Journal ArticleDOI
Monitoring of time between events with a double generally weighted moving average control chart
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This article is published in Quality and Reliability Engineering International.The article was published on 2019-03-01. It has received 31 citations till now. The article focuses on the topics: Robustness (computer science) & Moving average.read more
Citations
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Journal ArticleDOI
Simultaneous monitoring of magnitude and time-between-events data with a Max-EWMA control chart
TL;DR: Overall, performance study indicates that the Max-EWMA chart outperforms its existing counterparts with the same objective of detecting small shifts in process parameters and competes strongly in detecting large shifts.
Journal ArticleDOI
Generally weighted moving average monitoring schemes: Overview and perspectives
TL;DR: An overview of monitoring schemes from a class called generally weighted moving average (GWMA) is provided in this article, where a number of possible future GWMA-related schemes are documented and categorized in such a manner that it is easy to identify research gaps.
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A triple exponentially weighted moving average control chart for monitoring time between events
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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.
References
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Journal ArticleDOI
Phase I control charts for times between events
TL;DR: In this article, phase I control charts for exponentially distributed processes are discussed and methods for computing the control limits are given and the overall Type I error rates of these charts are evaluated.
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A study of time‐between‐events control chart for the monitoring of regularly maintained systems
Michael B. C. Khoo,Min Xie +1 more
TL;DR: An approach of integrating maintenance decision with statistical process monitoring methods is illustrated by adopting a modification for a time-between-events control chart, i.e. the exponential chart for monitoring the failure process of a maintained Weibull distributed system.
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Cumulative Sum Control Charts for Monitoring Weibull‐distributed Time Between Events
Mohammed S. Shafae,Mohammed S. Shafae,Rebecca M. Dickinson,William H. Woodall,Jaime A. Camelio +4 more
TL;DR: The ECUSUM chart is shown to be much less robust to departures from the exponential distribution than was previously claimed in the literature and the advantages of using one of the other two charts, which show surprisingly similar performance.
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Design of exponential control charts based on average time to signal using a sequential sampling scheme
TL;DR: The average time to signal (ATS) is used instead of the average run length to evaluate the performance of TBE charts, since the ATS involves both the number and the time of samples inspected until a signal occurs.
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The extended GWMA control chart
Shey-Huei Sheu,Yu-Tai Hsieh +1 more
TL;DR: In this paper, the double exponentially weighted moving average (DEWMA) control chart is proposed to detect medium shifts in the mean of a process when the shifts are between 0.5 and 1.5 standard deviations.