Speaker
Dr. Wenmeng Tian, Mississippi State University
Title
Modeling and Monitoring for Data-rich Manufacturing Systems: An Integrated Knowledge-driven Approach
Physical Location
Allen Hall 14
Abstract: With the advancement of sensing technology, various types of high volume data are available for quality improvement in advanced manufacturing systems. Those data types include diverse discrete data, signal profiles, digital images, and 3D point clouds. Various engineering knowledge, such as kinematics information and physical process models, can be used to guide the statistical learning for enhanced modeling accuracy and interpretability. This talk presents examples of my recent research projects on the integration of process knowledge into statistical modeling and monitoring for advanced manufacturing, including both subtractive and additive manufacturing processes. Both simulation and case studies are used to demonstrate the effectiveness of the proposed approaches. Finally, several challenges and research opportunities are discussed for data-rich manufacturing systems.