Multi-Physics Sensing and Machine Learning for Smart Manufacturing
Prof. Robert Gao, Case Western Reserve University
3:30 p.m., November 16, 2021 | Zoom
As the fundamental building blocks of Industry 4.0, sensing and artificial intelligence play a critical role in advancing the state of manufacturing. The ability in acquiring data, in-situ, and extracting clues from the data to guide the action of assistive infrastructures, such as robots, is essential to enhancing process control and production planning.
This seminar highlights research on manufacturing process-embedded sensing and machine learning for smart manufacturing, illustrated in two examples. The first example highlights the design and experimental evaluation of a multi-physics sensor with acoustic-based wireless data transmission capability for the online quantification of melt temperature, pressure, velocity, and viscosity within an injection mold. The second example illustrates machine learning methods for the recognition of current and prediction of future actions of human operators during assembly operations, which are the prerequisites for human-robot collaborative assembly. The presentation highlights the potential of use-inspired basic research in advancing the state of manufacturing.
Robert Gao is the Cady Staley Professor of Engineering and department chair of Mechanical and Aerospace Engineering at Case Western Reserve University in Cleveland, Ohio. Since receiving his Ph.D. degree from the Technical University of Berlin, Germany in 1991, he has been working on physics-based sensing methods, stochastic modeling and machine learning for improving the observability of dynamical systems such as manufacturing equipment and processes, with the goal to improve process and product quality control. Prof. Gao is a fellow of the ASME, IEEE, SME, and CIRP (International Academy for Production Engineering). He has published more than 180 journal articles and holds 13 patents. He is a recipient of the SME Eli Whitney Productivity Award, ASME Blackall Machine Tool and Gage Award, IEEE Instrumentation and Measurement Society’s Technical Award, IEEE Best Application in Instrumental and Measurement Award, and NSF CAREER award. Currently, he is serving as a senior editor for the IEEE/ASME Transactions on Mechatronics.
Contact Michelle Murray for Zoom link.