Application of Artificial Neural Network (ANN) for Predicting the Wear Behaviour of Al 2219-SiC_p Composite

Abstract:

In the present study, artificial neural network (ANN) model was developed to predict the wear characteristics of Al 2219-SiC_p composite. In the development of predictive model, weight fraction of the reinforcement, sintering temperature, applied normal load on the pin and disc speed were considered as model variables. Full factorial experiments were carried out and observed wear characteristics were taken as input for the model. A feed forward back propagation hierarchical neural network was considered in the study. Out of 81 datasets, 49 sets of data were used for training, 16 sets of data for validation and 16 sets of data for testing. The results exhibit good prediction accuracy of about 85% on average of all wear characteristics and percentage error was within the acceptable limits.

• Periodical: Applied Mechanics and Materials (Volume 852)
• Pages: 397-401
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.852.397
• Online since: September 2016
• Authors: Ganesh Radhakrishnan, Chandrasekaran Kesavan, Vignesh Ramesh, Tamilarasan Anandan
• Keywords: Aluminium Matrix Composites (AMCs), Artificial Neural Network, Sintering Temperature, Wear

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