Study on design of double sampling mean and variance control charts
碩士 === 國立政治大學 === 統計學系 === 104 === Control charts are effective tools for detecting manufacturing processes and service processes. Nowadays, much of the data in manufacturing or service industries comes from processes having non-normal or unknown distributions. The commonly used Shewhart control cha...
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ndltd-TW-104NCCU53370182017-10-08T04:31:18Z http://ndltd.ncl.edu.tw/handle/31218523354470458909 Study on design of double sampling mean and variance control charts 雙次抽樣平均數和變異數管制圖設計之研究 Wu, Sin Hong 吳信宏 碩士 國立政治大學 統計學系 104 Control charts are effective tools for detecting manufacturing processes and service processes. Nowadays, much of the data in manufacturing or service industries comes from processes having non-normal or unknown distributions. The commonly used Shewhart control charts, which depend heavily on the normality assumption, are not appropriately used for this situation. In this paper, we propose a standardized dynamic double sampling asymmetric EWMA mean control chart (SDDS EWMA-AM chart), a standardized dynamic double sampling asymmetric EWMA variance control chart (SDDS EWMA-AV chart), and their combined charts (joint SDDS EWMA-AM and SDDS EWMA-AV charts) to monitor process mean, variance and both shifts, respectively. The charts based on the double sampling procedure and two simple distribution-free transformed statistics are used for non-normal distribution of a quality variable. The performance of the proposed charts and that of some existing distribution-free mean and variance charts are compared. Further, a non-normal service times example from the service system of a bank branch is used to illustrate the applications of the proposed charts and to compare detection performance with the existing distribution-free mean and variance control charts. The charts we proposed show superior detection performance compared to the existing distribution-free mean and variance charts. Thus they are recommended. Yang, Su Fen 楊素芬 2016 學位論文 ; thesis 142 en_US |
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碩士 === 國立政治大學 === 統計學系 === 104 === Control charts are effective tools for detecting manufacturing processes and service processes. Nowadays, much of the data in manufacturing or service industries comes from processes having non-normal or unknown distributions. The commonly used Shewhart control charts, which depend heavily on the normality assumption, are not appropriately used for this situation. In this paper, we propose a standardized dynamic double sampling asymmetric EWMA mean control chart (SDDS EWMA-AM chart), a standardized dynamic double sampling asymmetric EWMA variance control chart (SDDS EWMA-AV chart), and their combined charts (joint SDDS EWMA-AM and SDDS EWMA-AV charts) to monitor process mean, variance and both shifts, respectively. The charts based on the double sampling procedure and two simple distribution-free transformed statistics are used for non-normal distribution of a quality variable. The performance of the proposed charts and that of some existing distribution-free mean and variance charts are compared. Further, a non-normal service times example from the service system of a bank branch is used to illustrate the applications of the proposed charts and to compare detection performance with the existing distribution-free mean and variance control charts. The charts we proposed show superior detection performance compared to the existing distribution-free mean and variance charts. Thus they are recommended.
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author2 |
Yang, Su Fen |
author_facet |
Yang, Su Fen Wu, Sin Hong 吳信宏 |
author |
Wu, Sin Hong 吳信宏 |
spellingShingle |
Wu, Sin Hong 吳信宏 Study on design of double sampling mean and variance control charts |
author_sort |
Wu, Sin Hong |
title |
Study on design of double sampling mean and variance control charts |
title_short |
Study on design of double sampling mean and variance control charts |
title_full |
Study on design of double sampling mean and variance control charts |
title_fullStr |
Study on design of double sampling mean and variance control charts |
title_full_unstemmed |
Study on design of double sampling mean and variance control charts |
title_sort |
study on design of double sampling mean and variance control charts |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/31218523354470458909 |
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