Abstract:Revolutionary computing technologies are driving significant advances in the manufacturing domain. High-fidelity simulations and virtual design environments allow unprecedented opportunities to test and validate systems before they are built, reducing overall design time and cost. Big Data streaming from the factory floor can be collected over high-speed networks,and stored in large-scale server farms (such as cloud-based systems). Comparison of key performance indicators between the expected or simulated system and the actual physical system can enable improved analytics, leading to increased performance. This talk will describe how the integration of simulation and plant-floor data can enable new control approaches that are able to optimize the overall performance of manufacturing systems.
Bio:
Dawn M. Tilbury is currently the Associate Dean for Research in the College of Engineering, University of Michigan. She received the B.S. degree in Electrical Engineering, summa cum laude, from the University of Minnesota in 1989, and the M.S. and Ph. D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1992 and 1994, respectively. In 1995, she joined the Mechanical Engineering Department at the University of Michigan, Ann Arbor, where she is currently Professor, with a joint appointment as Professor of EECS. Her research interests include distributed control of mechanical system swith network communication, logic control of manufacturing systems, reliability of ground robotics, and dynamic systems modeling of physiological systems. She was elected Fellow ofthe IEEE in 2008 and Fellow of the ASME in 2012, and is a Life Member of SWE.
