Computer Vision for Predictive Maintenance (PMx)

To improve military aircraft readiness and reduce costs by minimizing downtime for unscheduled maintenance.  The problem is the lack of ability to detect the early symptoms of an impending breakdown and prevent it, by doing the right maintenance on exactly the right component at exactly the right time. By enabling the capability for early detection, the amount of effort required to perform unnecessary preventive maintenance is reduced, allowing staff to focus their efforts on the most important needs for maintaining highly operational aircraft. Application of computer vision, using advanced machine learning algorithms, to Predictive Maintenance (PMx) uses Artificial Intelligence (AI) to analyze both analyze both real-time and historical data. Delta Airlines has already started using basic AI to perform PMx on its A320 and A330 fleet, leading them to double the number of days without a cancellation between 2013 to 2017. The Air Force is using non-computer vision AI techniques or Conditions-Based Maintenance Plus (CBM+) to perform PMx, such as data analysis and vibration sensors mounted on fixed-wing aircraft.  The Air Force is looking to predict more accurate maintenance needs on C-5M fleet, KC-135Rs, B-1, E-3, RC-135, OC-135, F-16, and F-35.