Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model
The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent sys...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ling, Man Ho [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: IEEE transactions on reliability - New York, NY, 1963, 65(2016), 2, Seite 957-968 |
|---|---|
| Übergeordnetes Werk: |
volume:65 ; year:2016 ; number:2 ; pages:957-968 |
| Links: |
|---|
| DOI / URN: |
10.1109/TR.2016.2521766 |
|---|
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OLC1977605001 |
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| 520 | |a The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. | ||
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10.1109/TR.2016.2521766 doi PQ20160719 (DE-627)OLC1977605001 (DE-599)GBVOLC1977605001 (PRQ)c931-a3c8d0a1e15bc46fb36d06d130b4e7440235d892d8e06e68d4551a78b761f77b0 (KEY)0062598120160000065000200957autopsydataanalysisforaseriessystemwithactiveredun DE-627 ger DE-627 rakwb eng 620 DNB Ling, Man Ho verfasserin aut Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. cumulative exposure model Load modeling load-sharing model Autopsy autopsy data exponential distribution Redundancy Active redundancy Maximum likelihood estimation series system Analytical models Data models Ng, Hon Keung Tony oth Chan, Ping Shing oth Balakrishnan, Narayanaswamy oth Enthalten in IEEE transactions on reliability New York, NY, 1963 65(2016), 2, Seite 957-968 (DE-627)129602957 (DE-600)241637-2 (DE-576)015096769 0018-9529 nnns volume:65 year:2016 number:2 pages:957-968 http://dx.doi.org/10.1109/TR.2016.2521766 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7407428 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 GBV_ILN_4310 AR 65 2016 2 957-968 |
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10.1109/TR.2016.2521766 doi PQ20160719 (DE-627)OLC1977605001 (DE-599)GBVOLC1977605001 (PRQ)c931-a3c8d0a1e15bc46fb36d06d130b4e7440235d892d8e06e68d4551a78b761f77b0 (KEY)0062598120160000065000200957autopsydataanalysisforaseriessystemwithactiveredun DE-627 ger DE-627 rakwb eng 620 DNB Ling, Man Ho verfasserin aut Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. cumulative exposure model Load modeling load-sharing model Autopsy autopsy data exponential distribution Redundancy Active redundancy Maximum likelihood estimation series system Analytical models Data models Ng, Hon Keung Tony oth Chan, Ping Shing oth Balakrishnan, Narayanaswamy oth Enthalten in IEEE transactions on reliability New York, NY, 1963 65(2016), 2, Seite 957-968 (DE-627)129602957 (DE-600)241637-2 (DE-576)015096769 0018-9529 nnns volume:65 year:2016 number:2 pages:957-968 http://dx.doi.org/10.1109/TR.2016.2521766 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7407428 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 GBV_ILN_4310 AR 65 2016 2 957-968 |
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10.1109/TR.2016.2521766 doi PQ20160719 (DE-627)OLC1977605001 (DE-599)GBVOLC1977605001 (PRQ)c931-a3c8d0a1e15bc46fb36d06d130b4e7440235d892d8e06e68d4551a78b761f77b0 (KEY)0062598120160000065000200957autopsydataanalysisforaseriessystemwithactiveredun DE-627 ger DE-627 rakwb eng 620 DNB Ling, Man Ho verfasserin aut Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. cumulative exposure model Load modeling load-sharing model Autopsy autopsy data exponential distribution Redundancy Active redundancy Maximum likelihood estimation series system Analytical models Data models Ng, Hon Keung Tony oth Chan, Ping Shing oth Balakrishnan, Narayanaswamy oth Enthalten in IEEE transactions on reliability New York, NY, 1963 65(2016), 2, Seite 957-968 (DE-627)129602957 (DE-600)241637-2 (DE-576)015096769 0018-9529 nnns volume:65 year:2016 number:2 pages:957-968 http://dx.doi.org/10.1109/TR.2016.2521766 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7407428 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 GBV_ILN_4310 AR 65 2016 2 957-968 |
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10.1109/TR.2016.2521766 doi PQ20160719 (DE-627)OLC1977605001 (DE-599)GBVOLC1977605001 (PRQ)c931-a3c8d0a1e15bc46fb36d06d130b4e7440235d892d8e06e68d4551a78b761f77b0 (KEY)0062598120160000065000200957autopsydataanalysisforaseriessystemwithactiveredun DE-627 ger DE-627 rakwb eng 620 DNB Ling, Man Ho verfasserin aut Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. cumulative exposure model Load modeling load-sharing model Autopsy autopsy data exponential distribution Redundancy Active redundancy Maximum likelihood estimation series system Analytical models Data models Ng, Hon Keung Tony oth Chan, Ping Shing oth Balakrishnan, Narayanaswamy oth Enthalten in IEEE transactions on reliability New York, NY, 1963 65(2016), 2, Seite 957-968 (DE-627)129602957 (DE-600)241637-2 (DE-576)015096769 0018-9529 nnns volume:65 year:2016 number:2 pages:957-968 http://dx.doi.org/10.1109/TR.2016.2521766 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7407428 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 GBV_ILN_4310 AR 65 2016 2 957-968 |
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10.1109/TR.2016.2521766 doi PQ20160719 (DE-627)OLC1977605001 (DE-599)GBVOLC1977605001 (PRQ)c931-a3c8d0a1e15bc46fb36d06d130b4e7440235d892d8e06e68d4551a78b761f77b0 (KEY)0062598120160000065000200957autopsydataanalysisforaseriessystemwithactiveredun DE-627 ger DE-627 rakwb eng 620 DNB Ling, Man Ho verfasserin aut Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. cumulative exposure model Load modeling load-sharing model Autopsy autopsy data exponential distribution Redundancy Active redundancy Maximum likelihood estimation series system Analytical models Data models Ng, Hon Keung Tony oth Chan, Ping Shing oth Balakrishnan, Narayanaswamy oth Enthalten in IEEE transactions on reliability New York, NY, 1963 65(2016), 2, Seite 957-968 (DE-627)129602957 (DE-600)241637-2 (DE-576)015096769 0018-9529 nnns volume:65 year:2016 number:2 pages:957-968 http://dx.doi.org/10.1109/TR.2016.2521766 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7407428 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-WIW GBV_ILN_70 GBV_ILN_4310 AR 65 2016 2 957-968 |
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Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model |
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autopsy data analysis for a series system with active redundancy under a load-sharing model |
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Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model |
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The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. |
| abstractGer |
The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. |
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The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. |
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Autopsy Data Analysis for a Series System With Active Redundancy Under a Load-Sharing Model |
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