A Case Western Reserve University research team will lead an effort to integrate artificial intelligence (AI) and sensing to improve materials and processing in manufacturing, part of a long-term, federally funded strategy to strengthen U.S. innovation and industrial productivity.
The Case Western Reserve-led team will lead the work to integrate AI and machine-learning (ML) with data from traditional materials science and manufacturing processes and a wide range of sensors.
“The goal is to improve the ability to use AI/ML to improve the full product lifecycle—product design, material selection, process design, quality assurance, service life,” said Nick Barendt, executive director of the Institute for Smart, Secure and Connected Systems (ISSACS) at Case Western Reserve and leader of the NIST project.
“This technology roadmap—synthesized from literature reviews, interviews with researchers and industry experts and workshops—will improve the nation’s ability to design and manufacture the highest-performing and most reliable, durable and high-quality products,” he said.
Among several other partners on the project are three Case School of Engineering researchers:
Robert Gao, chair of CWRU’s Department of Mechanical and Aerospace Engineering and the Cady Staley Professor;
The research team plans to bring together “stakeholders from across the country, experts with deep insights in all aspects of design and manufacturing,” Barendt said. “This is an effort to look out over the next 20-plus years to see what technologies need to be created and the related workforce required to spur the manufacturing ecosystem across the United States.”