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Navy Uses AI, Data Analytics to Address Aircraft Readiness Issues

2 mins read

The U.S. Navy is working to improve the readiness of its aircraft fleet using artificial intelligence, data analytics and the concept of reliability control boards, Federal News Network reported Thursday.

The service is using AI algorithms to process aircraft maintenance data and generate insights from the collected data. The Naval Air Warfare Center Aircraft Division (NAWCAD), for instance, is using the Army-developed Composite Learning Algorithm for Records Evaluation system to facilitate data processing.

“So the artificial intelligence solution looks at relationships in the data and what’s documented to say, ‘Hey, when you said [the problem is] this, it’s actually this. And that helps us score and correct all that maintenance data so we don’t have some of the inaccuracies that get perpetuated through the system,” said Jason Thomas, principal analyst at NAWCAD’s data analytics team.

Robert Smith, head of the reliability control board data analytics team at NAWCAD, told the network in an interview about the Failure Reporting and Corrective Action System and how it could help advance predictive maintenance using data.

“It will contain all the data behind a degrader, including what we’ve identified with CLARE,” Smith said of the system. “It will actually provide us with the ability to optimize our maintenance to predict failures before they occur. It will give us the confidence that the time on wing for a particular component is X. And before we get to X, and that aircraft is inducted for some type of maintenance, we will have the confidence to remove that component and replace it before it fails.”