A machine learning tool is being developed by Purdue University to increase the accuracy in additive manufacturing. The resulting research could increase precision and reduce testing time.
“We’re really taking a giant leap and working on the future of manufacturing,” said Arman Sabbaghi, an assistant professor of statistics in Purdue’s College of Science, who led the research team at Purdue with support from the National Science Foundation.
“We have developed automated machine learning technology to help improve additive manufacturing. This kind of innovation is heading on the path to essentially allowing anyone to be a manufacturer.” Additive manufacturing like 3D printing has changed the way many products are made and assembled.
But an ongoing issue has always been accuracy, especially when it comes to parts that need to fit together with extreme precision. The new technology addresses this downfall.