An efficient multivariate control charting mechanism based on SPRT
This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Avera...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ou, Yanjing [verfasserIn] |
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| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Rechteinformationen: |
Nutzungsrecht: © 2014 Taylor & Francis 2014 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: International journal of production research - London : Taylor & Francis, 1961, 53(2015), 7, Seite 1937-1949 |
|---|---|
| Übergeordnetes Werk: |
volume:53 ; year:2015 ; number:7 ; pages:1937-1949 |
| Links: |
|---|
| DOI / URN: |
10.1080/00207543.2014.925601 |
|---|
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OLC1963688678 |
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| 520 | |a This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. | ||
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10.1080/00207543.2014.925601 doi PQ20160617 (DE-627)OLC1963688678 (DE-599)GBVOLC1963688678 (PRQ)c2756-b89c054c3bdb137d0a15ba1a97c4fb164c1501b31379857db8b3334dbfdd0f950 (KEY)0019873020150000053000701937efficientmultivariatecontrolchartingmechanismbased DE-627 ger DE-627 rakwb eng 600 620 330 DNB 85.35 bkl 52.70 bkl Ou, Yanjing verfasserin aut An efficient multivariate control charting mechanism based on SPRT 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. Nutzungsrecht: © 2014 Taylor & Francis 2014 chart statistical process control synthetic chart sequential probability ratio test MEWMA chart hotelling's T Normal distribution Control charts Comparative studies Production management Operations research Multivariate analysis Chen, Nan oth Khoo, Michael B.C oth Enthalten in International journal of production research London : Taylor & Francis, 1961 53(2015), 7, Seite 1937-1949 (DE-627)129358835 (DE-600)160477-6 (DE-576)014731150 0020-7543 nnns volume:53 year:2015 number:7 pages:1937-1949 http://dx.doi.org/10.1080/00207543.2014.925601 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207543.2014.925601 http://search.proquest.com/docview/1655577079 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_21 GBV_ILN_26 GBV_ILN_70 GBV_ILN_4126 85.35 AVZ 52.70 AVZ AR 53 2015 7 1937-1949 |
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10.1080/00207543.2014.925601 doi PQ20160617 (DE-627)OLC1963688678 (DE-599)GBVOLC1963688678 (PRQ)c2756-b89c054c3bdb137d0a15ba1a97c4fb164c1501b31379857db8b3334dbfdd0f950 (KEY)0019873020150000053000701937efficientmultivariatecontrolchartingmechanismbased DE-627 ger DE-627 rakwb eng 600 620 330 DNB 85.35 bkl 52.70 bkl Ou, Yanjing verfasserin aut An efficient multivariate control charting mechanism based on SPRT 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. Nutzungsrecht: © 2014 Taylor & Francis 2014 chart statistical process control synthetic chart sequential probability ratio test MEWMA chart hotelling's T Normal distribution Control charts Comparative studies Production management Operations research Multivariate analysis Chen, Nan oth Khoo, Michael B.C oth Enthalten in International journal of production research London : Taylor & Francis, 1961 53(2015), 7, Seite 1937-1949 (DE-627)129358835 (DE-600)160477-6 (DE-576)014731150 0020-7543 nnns volume:53 year:2015 number:7 pages:1937-1949 http://dx.doi.org/10.1080/00207543.2014.925601 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207543.2014.925601 http://search.proquest.com/docview/1655577079 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_21 GBV_ILN_26 GBV_ILN_70 GBV_ILN_4126 85.35 AVZ 52.70 AVZ AR 53 2015 7 1937-1949 |
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10.1080/00207543.2014.925601 doi PQ20160617 (DE-627)OLC1963688678 (DE-599)GBVOLC1963688678 (PRQ)c2756-b89c054c3bdb137d0a15ba1a97c4fb164c1501b31379857db8b3334dbfdd0f950 (KEY)0019873020150000053000701937efficientmultivariatecontrolchartingmechanismbased DE-627 ger DE-627 rakwb eng 600 620 330 DNB 85.35 bkl 52.70 bkl Ou, Yanjing verfasserin aut An efficient multivariate control charting mechanism based on SPRT 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. Nutzungsrecht: © 2014 Taylor & Francis 2014 chart statistical process control synthetic chart sequential probability ratio test MEWMA chart hotelling's T Normal distribution Control charts Comparative studies Production management Operations research Multivariate analysis Chen, Nan oth Khoo, Michael B.C oth Enthalten in International journal of production research London : Taylor & Francis, 1961 53(2015), 7, Seite 1937-1949 (DE-627)129358835 (DE-600)160477-6 (DE-576)014731150 0020-7543 nnns volume:53 year:2015 number:7 pages:1937-1949 http://dx.doi.org/10.1080/00207543.2014.925601 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207543.2014.925601 http://search.proquest.com/docview/1655577079 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_21 GBV_ILN_26 GBV_ILN_70 GBV_ILN_4126 85.35 AVZ 52.70 AVZ AR 53 2015 7 1937-1949 |
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10.1080/00207543.2014.925601 doi PQ20160617 (DE-627)OLC1963688678 (DE-599)GBVOLC1963688678 (PRQ)c2756-b89c054c3bdb137d0a15ba1a97c4fb164c1501b31379857db8b3334dbfdd0f950 (KEY)0019873020150000053000701937efficientmultivariatecontrolchartingmechanismbased DE-627 ger DE-627 rakwb eng 600 620 330 DNB 85.35 bkl 52.70 bkl Ou, Yanjing verfasserin aut An efficient multivariate control charting mechanism based on SPRT 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. Nutzungsrecht: © 2014 Taylor & Francis 2014 chart statistical process control synthetic chart sequential probability ratio test MEWMA chart hotelling's T Normal distribution Control charts Comparative studies Production management Operations research Multivariate analysis Chen, Nan oth Khoo, Michael B.C oth Enthalten in International journal of production research London : Taylor & Francis, 1961 53(2015), 7, Seite 1937-1949 (DE-627)129358835 (DE-600)160477-6 (DE-576)014731150 0020-7543 nnns volume:53 year:2015 number:7 pages:1937-1949 http://dx.doi.org/10.1080/00207543.2014.925601 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207543.2014.925601 http://search.proquest.com/docview/1655577079 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_21 GBV_ILN_26 GBV_ILN_70 GBV_ILN_4126 85.35 AVZ 52.70 AVZ AR 53 2015 7 1937-1949 |
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10.1080/00207543.2014.925601 doi PQ20160617 (DE-627)OLC1963688678 (DE-599)GBVOLC1963688678 (PRQ)c2756-b89c054c3bdb137d0a15ba1a97c4fb164c1501b31379857db8b3334dbfdd0f950 (KEY)0019873020150000053000701937efficientmultivariatecontrolchartingmechanismbased DE-627 ger DE-627 rakwb eng 600 620 330 DNB 85.35 bkl 52.70 bkl Ou, Yanjing verfasserin aut An efficient multivariate control charting mechanism based on SPRT 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. Nutzungsrecht: © 2014 Taylor & Francis 2014 chart statistical process control synthetic chart sequential probability ratio test MEWMA chart hotelling's T Normal distribution Control charts Comparative studies Production management Operations research Multivariate analysis Chen, Nan oth Khoo, Michael B.C oth Enthalten in International journal of production research London : Taylor & Francis, 1961 53(2015), 7, Seite 1937-1949 (DE-627)129358835 (DE-600)160477-6 (DE-576)014731150 0020-7543 nnns volume:53 year:2015 number:7 pages:1937-1949 http://dx.doi.org/10.1080/00207543.2014.925601 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207543.2014.925601 http://search.proquest.com/docview/1655577079 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_21 GBV_ILN_26 GBV_ILN_70 GBV_ILN_4126 85.35 AVZ 52.70 AVZ AR 53 2015 7 1937-1949 |
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Ou, Yanjing ddc 600 bkl 85.35 bkl 52.70 misc chart misc statistical process control misc synthetic chart misc sequential probability ratio test misc MEWMA chart misc hotelling's T misc Normal distribution misc Control charts misc Comparative studies misc Production management misc Operations research misc Multivariate analysis An efficient multivariate control charting mechanism based on SPRT |
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600 620 330 DNB 85.35 bkl 52.70 bkl An efficient multivariate control charting mechanism based on SPRT chart statistical process control synthetic chart sequential probability ratio test MEWMA chart hotelling's T Normal distribution Control charts Comparative studies Production management Operations research Multivariate analysis |
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ddc 600 bkl 85.35 bkl 52.70 misc chart misc statistical process control misc synthetic chart misc sequential probability ratio test misc MEWMA chart misc hotelling's T misc Normal distribution misc Control charts misc Comparative studies misc Production management misc Operations research misc Multivariate analysis |
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ddc 600 bkl 85.35 bkl 52.70 misc chart misc statistical process control misc synthetic chart misc sequential probability ratio test misc MEWMA chart misc hotelling's T misc Normal distribution misc Control charts misc Comparative studies misc Production management misc Operations research misc Multivariate analysis |
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An efficient multivariate control charting mechanism based on SPRT |
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efficient multivariate control charting mechanism based on sprt |
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An efficient multivariate control charting mechanism based on SPRT |
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This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. |
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This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. |
| abstract_unstemmed |
This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling's T 2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling's T 2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme. |
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An efficient multivariate control charting mechanism based on SPRT |
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