NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES
The failure rate analysis of brake assemblies of a commercial airplane, i.e., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are us...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
2020
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/484/1/Paper_for_ACTA_Press_IJMS.pdf |
| الوسوم: |
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| _version_ | 1864513388520931328 |
|---|---|
| author | Al-Garni, Ahmed Z. |
| author2 | Jamal, Ahmad unknown |
| author2_role | author author |
| author_facet | Al-Garni, Ahmed Z. Jamal, Ahmad unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Al-Garni, Ahmed Z. Jamal, Ahmad unknown |
| dc.date.*.fl_str_mv | 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/484/1/Paper_for_ACTA_Press_IJMS.pdf NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES. International Journal of Modeling and simulation. (Submitted) |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Acta Press |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/484/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Aerospace |
| dc.title.none.fl_str_mv | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| dc.type.none.fl_str_mv | Article NonPeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | The failure rate analysis of brake assemblies of a commercial airplane, i.e., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. Three years of data are used for model building and validation. The results show that the failure rate predicted by neural network is closer in agreement with the actual data than the failure rate predicted by the Weibull model. Results also indicate that neural network can be effectively integrated into aviation cost effective maintenance facility computerized material requirement planning system to forecast the number of brake assemblies needed for a given planning horizon. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_2c4ed452afce3254bb9332179b870acf |
| identifier_str_mv | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES. International Journal of Modeling and simulation. (Submitted) |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::484 |
| publishDate | 2020 |
| publisher.none.fl_str_mv | Acta Press |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKESAl-Garni, Ahmed Z.Jamal, AhmadunknownAerospaceThe failure rate analysis of brake assemblies of a commercial airplane, i.e., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. Three years of data are used for model building and validation. The results show that the failure rate predicted by neural network is closer in agreement with the actual data than the failure rate predicted by the Weibull model. Results also indicate that neural network can be effectively integrated into aviation cost effective maintenance facility computerized material requirement planning system to forecast the number of brake assemblies needed for a given planning horizon.Acta PressArticleNonPeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/484/1/Paper_for_ACTA_Press_IJMS.pdf NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES. International Journal of Modeling and simulation. (Submitted) enhttps://eprints.kfupm.edu.sa/id/eprint/484/2020info:eu-repo/semantics/openAccessoai::4842019-11-01T13:24:03Z |
| spellingShingle | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES Al-Garni, Ahmed Z. Aerospace |
| status_str | publishedVersion |
| title | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| title_full | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| title_fullStr | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| title_full_unstemmed | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| title_short | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| title_sort | NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES |
| topic | Aerospace |
| url | https://eprints.kfupm.edu.sa/id/eprint/484/1/Paper_for_ACTA_Press_IJMS.pdf |