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• W2921096484 endingPage "356" @default.
• W2921096484 startingPage "356" @default.
• W2921096484 abstract "Control charts are considered as powerful tools in detecting any shift in a process. Usually, the Shewhart control chart is used when data follows the symmetrical property of a normal distribution. In practice, the data from the industry may follow a non-symmetrical distribution or an unknown distribution. The average run length (ARL) is a significant measure to assess the performance of the control chart. The ARL may mislead when the statistic is computed from an asymmetric distribution. To handle this issue, in this paper, an ARL-unbiased hybrid exponentially weighted moving average proportion (HEWMA-p) chart is proposed for monitoring the process variance for a non-normal distribution or an unknown distribution. The efficiency of the proposed chart is compared with the existing chart in terms of ARLs. The proposed chart is more efficient than the existing chart in terms of ARLs. A real example is given for the illustration of the proposed chart in the industry." @default.
• W2921096484 created "2019-03-22" @default.
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• W2921096484 date "2019-03-09" @default.
• W2921096484 modified "2023-10-17" @default.
• W2921096484 title "A Nonparametric HEWMA-p Control Chart for Variance in Monitoring Processes" @default.
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• W2921096484 doi "https://doi.org/10.3390/sym11030356" @default.
• W2921096484 hasPublicationYear "2019" @default.
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