UNIVERSITY PARK, Pa. — On July 11, Soundar Kumara, Allen E. Pearce and Allen M. Pearce Professor of Industrial Engineering at Penn State, spoke at a briefing in Washington, D.C., hosted by the House Manufacturing Caucus, co-chaired by U.S. Reps. Tim Ryan, D-Ohio, and Tom Reed, R-N.Y.
The briefing, “Artificial Intelligence and Manufacturing: The Power to Make Anything Anywhere Quickly,” focused on applying artificial intelligence and manufacturing to revolutionize, strengthen and expand the manufacturing capacity of the United States.
“Given the critical importance of strengthening manufacturing for our nation, I was honored to lend my expertise to this briefing, and it was a unique and fulfilling experience,” Kumara said.
Kumara was invited to address the caucus due to his expertise in smart manufacturing systems and his cutting-edge research in solving manufacturing and health care problems using artificial intelligence, sensor networks, data analytics and complex networks.
“From his early work on expert systems to his current focus on smart manufacturing, Soundar has been a thought leader in industrial and manufacturing engineering for many years,” said Ling Rothrock, professor and interim department head of the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering. “We are proud to have him represent Penn State at the congressional briefing as national leaders ponder the future of manufacturing.”
Each speaker was given approximately 12 minutes to explain their perspective. The panelists were Kumara; Jack Beuth, professor and mechanical engineering co-director of the NextManufacturing Center at Carnegie Mellon University; Kevin Jurrens, deputy chief of the Intelligent Systems Division Engineering Laboratory at the National Institute of Standards and Technology; Kristin Morgan, additive manufacturing lead for the NASA Marshall Space Flight Center; and Vincent C. Paquit, data analytics lead in the Manufacturing Demonstration Facility at Oak Ridge National Laboratory.
“In my talk, I focused on deep learning as well as the many challenges of dealing with large amounts of real-time data in manufacturing,” Kumara said. “These two elements will become even more challenging in the data-intensive future.”
Kumara elaborated that there is potential use of embedded sensors to collect real-time data as a product is used, which can then be utilized to redesign the product and manufacturing process.
He added, “People and machines will soon be working together synergistically, and researchers and practitioners should consider this point carefully to design and operate the smart factories of the future.”