Journal ArticleDOI
Distribution-free triple EWMA control chart for monitoring the process location using the Wilcoxon rank-sum statistic with fast initial response feature
Tokelo Irene Letshedi,Jean-Claude Malela-Majika,Philippe Castagliola,Sandile Charles Shongwe +3 more
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This article is published in Quality and Reliability Engineering International.The article was published on 2021-07-01. It has received 14 citations till now. The article focuses on the topics: EWMA chart & Wilcoxon signed-rank test.read more
Citations
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Journal ArticleDOI
A critique of a variety of “memory-based” process monitoring methods
TL;DR: Many extensions and modifications have been made to standard process monitoring methods such as the exponentially weighted moving average (EWMA) chart and the cumulative sum (CUSUM) chart as mentioned in this paper , usually to put greater emphasis on past data and less weight on current and recent data.
Journal ArticleDOI
A nonparametric CUSUM scheme for monitoring multivariate time-between-events-and-amplitude data with application to automobile painting
TL;DR: Monitoring time-between-events-and-amplitude (TBEA) data, including the time interval between two successive nonconforming events and the amplitude of an event, is significant in many applications.
Journal ArticleDOI
Monitoring univariate and multivariate profiles using the triple exponentially weighted moving average scheme with fixed and random explanatory variables
TL;DR: In this article, the authors used the triple exponentially weighted moving average (TEWMA) scheme to develop new monitoring schemes for univariate and multivariate linear profiles to monitor the model parameters.
Journal ArticleDOI
Monitoring univariate and multivariate profiles using the triple exponentially weighted moving average scheme with fixed and random explanatory variables
TL;DR: In this article , the authors used the triple exponentially weighted moving average (TEWMA) scheme to develop new monitoring schemes for univariate and multivariate linear profiles to monitor model parameters in conjunction with the error variance of the process with fixed and random explanatory variables.
Journal ArticleDOI
Nonparametric EWMA-Type Control Charts for Monitoring Industrial Processes: An Overview
TL;DR: An up-to-date overview of nonparametric Exponentially Weighted Moving Average (EWMA) control charts is provided, to emphasize their crucial role in the contemporary online statistical process control.
References
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Book ChapterDOI
Individual Comparisons by Ranking Methods
TL;DR: The comparison of two treatments generally falls into one of the following two categories: (a) a number of replications for each of the two treatments, which are unpaired, or (b) we may have a series of paired comparisons, some of which may be positive and some negative as mentioned in this paper.
Book
Statistical quality control : a modern introduction
TL;DR: Part I: Introduction Chapter 1: Quality Improvement in the Modern Business Environment Chapter 2: The DMAIC Process Chapter 3: Statistical Methods Useful in Quality Control and Improvement Chapter 4: Inferences about Process Quality
Journal ArticleDOI
EWMA Control Charts with Time-Varying Control Limits and Fast Initial Response
TL;DR: The control limits of an exponentially weighted moving average (EWMA) control chart should vary with time, approaching asymptotic limits as time increases as discussed by the authors, however, previous analyses of EWMA charts have focused on only the control limits.
Journal ArticleDOI
The Generally Weighted Moving Average Control Chart for Detecting Small Shifts in the Process Mean
Shey-Huei Sheu,Tse-Chieh Lin +1 more
TL;DR: In this paper, a generalized control chart called the generally weighted moving average (GWMA) control chart was proposed and analyzed for detecting small shifts in the mean of a process, with time varying control limits to detect start-up shifts more sensitively.
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Modified exponentially weighted moving average (EWMA) control chart for an analytical process data
Alpaben K. Patel,Jyoti Divecha +1 more