Title: Modelling of turning parameters of Al-Cu/TiB₂ in-situ metal matrix composites using artificial neural network

Authors: P. Senthil; T. Selvaraj; S. Vinodh

Addresses: Department of Production Engineering, National Institute of Technology, Tiruchirappalli 620 015, India. ' Department of Production Engineering, National Institute of Technology, Tiruchirappalli 620 015, India. ' Department of Production Engineering, National Institute of Technology, Tiruchirappalli 620 015, India

Abstract: This article presents a feed forward backpropagation neural network model for predicting the turning parameters of Al-Cu/TiB₂ in-situ metal matrix composites (MMCs). The workpiece material is prepared by casting route and then extruded as cylindrical rod. The experiments are designed using 3³ factorial design and conducted on computer numerical control (CNC) lathe. The input parameters for artificial neural network (ANN) model are cutting speed, feed and depth of cut. The output parameters for the model are tangential and axial forces, surface roughness and material removal rate. The ANN model is trained and tested with a set of input and output parameters. The predicted response values using ANN model are found to be in very good agreement with the untrained experimental values.

Keywords: artificial neural networks; ANNs; Al-Cu; copper; aluminium; TiB2; titanium diboride; metal matrix composites; CNC turning; cutting speed; feed; depth of cut; machining parameters; tangential forces; axial forces; surface roughness; surface quality; material removal rate; MRR; modelling.

DOI: 10.1504/IJAOM.2012.049913

International Journal of Advanced Operations Management, 2012 Vol.4 No.4, pp.272 - 282

Received: 31 Jan 2012
Accepted: 05 Feb 2012
Published online: 11 Aug 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article