ABSTRACT
Among various quality assurance activities, process capability indices (PCIs) are recognized as the most effective tools to quantify and evaluate process performance. The one-sided capability index can adequately measure the process capability for processes with a smaller-is-better (S-type) quality characteristic. While focusing on the index , this study constructs a capability control chart to monitor the short-term capability based on the exponentially weighted moving average (EWMA). Simulations have shown that the EWMA capability control chart is adaptive regarding average run length. Further, this study applies change-point analysis to determine whether and when the short-term capability-level changes. Using these two proposed methods, engineers can realize a variety of short-term process capabilities in good time and implement control measures efficiently against a poor long-term process capability.
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Notes on contributors
Mou-Yuan Liao
Mou-Yuan Liao is currently a professor in the Department of Data Science and Big Data Analytics, Providence University. He received his PhD degree in Industrial Engineering and Management from National Chiao Tung University (NCTU) in 2007 and the MS degree in Statistics from Cheng Kung University (NCKU) in 2002. His research interests include statistical process control, statistical computing, machine learning and data mining.
Chien-Wei Wu
Chien-Wei Wu is currently a professor in the Department of Industrial Engineering and Engineering Management at National Tsing Hua University (NTHU). He received his PhD degree in Industrial Engineering and Management with Outstanding Ph. D. Student Award from National Chiao Tung University (NCTU) in 2004, the MS degree in Statistics from NTHU in 2002 and the BS degree in Applied Mathematics with the Phi Tao Phi Honor from National Chung Hsing University (NCHU) in 2000. He worked for National Taiwan University of Science and Technology (NTUST) and Feng Chia University (FCU) before he joined NTHU. He has received Dr Ta-You Wu Memorial Award (Outstanding Young Researcher Award) from the National Science Council (NSC) in 2011 and Outstanding Young Industrial Engineer Award from the Chinese Institute of Industrial Engineers (CIIE) in 2011, Excellent Research Award in 2011 and Excellent Teaching Award in 2012 from NTUST and Outstanding Research Award from NSC in 2021. His research interests include quality engineering and management, statistical process control, process capability analysis, applied statistics and data analysis.