Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length
The shape of run-length distribution changes with process shifts. This leads to complexity in interpreting the average run length performance. In this article, we show that the percentiles of the run-length distribution, especially the median run length (MRL), are more intuitive. The 5th and 95th pe...
| Main Authors: | , , , , |
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| Format: | Article |
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ASTM International
2018
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| _version_ | 1825722026030006272 |
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| author | Teoh, Wei Lin Lim, J.Y. Khoo, Michael Boon Chong Chong, Zhi Lin Yeong, Wai Chung |
| author_facet | Teoh, Wei Lin Lim, J.Y. Khoo, Michael Boon Chong Chong, Zhi Lin Yeong, Wai Chung |
| author_sort | Teoh, Wei Lin |
| collection | UM |
| description | The shape of run-length distribution changes with process shifts. This leads to complexity in interpreting the average run length performance. In this article, we show that the percentiles of the run-length distribution, especially the median run length (MRL), are more intuitive. The 5th and 95th percentiles of the run-length distribution are also provided in order to investigate the variation and spread of the run length. We develop two new optimal-design procedures for the exponentially weighted moving average (EWMA) charts, for monitoring the coefficient-of-variation (CV) squared (EWMA-γ2). These include minimization of the out-of-control MRL and the out-of-control expected MRL for deterministic and unknown shift sizes, respectively. Both the zero and steady states are discussed in this article. The optimal EWMA-γ2 chart is illustrated with real industrial data obtained from a metal sintering process. A comparative study reveals the superiority of the EWMA-γ2 charts for certain ranges of shifts in the CV. Copyright © 2018 by ASTM International |
| first_indexed | 2024-03-06T05:59:21Z |
| format | Article |
| id | um.eprints-23256 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:59:21Z |
| publishDate | 2018 |
| publisher | ASTM International |
| record_format | dspace |
| spelling | um.eprints-232562019-12-18T02:50:05Z http://eprints.um.edu.my/23256/ Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length Teoh, Wei Lin Lim, J.Y. Khoo, Michael Boon Chong Chong, Zhi Lin Yeong, Wai Chung HA Statistics The shape of run-length distribution changes with process shifts. This leads to complexity in interpreting the average run length performance. In this article, we show that the percentiles of the run-length distribution, especially the median run length (MRL), are more intuitive. The 5th and 95th percentiles of the run-length distribution are also provided in order to investigate the variation and spread of the run length. We develop two new optimal-design procedures for the exponentially weighted moving average (EWMA) charts, for monitoring the coefficient-of-variation (CV) squared (EWMA-γ2). These include minimization of the out-of-control MRL and the out-of-control expected MRL for deterministic and unknown shift sizes, respectively. Both the zero and steady states are discussed in this article. The optimal EWMA-γ2 chart is illustrated with real industrial data obtained from a metal sintering process. A comparative study reveals the superiority of the EWMA-γ2 charts for certain ranges of shifts in the CV. Copyright © 2018 by ASTM International ASTM International 2018 Article PeerReviewed Teoh, Wei Lin and Lim, J.Y. and Khoo, Michael Boon Chong and Chong, Zhi Lin and Yeong, Wai Chung (2018) Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length. Journal of Testing and Evaluation, 47 (1). p. 20170118. ISSN 0090-3973, DOI https://doi.org/10.1520/JTE20170118 <https://doi.org/10.1520/JTE20170118>. https://doi.org/10.1520/JTE20170118 doi:10.1520/JTE20170118 |
| spellingShingle | HA Statistics Teoh, Wei Lin Lim, J.Y. Khoo, Michael Boon Chong Chong, Zhi Lin Yeong, Wai Chung Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length |
| title | Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length |
| title_full | Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length |
| title_fullStr | Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length |
| title_full_unstemmed | Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length |
| title_short | Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length |
| title_sort | optimal designs of ewma charts for monitoring the coefficient of variation based on median run length and expected median run length |
| topic | HA Statistics |
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