data set to predict a potential future failure of the transponder.
In the aviation industry, any unplanned maintenance events negatively impact airline operations and their customers. L3Harris is looking to improve their product offering for their airline customers.
The software package is designed to analyze fault data sets specific to the NXT series transponder. The software packages includes a maintenance sorting prediction algorithm that uses gradient boosting to generate maintenance schedules of avionic transponders. The maintenance schedule output from the software will lead to reduced costs for the customer and improve L3Harris’s product offering.
Predictive Maintenance Trend Monitoring for Avionics Equipment
Project goal
Evaluate historical fault information recorded for NXT transponders, and apply Artificial Intelligence (AI) on the fault data set to predict a potential future failure of the transponder.
In the aviation industry, any unplanned maintenance events negatively impact airline operations and their customers. L3Harris is looking to improve their product offering for their airline customers.
The software package is designed to analyze fault data sets specific to the NXT series transponder. The software packages includes a maintenance sorting prediction algorithm that uses gradient boosting to generate maintenance schedules of avionic transponders. The maintenance schedule output from the software will lead to reduced costs for the customer and improve L3Harris’s product offering.