Title: Machining parameter optimisation of Al/SiCp composite materials using artificial neural networks
Authors: N.C. Brintha; Shajulin Benedict; J.T. Winowlin Jappes
Addresses: Department of Computer Science, PonJesly Engineering College, Parvathipuram, Nagercoil – 629 003, Kanyakumari District, Tamilnadu, India ' Department of Computer Science, St. Xaviers Catholic College of Engineering, Chunkankadai, Kanyakumari – 629 807, Tamilnadu, India ' Department of Mechanical Engineering, Cape Institute of Technology, Levengipuram, Rajakrishnapuram Post, Tirunelveli District – 627114, Tamil Nadu, India
Abstract: Composite materials have received potential applications in different fields. The major problem encountered during the machining of composite materials is the flank wear and surface roughness. For this study, metal matrix composite material namely Al/SiCp was considered. Mathematical modelling and experimentation results on the effect of wear and surface roughness were presented. In this work, neural network has been used for machining parameter optimisation. On comparing the results produced from neural network model and mathematical modelling, the results of neural network model were found to be more accurate and nearer to the experimental values.
Keywords: metal matrix composites; MMCs; machining parameters; parameter optimisation; artificial neural networks; ANNs; mathematical modelling; flank wear; surface roughness; surface quality.
International Journal of Computer Aided Engineering and Technology, 2015 Vol.7 No.1, pp.2 - 14
Published online: 17 Nov 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article