https://orcid.org/0000-0002-9666-5554
![Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5933/TOC-Subject-Sample-2021-Engineering-Tech.jpg"})
Abstract
We argue against the use of generally weighted moving average (GWMA) control charts. Our primary reasons are the following: (1) There is no recursive formula for the GWMA control chart statistic, so all previous data must be stored and used in the calculation of each chart statistic. (2) The Markovian property does not apply to the GWMA statistics, so computer simulation must be used to determine control limits and the statistical performance. (3) An appropriately designed, and much simpler, exponentially weighted moving average (EWMA) chart provides as good or better statistical performance. (4) In some cases the GWMA chart gives more weight to past data values than to current values.
Additional information
Notes on contributors
Sven Knoth
Sven Knoth is a professor of Statistics in the Department of Mathematics and Statistics within the School of Economic and Social Sciences at the Helmut Schmidt University, Hamburg, Germany. Prior to that, he worked as a Senior SPC Engineer at Advanced Mask Technology Center (AMTC) Dresden, Germany, from 2004 to 2009. He is an Associate Editor of Computational Statistics and Quality Engineering.
William H. Woodall
William H. Woodall is an emeritus professor in the Department of Statistics at Virginia Tech. He is a former editor of the Journal of Quality Technology (2001–2003). He is the recipient of the Box Medal (2012), Shewhart Medal (2002), Hunter Award (2019), Youden Prize (1995, 2003), Brumbaugh Award (2000, 2006), Bisgaard Award (2012), Nelson Award (2014), Ott Foundation Award (1987), and best paper award for IIE Transactions on Quality and Reliability Engineering (1997). He is a Fellow of the American Statistical Association, a Fellow of the American Society for Quality, and an elected member of the International Statistical Institute.
Víctor G. Tercero-Gómez
Víctor G. Tercero-Gómez is a professor at the Department of Industrial Engineering, in the School of Engineering and Sciences at Tecnologico de Monterrey. Certified Black Belt and Master Black Belt in Six Sigma. His research interests include SPM, nonparametric statistics and quality engineering.