As manufacturing quality has become a decisive factor in global market competition, quality control techniques such as Statistical Process Control (SPC) and Engineering Process Control (EPC) are becoming popular in industries. With advances in information, sensing, and data capture technology, large volumes of data are being routinely collected and shared over multiple-stage processes, which have growing impacts on the existing SPC and EPC methods. Thus, there is an urgent need for an effective quality control strategy for a multistage process combining SPC and EPC. However, some technical challenges, such as the eliminating of the "window of opportunity" for detection, the handling of the dynamics and autocorrelation structure, and the decomposing of the confounded incoming signals, need to be addressed to ensure high detectability and traceability. This research will tackle these unique issues due to SPC and EPC integration, and provide an effective approach to improve the detectability and traceability of monitoring and diagnosing a multistage process.

Personal Profile
Dr. Fugee Tsung is an assistant professor of Industrial Engineering and Engineering Management at the Hong Kong University of Science and Technology. He received both his PhD and MSc in Industrial and Operations Engineering from the University of Michigan, Ann Arbor, and his BSc in Mechanical Engineering from National Taiwan University. He worked for Ford Motor Company and Rockwell International and did his post-doctoral research with Chrysler Corporation. He serves as an elected Council Member for Institute for Operations Research and the Management Sciences (INFORMS) Quality, Statistics and Reliability (QSR) Section. He is also a member of IIE, ASQ, and ASQ Six Sigma Forum. His current research interests include quality engineering and management, process control, monitoring and diagnosis.