NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES. International Journal of Modeling and simulation. (Submitted)
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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 aviation cost effective maintenance facility computerized material requirement planning system to forecast the number of brake assemblies needed for a given planning horizon.
| Item Type: | Article |
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| Subjects: | Aerospace |
| Department: | College of Engineering and Physics > Aerospace Engineering |
| Depositing User: | AHMAD JAMAL |
| Date Deposited: | 19 Mar 2008 07:43 |
| Last Modified: | 01 Nov 2019 13:24 |
| URI: | http://eprints.kfupm.edu.sa/id/eprint/484 |