Failure Rate Analysis of Boeing 737 Brakes Employing Neural Network

(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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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)
Subjects: Aerospace
Department: College of Engineering and Physics > Aerospace Engineering
Depositing User: AHMAD JAMAL
Date Deposited: 15 Mar 2008 14:01
Last Modified: 01 Nov 2019 13:23