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Today, 3-D printing generates parts used in ships, planes, vehicles and spacecraft. However, high-value and intricate parts sometimes require constant monitoring by expert specialists to get them right. Lockheed Martin and the US Office of Naval Research are exploring how to apply artificial intelligence to train robots to independently oversee and optimize 3-D printing of complex parts.
Currently, technicians spend many hours per build testing quality after fabrication, but that’s not the only waste in developing a complex part. It’s common practice to build each part compensating for the weakest section for a part and allowing more margin and mass in the rest of the structure. Lockheed Martin’s research will help machines make decisions about how to optimize structures based on previously verified analysis.
The two-year, $5.8 million contract specifically studies and will customize multi-axis robots that use laser beams to deposit material. The team will develop software models and sensor modifications for the robots to build better components, according to lockheedmartin.com.
“We will research ways machines can observe, learn and make decisions by themselves to make better parts that are more consistent, which is crucial as 3-D printed parts become more and more common,” said Brian Griffith, Lockheed Martin’s project manager. “Machines should monitor and make adjustments on their own during printing to ensure that they create the right material properties during production.”
The team is starting with the most common titanium alloy, Ti-6AI-4V, and integrating the related research with seven industry, national lab and university partners.