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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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.
Journal ArticleDOI
A triple exponentially weighted moving average control chart for monitoring time between events
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.
References
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Poisson Generally Weighted Moving Average and Double GWMA Control Charts
TL;DR: In this paper, a generally weighted moving average (GWMA) control chart for monitoring Poisson observations is introduced, and a novel control chart called "Poisson double GWMA" (PDGWMA), which is more sensitive than other control charts in detecting an out-of-control signal in most of situations, particularly in the cases of downward process shifts.