RISE Lab Introduction
Dr. Chengying Xu is currently an associate professor at the University of Central Florida (UCF), Orlando, Florida. Her general research interests include advanced material manufacturing, intelligent systems and control, manufacturing system dynamics, sensing technique and sensor network, robotics. Dr. Xu has co-authored textbook "Intelligent Systems: Modeling, Optimization and Control" (CRC Press, 2008). She has authored and coauthored around 30 publications in archived journals and refereed conference proceedings, and received the Best Paper in Session Award in the 3rd International Conference on Cybernetics and Information Technologies Systems and Applications (CITSA). She is the Associate Editor for International Journal of Nanomanufacturing.
Dr. Xu has been awarded projects from NSF, DOE, ONR, Florida High Tech Corridor, Florida Center for Advanced Aero-Propulsion (FCAAP), Idaho National Laboratory, General Dynamics after she came to UCF to be a tenure track assistant professor in 2007. One of the remarkable ongoing research project of Dr. Xu is on micro-machining process of Polymer-derived Ceramics (PDC) ultrahigh-temperature sensors. It is widely agreed that high-temperature sensors are critical for next generation turbine technology, further optimizing turbine design and for real-time monitoring turbine operation conditions to make engines “smart”. In addition, the high-temperature sensors are also becoming critical for material processing, nuclear reactors and hypersonic space vehicles. Micro-machining of PDC ultrahigh-temperature sensors is one of the most appealing methods due to its non-dependence on workpiece material and shape, high geometric accuracy and surface quality, and overall quick productivity. Currently Dr. Xu has multiple collaborations with material scientists for this fundamental research.
In her Ph.D. research, one of Dr. Xu’s most significant achievements is that she independently designed a novel hierarchical fuzzy control scheme and implemented it on a three-axis MAZAK CNC machining center with a National Instruments real-time controller, which serves as a compact PC platform for intelligent control calculation, modular instrumentation and data acquisition. The grinding machine process is a typical multivariable nonlinear system with time-varying characteristic, which gives operators dramatic difficulty in modeling and control under various process uncertainties. Due to Dr. Xu’s research contribution, the embedded fuzzy controller automatically reduced the total cycle time around 10-30% without human interactions, thus extending the tool life substantially and improving the workpiece surface finish. The automation of machines to operate at optimal conditions without human intervention can reduce operation staff, cut-costs, achieve better quality products, and increase competitiveness of U.S. companies. These advantages will definitely benefit the US manufacturing market once it is implemented in manufacturing industry. Dr. Xu’s exceptional work in her Ph.D. research has been published in numerous prestigious peer-reviewed journals and presented in internationally recognized conferences. She was awarded the Chroafas Best Dissertation Award and Bilsland Dissertation Fellowship from Purdue University in 2006-2007.