Condition Monitoring and Control for Intelligent Manufacturing

- Intelligent Machine Tools - Towards Adaptive Control

- Condition-Based Monitoring of Manufacturing Equipment

- Condition-Based Monitoring of Manufacturing Processes

- From Monitoring to Diagnosis to Prognosis

- Adaptive Control Based on In-Situ Monitoring

- Harmonic Wavelet Packet Transform: A New Approach to Machine Condition Monitoring and Health Evaluation

- Extraction of Machinery Health Index in CBM based on Wavelet Modulus Maxima

- Understanding System Dynamics via Transfer Function in Modeling Production Control Systems

- Predictive Control of Flexible Structures

- Monitoring and Optimization of Ball-End Milling Process

- Sensing-System Reconfiguration: A Comparison of On-Line Methods

- Error Recovery for Real-Time Manufacturing Control via Augmented Petri Nets

- A Weighted-PCA Based Feature Selection Algorithm for Intelligent Monitoring

- An Adaptive Fuzzy Inference System for Prediction of Cutting Forces in End Milling

- Intelligent Monitoring and Optimization of Cutting Process for CNC Turning

- A Comparison of Two Covariates for Condition-based Maintenance Using Economic Measures of Performance

- Agent-based Modular Control Architecture for Reconfigurable Manufacturing Systems

- A Web-based Approach to Real-time Monitoring and Remote Control

Dr. Lihui Wang is a research officer of Integrated Manufacturing Technologies Institute at National Research Council of Canada (NRC). He received his Ph.D. and M.Sc. degrees from the Kobe University, Japan in 1993 and 1990, and his B.Sc. from China in 1982, respectively. Prior to joining NRC, he has worked for two years at the Kobe University and another two years at the Toyohashi University of Technology (both in Japan) as an Assistant Professor. His work on web-based monitoring and remote control has won the Best Paper Award at the FAIM 2002 international conference in Germany, and his research on intelligent shop floor has won the Best Poster Award at PRO-VE'03, the 4th IFIP Working Conference on Virtual Enterprises in Switzerland. In addition, he is also a five-time winner of the NRC Institute Awards on Excellence & Leadership in R&D and Global Reach. His research interests are focused on web-based real-time monitoring and control, distributed artificial intelligence, intelligent manufacturing systems, and distributed process planning. He published over 100 research papers in engineering journals and refereed conference proceedings, and has edited 3 conference proceedings on manufacturing research.

Dr. Robert X. Gao is an Associate Professor of Mechanical Engineering at the University of Massachusetts Amherst, USA. He received his B.S. degree from China, and his M.S. and Ph.D. from the Technical University Berlin, Germany, in 1982, 1985, and 1991, respectively. Since starting his academic career in 1992, he has been conducting research in the general area of embedded sensors and sensor networks, "smart" electromechanical systems, wireless data communication, and signal processing for machine health monitoring, diagnosis, and prognosis. Dr. Gao has published over 100 refereed papers on journals and international conferences, and has one US patent and two pending patent applications on sensing. He is an Associate Editor for the IEEE Transactions on