Lockheed Martin and the Office of US Naval Research are exploring how to apply artificial intelligence to train robots to independently oversee and optimize 3-D printing of complex parts.
Soon robots like this could make decisions on how to build more effective 3-D printed parts. This multi-axis printer uses laser beams to deposit material and make metal components, which could be important resources for people far from supply chains.
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.
"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."
Researchers will apply machine learning techniques to additive manufacturing so variables can be monitored and controlled by the robot during fabrication.
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 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.