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• W2022184282 abstract "Process knowledge can be exploited to improve the performance of control charts and it is not unusual to know that a specific variable shifts above or below its mean under an assignable cause. In such a case, a one-sided control chart is common. The available statistical theory for the one-sided tests is used to provide a reasonable compromise for a numerical procedure to design and implement multivariate solutions. Although simulation is used in the analysis, it is not a direct estimate of performance through simulation. Instead, weights are estimated and these are used to easily set a desired on-target average run length. Furthermore, an interesting quadratic programming solution is incorporated into the analysis. Then the statistical results are extended to a partial one-sided case where only some (not all) variables are known to shift in one direction and the numerical procedure is extended to design and implement the charts. A modern method can blend theory and algorithms into a practical solution. We conclude that modern computer software permits an efficient solution to this problem with meaningful performance advantages over traditional multivariate control charts." @default.
• W2022184282 created "2016-06-24" @default.
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• W2022184282 date "2006-08-01" @default.
• W2022184282 modified "2023-10-12" @default.
• W2022184282 title "Multivariate one-sided control charts" @default.
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• W2022184282 doi "https://doi.org/10.1080/07408170600692176" @default.
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