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Failure Rate Analysis of Boeing 737 Brakes Employing Neural Network

Al-Garni, Ahmed Z. and Jamal, Ahmad and Saeed, Farooq and kassem, Ayman H. (2007) Failure Rate Analysis of Boeing 737 Brakes Employing Neural Network. In: 7th AIAA Aviation Technology, Integration and Operations Conference (ATIO), 18 - 20 September 2007, Belfast, Northern Ireland.

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Abstract

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 an aviation maintenance facility computerized material requirement planning system to forecast the number of brake assemblies needed for a given planning horizon.



Item Type:Conference or Workshop Item (Paper)
Date:19 September 2007
Subjects:Aerospace
Divisions:College Of Engineering Sciences > Aerospace Engineering Dept
Creators:Al-Garni, Ahmed Z. and Jamal, Ahmad and Saeed, Farooq and kassem, Ayman H.
Email:algarni@kfupm.edu.sa, ahmadj@kfupm.edu.sa, farooqs@kfupm.edu.sa, akassem@kfupm.edu.sa
ID Code:336
Deposited By:AHMAD JAMAL
Deposited On:15 Mar 2008 17:01
Last Modified:12 Apr 2011 13:05

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