“We can do that inspection quicker, we can do it with better granularity and we can do it repetitively,” he continued. “The way the aircraft tracks and how we do that inspection, the next time that specific aircraft comes in, we can run that exact same track and thereby do a corollary on the digital printout from the first time we did it to the second time we did it. And thereby we can pinpoint [issues] in a manner that sometimes the human eye cannot see,” allowing for more accurate, affordable and safe inspections, which in turn allows “aircraft to get back out in terms of mission readiness better than we've ever done before.”

"A groundbreaking drone program has been successfully tested at Dover Air Force Base, offering a safer and more efficient method for inspecting the towering T-tail of a C-5 M Super Galaxy aircraft, which reaches a height of 65 feet..."We’re always looking for the best way to do things here," Ken Jones, 436th Mission Generation Group process improvement and innovation manager noted. "It’s a win-win situation to be able to do it better and safer."

“There are 34 points of interest, and that information is fed automatically back in another system within 10 seconds,” said Ken Jones, 436th Mission Generation Group process improvement and innovation manager. “The idea is to keep us from having to put Airmen in harm’s way up on the wings and tail.” The new program also saves time. Traditional inspections that require personnel to use a harness can take hours, said Jones. The drone completed its job in about 10 minutes.

"After the inspection was complete, the drone slowly made its way back to the ground, taking just 10 to 15 minutes to scan a quarter of the almost 250-ft long aircraft — a timeline that is significantly less than it would take a safety check from a human and proved to be more accurate"

While Boeing and Near Earth Autonomy have worked together for months previously, assessing and digitally archiving the status of Boeing C-17 cargo planes at Joint Base Pearl Harbor-Hickam in Hawaii, the work on the East Coast marks “a big moment” for the AAI initiative, according to Belanger.

The Air Force tests out new tech to scan aircraft for potential damage and wear and tear. Can drones do the job better than humans?

Boeing engineers have pushed the envelope – and caught the customer’s attention – with the next step in autonomous aircraft inspections, an automatic damage detection software. The software, called ADDS for short, is paving the way for safer and more efficient C-17 maintenance processes.

"You’ll be able to pull up a tail number, click anywhere on the 3D model of that aircraft, and see a history of images of that exact part you clicked on,” said Alli Locher, Near Earth Autonomy senior product manager. “And, you’ll be able to do that from anywhere in the world.” By seamlessly integrating human expertise with  powerful autonomy, the future of aircraft inspection, maintenance and transportation is safer, faster  and even more reliable.

The equipment has been certified to meet requirements of the National Defense Authorization Act (NDAA), ensuring components have been made in the U.S. or U.S.-friendly countries. NDAA compliance is necessary to work on U.S. defense aircraft, and no other current drone offer meets these requirements.

“The Autonomous Aircraft Inspection (AAI) pictures that are being taken and the data being captured and analyzed is immensely valuable so that’s the big strategic sustainment value of what we’re doing–and the operational impact of keeping young airmen off the tail, or when they go up to the tail they know what they’re looking for.”

"We’re trying to upskill that human inspection, so when they do go on the C-17 tail, they’re not guessing. They know exactly what to bring, they know exactly what to expect. And in the end, they’re going to get the aircraft out of the hangar, back to the crews, back into the fight much, much faster."

Whereas traditional exterior examinations can take hours and still miss tiny details, the drone-centric approach, fueled by pattern recognition and 3D models, is far quicker and feeds verified observations to a secure repository, officials said.