Short Title: Int. J. Mech. Eng. Robot. Res.
Frequency: Bimonthly
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.
2024-10-25
2024-09-24
Abstract—Machining operations have been the core of the manufacturing industry since the industrial revolution. The productivity and quality are two important characteristics those control most of the manufacturing processes. Surface roughness imposes one of the most significant constraints for the selection of cutting parameters and machine tools in development of a process. The optimized parameters of machining are important especially to maximize production rate and to reduce cost. In actual practice, all the factors which affect the surface roughness are classified into tool variables, work piece variables and cutting conditions. To this end, a great deal of research has been performed in order to quantify the effect of various turning process parameters to surface quality. In this paper, an attempt is made to review the optimization of surface roughness in turning operations using Taguchi method, which is being applied successfully in industrial applications for optimal selection of process variables in the area of machining. Index Terms—Optimization, Surface roughness, Turning, Significant constraints, Surface quality
Cite: Govindan P and Vipindas M P, "Surface Quality Optimization in Turning Operations Using Taguchi Method-A Review," International Journal of Mechanical Engineering and Robotics Research, Vol. 3, No. 1, pp. 89-118, January 2014.