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題名 Quality control under nonparametric bivariate location and dispersion processes
作者 陳立榜;楊素芬
Chen, Li-Pang;Yang, Su-Fen;Jiang, Ting-An
貢獻者 統計系
日期 2021-10
上傳時間 7-Oct-2022 13:43:31 (UTC+8)
摘要 Control charts are effective tools for detecting out-of-control conditions of process parameters in manufacturing and service industries. The development of distributionfree control charts is important in statistical process control when the process quality variable follows an unknown or a non-normal distribution. This research proposes the bivariate kernel estimation to establish a new control region based on the exponentially weighted moving average median statistic and exponentially weighted moving average interquartile range statistic for simultaneously monitoring the process location and dispersion. Under proposed kernel estimator and control region, we further set up a corresponding new control chart. Moreover, we compute the out-of-control average run length to evaluate out-of-control detection performance of the proposed control region and also compare the proposed control region with some existing location and dispersion control charts. Results show that our proposed chart always exhibits superior detection performance when the shifts in process location and/or dispersion are small or moderate. The proposed method is also applied to analyze the random service time data of a bank branch in Taiwan.
關聯 The 30th South Taiwan Statistics Conference and 2021Chinese Institute of Probability and Statistics Annuals Meeting, Institute of Statistics, National University of Kaohsiung
資料類型 conference
dc.contributor 統計系
dc.creator (作者) 陳立榜;楊素芬
dc.creator (作者) Chen, Li-Pang;Yang, Su-Fen;Jiang, Ting-An
dc.date (日期) 2021-10
dc.date.accessioned 7-Oct-2022 13:43:31 (UTC+8)-
dc.date.available 7-Oct-2022 13:43:31 (UTC+8)-
dc.date.issued (上傳時間) 7-Oct-2022 13:43:31 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/142351-
dc.description.abstract (摘要) Control charts are effective tools for detecting out-of-control conditions of process parameters in manufacturing and service industries. The development of distributionfree control charts is important in statistical process control when the process quality variable follows an unknown or a non-normal distribution. This research proposes the bivariate kernel estimation to establish a new control region based on the exponentially weighted moving average median statistic and exponentially weighted moving average interquartile range statistic for simultaneously monitoring the process location and dispersion. Under proposed kernel estimator and control region, we further set up a corresponding new control chart. Moreover, we compute the out-of-control average run length to evaluate out-of-control detection performance of the proposed control region and also compare the proposed control region with some existing location and dispersion control charts. Results show that our proposed chart always exhibits superior detection performance when the shifts in process location and/or dispersion are small or moderate. The proposed method is also applied to analyze the random service time data of a bank branch in Taiwan.
dc.format.extent 133324 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) The 30th South Taiwan Statistics Conference and 2021Chinese Institute of Probability and Statistics Annuals Meeting, Institute of Statistics, National University of Kaohsiung
dc.title (題名) Quality control under nonparametric bivariate location and dispersion processes
dc.type (資料類型) conference