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Open AccessArticle

An Enhanced Auxiliary Information-Based EWMA-t Chart for Monitoring the Process Mean

1
Department of Information Management, Shih Chien University Kaohsiung Campus, Kaohsiung City 845, Taiwan
2
Department of Industrial Management and Enterprise Information, Aletheia University, New Taipei City 251, Taiwan
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(7), 2252; https://doi.org/10.3390/app10072252
Received: 20 February 2020 / Revised: 15 March 2020 / Accepted: 22 March 2020 / Published: 26 March 2020
(This article belongs to the Section Applied Industrial Technologies)
The exponentially weighted moving average t chart using auxiliary information (AIB-EWMA-t chart) is an effective approach for monitoring small process mean shifts when the process standard deviation is unstable or poorly estimated. To further enhance the sensitivity of the AIB-EWMA-t chart, in this study, we propose an AIB generally weighted moving average (GWMA) t chart (AIB-GWMA-t chart) to monitor the process mean. The existing EWMA-t, GWMA-t, and AIB-EWMA-t charts are special cases of the AIB-GWMA-t chart. Numerical simulation studies indicate that the AIB-GWMA-t chart performs uniformly and substantially better than the EWMA-t and GWMA-t charts in terms of average run length. Moreover, the AIB-GWMA-t chart with large design and adjustment parameters also outperforms the AIB-EWMA-t chart when the correlation coefficients are within a certain range. An illustrative example is provided to highlight the efficiency of the proposed AIB-GWMA-t chart in detecting small process mean shifts. View Full-Text
Keywords: average run length; auxiliary information; EWMA-t chart; GWMA-t chart; statistical process control average run length; auxiliary information; EWMA-t chart; GWMA-t chart; statistical process control
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Chen, J.-H.; Lu, S.-L. An Enhanced Auxiliary Information-Based EWMA-t Chart for Monitoring the Process Mean. Appl. Sci. 2020, 10, 2252.

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