Investigations on Drilling of Multimaterial and Analysis by ANN

Abstract:

This paper presents experimental and analytical investigation on drilling of carbon fibre reinforced plastic and aluminium stacks. The experimental results conducted as per full factorial experimental design reveal that drill diameter and feed rate have significant effects in reducing thrust force and torque while spindle speed has the least effect. The analytical study is based on artificial neural network (ANN) training using feed-forward back propagation network. The correlations obtained by multi-variable regression analysis and ANN, indicate that ANN is more effective than regression analysis.

• Periodical: Key Engineering Materials (Volume 443)
• Pages: 347-352
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.443.347
• Online since: June 2010
• Authors: Vijayan Krishnaraj, Redouane Zitoune, Francis Collombet
• Keywords: CFRP/Aluminium Stack, Drilling, Neural Network (NN), Regression, Thrust Force, Torque

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