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題名 Service quality variation monitoring using the interquartile range control chart
作者 楊素芬
Yang, Su-Fen
Jiang, Ting-An
貢獻者 統計系
關鍵詞 Control chart ;  process variability ;  interquartile range ;  free-distribution ; average run length
日期 2018-09
上傳時間 26-May-2020 14:25:13 (UTC+8)
摘要 Control charts are effective tools for signal detection for both manufacturing and service processes. Much of the data in service industries come from processes exhibiting non-normal or unknown distributions, for which Shewhart variables control charts are not appropriate. This paper thus proposes a new exponentially weighted moving average (EWMA) interquartile range control chart with single sampling and double sampling schemes, respectively, for detecting the out-of-control variance/standard deviation of a critical quality characteristic that exhibits a non-normal or unknown distribution. We explore the sampling properties of the new monitoring statistics, and calculate the average run length of the proposed chart to compare the out-of-control detection performance with existing nonparametric variance charts/standard deviation for cases in which the critical quality characteristic follows the normal and non-normal distributions. Comparison results show that the proposed double sampling EWMA interquartile range control chart exhibits better detection performance than that of the single sampling EWMA interquartile range control chart. Moreover, the former always outperforms existing control charts for small and medium shifts in process variance/standard deviation. Finally, we use a numerical example with service data from a local bank branch to illustrate the application of the proposed control chart.
關聯 Quality Technology and Quantitative Management, Vol.16, No.5, pp.613-627
資料類型 article
DOI https://doi.org/10.1080/16843703.2018.1519921
dc.contributor 統計系
dc.creator (作者) 楊素芬
dc.creator (作者) Yang, Su-Fen
dc.creator (作者) Jiang, Ting-An
dc.date (日期) 2018-09
dc.date.accessioned 26-May-2020 14:25:13 (UTC+8)-
dc.date.available 26-May-2020 14:25:13 (UTC+8)-
dc.date.issued (上傳時間) 26-May-2020 14:25:13 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/129921-
dc.description.abstract (摘要) Control charts are effective tools for signal detection for both manufacturing and service processes. Much of the data in service industries come from processes exhibiting non-normal or unknown distributions, for which Shewhart variables control charts are not appropriate. This paper thus proposes a new exponentially weighted moving average (EWMA) interquartile range control chart with single sampling and double sampling schemes, respectively, for detecting the out-of-control variance/standard deviation of a critical quality characteristic that exhibits a non-normal or unknown distribution. We explore the sampling properties of the new monitoring statistics, and calculate the average run length of the proposed chart to compare the out-of-control detection performance with existing nonparametric variance charts/standard deviation for cases in which the critical quality characteristic follows the normal and non-normal distributions. Comparison results show that the proposed double sampling EWMA interquartile range control chart exhibits better detection performance than that of the single sampling EWMA interquartile range control chart. Moreover, the former always outperforms existing control charts for small and medium shifts in process variance/standard deviation. Finally, we use a numerical example with service data from a local bank branch to illustrate the application of the proposed control chart.
dc.format.extent 129 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Quality Technology and Quantitative Management, Vol.16, No.5, pp.613-627
dc.subject (關鍵詞) Control chart ;  process variability ;  interquartile range ;  free-distribution ; average run length
dc.title (題名) Service quality variation monitoring using the interquartile range control chart
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1080/16843703.2018.1519921
dc.doi.uri (DOI) https://doi.org/10.1080/16843703.2018.1519921