Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model

Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity...
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Autor*in:	Faiyetole, Ayodele Adekunle [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Survival analysis Human reliability Software reliability Reparameterization Hazard ratio Max 8 crash

Anmerkung:	© Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Aerospace systems - Singapore : Springer Singapore, 2018, 6(2023), 2 vom: 10. März, Seite 259-283
Übergeordnetes Werk:	volume:6 ; year:2023 ; number:2 ; day:10 ; month:03 ; pages:259-283

Links:	Volltext

DOI / URN:	10.1007/s42401-023-00202-z

Katalog-ID:	SPR051805987

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520			\|a Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events.
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912			\|a GBV_ILN_110
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_266
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
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912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
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912			\|a GBV_ILN_2015
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912			\|a GBV_ILN_2026
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912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
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912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
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912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
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912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
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912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
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912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
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912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
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912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
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allfields	10.1007/s42401-023-00202-z doi (DE-627)SPR051805987 (SPR)s42401-023-00202-z-e DE-627 ger DE-627 rakwb eng Faiyetole, Ayodele Adekunle verfasserin (orcid)0000-0001-8103-0663 aut Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. Survival analysis (dpeaa)DE-He213 Human reliability (dpeaa)DE-He213 Software reliability (dpeaa)DE-He213 Reparameterization (dpeaa)DE-He213 Hazard ratio (dpeaa)DE-He213 Max 8 crash (dpeaa)DE-He213 Enthalten in Aerospace systems Singapore : Springer Singapore, 2018 6(2023), 2 vom: 10. März, Seite 259-283 (DE-627)1035875527 (DE-600)2946651-9 2523-3955 nnns volume:6 year:2023 number:2 day:10 month:03 pages:259-283 https://dx.doi.org/10.1007/s42401-023-00202-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2023 2 10 03 259-283
spelling	10.1007/s42401-023-00202-z doi (DE-627)SPR051805987 (SPR)s42401-023-00202-z-e DE-627 ger DE-627 rakwb eng Faiyetole, Ayodele Adekunle verfasserin (orcid)0000-0001-8103-0663 aut Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. Survival analysis (dpeaa)DE-He213 Human reliability (dpeaa)DE-He213 Software reliability (dpeaa)DE-He213 Reparameterization (dpeaa)DE-He213 Hazard ratio (dpeaa)DE-He213 Max 8 crash (dpeaa)DE-He213 Enthalten in Aerospace systems Singapore : Springer Singapore, 2018 6(2023), 2 vom: 10. März, Seite 259-283 (DE-627)1035875527 (DE-600)2946651-9 2523-3955 nnns volume:6 year:2023 number:2 day:10 month:03 pages:259-283 https://dx.doi.org/10.1007/s42401-023-00202-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2023 2 10 03 259-283
allfields_unstemmed	10.1007/s42401-023-00202-z doi (DE-627)SPR051805987 (SPR)s42401-023-00202-z-e DE-627 ger DE-627 rakwb eng Faiyetole, Ayodele Adekunle verfasserin (orcid)0000-0001-8103-0663 aut Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. Survival analysis (dpeaa)DE-He213 Human reliability (dpeaa)DE-He213 Software reliability (dpeaa)DE-He213 Reparameterization (dpeaa)DE-He213 Hazard ratio (dpeaa)DE-He213 Max 8 crash (dpeaa)DE-He213 Enthalten in Aerospace systems Singapore : Springer Singapore, 2018 6(2023), 2 vom: 10. März, Seite 259-283 (DE-627)1035875527 (DE-600)2946651-9 2523-3955 nnns volume:6 year:2023 number:2 day:10 month:03 pages:259-283 https://dx.doi.org/10.1007/s42401-023-00202-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2023 2 10 03 259-283
allfieldsGer	10.1007/s42401-023-00202-z doi (DE-627)SPR051805987 (SPR)s42401-023-00202-z-e DE-627 ger DE-627 rakwb eng Faiyetole, Ayodele Adekunle verfasserin (orcid)0000-0001-8103-0663 aut Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. Survival analysis (dpeaa)DE-He213 Human reliability (dpeaa)DE-He213 Software reliability (dpeaa)DE-He213 Reparameterization (dpeaa)DE-He213 Hazard ratio (dpeaa)DE-He213 Max 8 crash (dpeaa)DE-He213 Enthalten in Aerospace systems Singapore : Springer Singapore, 2018 6(2023), 2 vom: 10. März, Seite 259-283 (DE-627)1035875527 (DE-600)2946651-9 2523-3955 nnns volume:6 year:2023 number:2 day:10 month:03 pages:259-283 https://dx.doi.org/10.1007/s42401-023-00202-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2023 2 10 03 259-283
allfieldsSound	10.1007/s42401-023-00202-z doi (DE-627)SPR051805987 (SPR)s42401-023-00202-z-e DE-627 ger DE-627 rakwb eng Faiyetole, Ayodele Adekunle verfasserin (orcid)0000-0001-8103-0663 aut Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. Survival analysis (dpeaa)DE-He213 Human reliability (dpeaa)DE-He213 Software reliability (dpeaa)DE-He213 Reparameterization (dpeaa)DE-He213 Hazard ratio (dpeaa)DE-He213 Max 8 crash (dpeaa)DE-He213 Enthalten in Aerospace systems Singapore : Springer Singapore, 2018 6(2023), 2 vom: 10. März, Seite 259-283 (DE-627)1035875527 (DE-600)2946651-9 2523-3955 nnns volume:6 year:2023 number:2 day:10 month:03 pages:259-283 https://dx.doi.org/10.1007/s42401-023-00202-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2023 2 10 03 259-283
language	English
source	Enthalten in Aerospace systems 6(2023), 2 vom: 10. März, Seite 259-283 volume:6 year:2023 number:2 day:10 month:03 pages:259-283
sourceStr	Enthalten in Aerospace systems 6(2023), 2 vom: 10. März, Seite 259-283 volume:6 year:2023 number:2 day:10 month:03 pages:259-283
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Survival analysis Human reliability Software reliability Reparameterization Hazard ratio Max 8 crash
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container_title	Aerospace systems
authorswithroles_txt_mv	Faiyetole, Ayodele Adekunle @@aut@@
publishDateDaySort_date	2023-03-10T00:00:00Z
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author	Faiyetole, Ayodele Adekunle
spellingShingle	Faiyetole, Ayodele Adekunle misc Survival analysis misc Human reliability misc Software reliability misc Reparameterization misc Hazard ratio misc Max 8 crash Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model
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topic_title	Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model Survival analysis (dpeaa)DE-He213 Human reliability (dpeaa)DE-He213 Software reliability (dpeaa)DE-He213 Reparameterization (dpeaa)DE-He213 Hazard ratio (dpeaa)DE-He213 Max 8 crash (dpeaa)DE-He213
topic	misc Survival analysis misc Human reliability misc Software reliability misc Reparameterization misc Hazard ratio misc Max 8 crash
topic_unstemmed	misc Survival analysis misc Human reliability misc Software reliability misc Reparameterization misc Hazard ratio misc Max 8 crash
topic_browse	misc Survival analysis misc Human reliability misc Software reliability misc Reparameterization misc Hazard ratio misc Max 8 crash
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title	Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model
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title_full	Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model
author_sort	Faiyetole, Ayodele Adekunle
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title_sort	accident propensity assessment of boeing 737 aircraft variants using the gompertz distribution model
title_auth	Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model
abstract	Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract Aircraft is a socio-technical system with some unavoidable accidents due to its complexity. Although Boeing 737 Aircraft was the best-selling commercial airliner, a relatively new variant, Max 8, suffered two rapidly successive mishaps, serving as a motivation for this study. The propensity of 737 to accidents considering some predictors, is, therefore, objectified. Specifically, it examined accidents involving 737 Aircraft variants from 1970 to 2021. Cox proportional hazards regression model and Weibull distribution model were considered but Gompertz distribution models, with the best goodness-of-fit for the data, were applied to estimate Aircraft survival functions and hazard ratios, with interactions per airline, causes of accidents, and fatality rates. The study showed that the survivability of 737–100 outperformed all the other series, while Max 8 had a high hazard ratio when interacting with the airline operator factor, i.e., management or ownership. Reparameterization of Aircraft–predictor interactions show different significance levels in that airline management or ownerships contribute a long way to accidents. The high cost of Aircraft maintenance is a strong determinant of accidents. The reparameterized results further show that pilot errors significantly contribute to accidents. This investigation suggests that although two Max 8 failed with a 100% fatality rate, 737 was generally safe. The study concludes that the trend toward intuitive and accurate components diagnostics beyond the prognostic and health management approach should be invigorated. In addition, despite the rigorous certification process embarked upon by the FAA, it is suggested that intuitive human reliability analysis regarding the human–machine team, such as flight crews and pilots, and the human failure events be further entrenched in quantifying failure events. © Shanghai Jiao Tong University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model
url	https://dx.doi.org/10.1007/s42401-023-00202-z
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doi_str	10.1007/s42401-023-00202-z
up_date	2024-07-03T23:52:19.520Z
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Accident propensity assessment of Boeing 737 Aircraft variants using the Gompertz distribution model

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