Title: Optimisation of cutting parameters in CNC turning of EN-19 using tungsten carbide

Authors: M. Suresh; R. Meby Selvaraj; K. Rajkumar; V.M. Saravanan

Addresses: Department of Mechanical Engineering, P.S.R. Engineering College, Sivakasi-626140, Tamil Nadu, India ' Department of Mechanical Engineering, P.S.R. Engineering College, Sivakasi-626140, Tamil Nadu, India ' Department of Mechanical Engineering, P.S.R. Engineering College, Sivakasi-626140, Tamil Nadu, India ' Department of Mechanical Engineering, P.S.R. Engineering College, Sivakasi-626140, Tamil Nadu, India

Abstract: Efficient turning of high performance EN series material can be achieved through proper selection of turning process parameters to minimise surface roughness and maximise the material removal rate. This present paper outlines an experimental study to optimise and study the effects of process parameters in CNC turning on surface roughness of EN19/AISI4140 (medium carbon steel) work material in dry environment conditions. The orthogonal array, signal to noise ratio and regression technique were employed to study the performance characteristics in CNC turning operation. Four machining parameters were chosen as process parameters. They are cutting speed, feed rate, tool nose radius and depth of cut. The experimentation plan was designed using Taguchi's L9 orthogonal array (OA) and Minitab-16 statistical software. Optimal values of process parameters for desired performance characteristics were obtained by Taguchi design of experiment. Moreover prediction models had been developed with the help of regression analysis to find the effect of cutting parameters.

Keywords: Taguchi methods; surface roughness; EN19; cutting speed; tool nose radius; feet rate; depth of cut; material removal rate; MRR; surface quality; optimisation; CNC turning; tungsten carbide; medium carbon steel; orthogonal arrays; signal to noise ratio; SNR; regression; design of experiments; DOE.

DOI: 10.1504/IJCAET.2017.083394

International Journal of Computer Aided Engineering and Technology, 2017 Vol.9 No.2, pp.218 - 228

Received: 22 Aug 2014
Accepted: 01 Dec 2014
Published online: 27 Mar 2017 *

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