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題名 An Improved Distribution Free EWMA Mean Chart
作者 楊素芬
Yang,Su-Fen
貢獻者 統計系
關鍵詞 mean chart; binomial distribution; skewed distribution; average run length
日期 2013-10
上傳時間 10-十二月-2013 17:14:35 (UTC+8)
摘要 Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much service data comes from a process with variables having non-normal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, should not be properly used here. In this paper, we propose an improved asymmetric EWMA mean chart based on a simple statistic to monitor process mean shift. We explored the sampling properties of the new monitoring statistic and calculated the average run lengths of the proposed asymmetric EWMA mean chart. We recommend the proposed improved asymmetric EWMA mean chart because the average run lengths of the modified charts are more accurate and reasonable than those of the five existed mean charts. A numerical example of service times with a right skewed distribution from a service system of a bank branch is used to illustrate the application of the improved asymmetric EWMA mean chart and to compare it with the five existing mean charts. The proposed chart showed better detection performance than those of the five existing mean charts in monitoring and detecting shifts in the process mean.
關聯 Communications in Statistics-Simulation and Computation,Published online: 10 Oct 2013
資料類型 article
DOI http://dx.doi.org/10.1080/03610918.2013.763980
dc.contributor 統計系en_US
dc.creator (作者) 楊素芬zh_TW
dc.creator (作者) Yang,Su-Fenen_US
dc.date (日期) 2013-10en_US
dc.date.accessioned 10-十二月-2013 17:14:35 (UTC+8)-
dc.date.available 10-十二月-2013 17:14:35 (UTC+8)-
dc.date.issued (上傳時間) 10-十二月-2013 17:14:35 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/62347-
dc.description.abstract (摘要) Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much service data comes from a process with variables having non-normal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, should not be properly used here. In this paper, we propose an improved asymmetric EWMA mean chart based on a simple statistic to monitor process mean shift. We explored the sampling properties of the new monitoring statistic and calculated the average run lengths of the proposed asymmetric EWMA mean chart. We recommend the proposed improved asymmetric EWMA mean chart because the average run lengths of the modified charts are more accurate and reasonable than those of the five existed mean charts. A numerical example of service times with a right skewed distribution from a service system of a bank branch is used to illustrate the application of the improved asymmetric EWMA mean chart and to compare it with the five existing mean charts. The proposed chart showed better detection performance than those of the five existing mean charts in monitoring and detecting shifts in the process mean.en_US
dc.format.extent 128 bytes-
dc.format.mimetype text/html-
dc.language.iso en_US-
dc.relation (關聯) Communications in Statistics-Simulation and Computation,Published online: 10 Oct 2013en_US
dc.subject (關鍵詞) mean chart; binomial distribution; skewed distribution; average run lengthen_US
dc.title (題名) An Improved Distribution Free EWMA Mean Charten_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1080/03610918.2013.763980-
dc.doi.uri (DOI) http://dx.doi.org/10.1080/03610918.2013.763980-