Artificial Neural Network System for the Design of Airbag Fabrics

Abstract

Engineered fabric manufacturing needs a thorough understanding of the functional properties and their key control construction parameters. When the relationship between a set of interrelated properties goes out of the complete comprehension of human brain, neural networks could be used to find the unknown function. This article describes the method of applying the artificial neural network for the prediction performance parameters for airbag fabrics. The results of the ANN performance prediction had low prediction error i.e., 12% with all the samples and the artificial neural network based on Error Back-propagation were found promising for a new domain of design prediction technique. The prediction performance of the neural network was based on the amount of training given to it, i.e., the diversity of the data and the amount of data; resulting in better the mapping of the network, and better predictions. Airbag fabrics could be successfully engineered using artificial neural network.

Keywords

airbag fabric design engineering neural network back-propagation algorithm edgecomb resistance specific packability.

References

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