Journal ArticleDOI
Joint monitoring of mean and variance using Max-EWMA for Weibull process
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In this paper, the authors proposed a maximum exponentially weighted moving average (MEWA) algorithm for the normal process mean and dispersion monitoring, which can be used to simultaneously monitor the process dispersion and mean.Abstract:
Simultaneously monitoring of process mean and dispersion for the normal process has gained considerable attention. In this manuscript, we have proposed a maximum exponentially weighted moving avera...read more
References
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Journal ArticleDOI
Monitoring Process Mean and Variability with One EWMA Chart
TL;DR: A new EWMA chart is proposed which effectively combines the usual two EWMA charts into one chart and has the property that it is effective in detecting both increases and decreases in mean and/or variability.
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On Properties of Q Charts for Variables
TL;DR: The sensitivity of four tests on Shewhart type Q charts and of specially designed EWMA and CUSUM Q charts to detect one-step permanent shifts of either a normal mean or standard deviation has been studied as discussed by the authors.
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X and R Control Charts for Skewed Populations
Ds Bai,Insung Choi +1 more
TL;DR: In this article, a weighted variance concept is used to set up control limits of X and R charts for skewed populations, based on the direction and degree of skewness estimated.
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Control Charts for Weibull Processes With Standards Given
TL;DR: In this article, the traditional median and range chart limits from s-normal theory are applied to Weibull processes, and the risk (the probability of a single point falling outside the control limits) is substantially different from the 0.003 a control chart user might have hoped for.