MOUNTAIN VIEW, Calif. – Companies are cautiously applying artificial intelligence to satellite manufacturing.
For example, Blue Canyon Technologies wants to better understand how AI can contribute to manufacturing without compromising cybersecurity.
“When you’re trying to teach an AI machine, where does the data go,” Blue Canyon Technologies general manager Chris Winslet asked at the Satellite Innovation Conference here. “There are also concerns about bringing in data from external applications. Where are they coming from?”
Still, AI can aid Blue Canyon, a subsidiary of Raytheon Technologies, in its engineering design process.
“We want to be able to use AI to turn large amounts of data into information,” says Winslet. That way, people can spend their time making decisions instead of looking through spreadsheets, he added.
kongsberg nano avionics
Karolis Senvaitis, director of engineering operations at Kongsberg NanoAvionics, shares Winslett’s concerns about AI models.
“How can I trust what I’m getting? What’s the source?” Senvaitis asked. “If you’re tabulating results, are you getting the results you want?”
Until these questions are clearly answered, “it’s hard to imagine this being directly integrated into manufacturing or testing,” Senvaitis said.
However, he agreed that AI can help collect and analyze large datasets.
Makina Lab
For Machina Labs, a Los Angeles startup developing robotic technology for metal tool manufacturing, the origin of the data doesn’t really matter. machina Labs generates its own data rather than ingesting it from myriad sources and suppliers.
“Many of our processes incorporate design engineers and process development engineers, who essentially interpret this large amount of data that is generated by our molding robots,” says Machina Labs Production said John Borrego, Vice President. “Using load and position sensors and highly accurate scanning software and devices, we can determine if a part meets our requirements.”
Data from sensors and devices is stored in a secure cloud.
“We have only scratched the surface because we now have concrete data that we can use and leverage to optimize our processes and reduce all kinds of quality defects in future parts,” Borrego said. I am.
