Description:
This session seeks research results in which artificial intelligence (AI), big data, or data analytics have been utilized for significant advances in efficiency of manufacturing. Novel techniques in these domains that enabled industrial advances are welcome, and the focus should be on results which have been applied to industrial-scale systems in practice or in high-fidelity simulations. Submissions from industry and national labs are welcome to facilitate discussions at the industry/national lab/academic interface as it pertains to these data-based strategies for next-gen manufacturing. Discussion of policy and other practical considerations in the implementation of AI, big data, and data analytics for next-gen manufacturing are also within the scope.
Sponsor:
Next-Gen Manufacturing
Co-Sponsor(s):
Information Management and Intelligent Systems (10E), Sensors (T9), Process Development Division (12)
Chair:
Joel Paulson
Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH
Co-Chair:
Mona Bavarian
Microelectronics, University of Nebraska-Lincoln, LINCOLN, NE
Abstract Submissions Closed
See more of this Group/Topical: Topical Conference: Next-Gen Manufacturing