Statistical Process Control of Multistage Processes
Fugee Tsung
Department of Industrial Engineering and Engineering Management
Hong Kong University of Science & Technology
Wednesday, April 27, 2005
4:30 - 5:45 PM
Terman Engineering Center, Room 453
Abstract:
As quality and Six Sigma excellence has become a decisive factor in
global market competition, quality control techniques such as
Statistical Process Control (SPC) 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 has a growing impact on the existing SPC
methods. In this talk, we will focus on some recent advances in
multistage SPC.
More specifically, a regression control chart is used to monitor and
diagnose multistage processes. Its basic idea is to remove the influence
of the covariate from the previous stage using regression adjustment and
then apply a regular control scheme to the regression residual of the
current stage. In practice, the regression model relating the output and
the covariate is rarely known and needs to be estimated. The run length
performance of the regression control chart when the true parameters are
replaced with their estimates will be studied.
Bio:
Dr. Fugee Tsung is an associate professor in the Department of
Industrial Engineering and Engineering Management at the Hong Kong
University of Science & Technology. He received both his M.S. and
Ph.D. in Industrial and Operations Engineering from the University of
Michigan, Ann Arbor, and his B.S. degree in Mechanical Engineering from
National Taiwan University. He worked for Ford Motors and Rockwell
International and did his post-doctoral research with Chrysler. He is
now a Department Editor for the IIE Transactions on Quality and
Reliability, Associate Editor for IJRQSE and IJSSCA, and Chairing the
Quality, Statistics, and Reliability (QSR) Section at INFORMS. He is
also the winner of the Best Paper Award for the IIE Transactions focus
issue on Quality and Reliability in 2003. His current research
interests include quality engineering and management, statistical
process control, monitoring and diagnosis.
Operations Research Colloquia: http://or.stanford.edu/oras_seminars.html