Optimization of CNC Turning Process Parameters for Prediction of Surface Roughness through Taguchis Parametric Design Approach

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ISSN: 2278-0149 (Online)
Short Title: Int. J. Mech. Eng. Robot. Res.
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Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.

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D Kanakaraja1 , D Anjan Kumar Reddy1, M Adinarayana1, and L Vamsi Krishna Reddy2

1.Department of Mechanical Engg., Sir Vishveshwaraiah Institute of Science and Technology, Madanapalli, Andhra Pradesh, India.
2.Department of Mechanical Engg., Sri Srinivasa Ramanujan Institute of Technology, Rotarypuram, Anantapuramu, Andhra Pradesh, India.

Abstract—Metal cutting operations still represent the largest class of manufacturing operations where turning is the most commonly employed material removal process and there are lots of studies to investigate this complex process in both academic and industrial world. Predicting the better cutting condition during turning is of great importance as it helps in getting the Surfaces quality before machining starts. The major indication of surfaces quality on machined parts is surface roughness. Again, optimization of cutting parameters is one of the most important elements in any process planning of metal parts as economy of machining operation plays a key role in gaining competitive advantage. This paper presents an experimental study of main cutting condition in turning of SAE 8822 Alloy steel work and finding the influence of turning parameters during turning. For experimentation over this proposed work, a CNC turning centre would be engaged for machining the SAE 8822 Alloy steel work piece material with carbide cutting tool insert with a set of values for the given parameters. The experimentation is carried out considering three machining parameters: cutting speed, feed rate and depth of cut as independent variables. Design of Experiment (DOE) with Taguchi L9 Orthogonal Array (OA) is used for finding the optimized solution. An attempt has been made to find the influence of turning parameters speed, feed, and depth of cut using Analysis of Variance (ANOVA). Finally, the ranges for best cutting conditions are proposed for serial industrial production.

Index Terms—Optimisation, CNC turning, Surface roughness, Taguchi orthogonal array, ANOVA

Cite: D Kanakaraja, D Anjan Kumar Reddy, M Adinarayana, and L Vamsi Krishna Reddy, "Optimization of CNC Turning Process Parameters for Prediction of Surface Roughness through Taguchis Parametric Design Approach," International Journal of Mechanical Engineering and Robotics Research, Vol.3, No.4, pp. 708-714, October 2014.