Multi Response Optimization on Alsi 410 and En 19 Steel in Turning Operation Using Grey Relational Analysis

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Short Title: Int. J. Mech. Eng. Robot. Res.
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Home > Articles > All Issues > 2014 > Volume 3, No. 2, April 2014 >

V Vignesh Kumar1 , K Raja2, P Marimuthuc3, and K Chandrasekaran2

1.Department of Mechanical Engineering, Anna University, Regional Office, Madurai, Tamil Nadu, India.
2.Department of Mechanical Engineering, University College of Engineering, Anna University, Ramanathapuram, Tamil Nadu, India.
3.Department of Mechanical Engineering, Syed Ammal Engineering College, Ramanathapuram, Tamil Nadu, India.

Abstract— The machining industries are focused primarily on the attainment of high quality, excellent surface finish, high production rate, economy of machining. Surface Roughness (SR) of a product is very essential in determining the quality and Material Removal Rate (MRR) is an important to increase the making rate. In turning operation, there are many parameters such as cutting speed, depth of cut and feed rate that have great force on the response. Optimized cutting parameters are very important for controlling the required SR and MRR. The focal point of present experimental study is to optimize the cutting parameters for CNC turning on AISI410 and EN 19 steel during dry condition. The multi layered of 6 μm with titanium coated cutting inserts is used for turning all the trials. Multi response optimization of cutting parameters is obtained by using Grey Relational Analysis (GRA). Analysis of variance (ANOVA) is engaged to study the performance characteristics of machining parameters. Thus, it is possible to increase machine utilization and reduction of production cost in an automated manufacturing environment.

Index Terms— AISI410, EN19 steel, Grey relational analysis, Material removal rate, Surface roughness, ANOVA

Cite: V Vignesh Kumar, K Raja, P Marimuthuc, and K Chandrasekaran, " Multi Response Optimization on Alsi 410 and En 19 Steel in Turning Operation Using Grey Relational Analysis," International Journal of Mechanical Engineering and Robotics Research, Vol. 3, No. 2, pp. 121-130, April 2014.