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.
2024-02-24
2024-01-04
2023-11-02
Abstract—In this paper Taguchi method has been applied for optimizing process parameters namely, cutting speed, feed rates and depth of cut during turning of mild steel bar with TIN-coated carbide tools. The analysis of variance (ANOVA) has been applied to identify the significant process parameters influencing material removal rate (MRR). An orthogonal array has been constructed to find the experimental results of machining and further signal-to-noise (S/N) ratio has been computed to construct the analysis of variance (ANOVA) table to study the performance characteristics in dry turning operations. The results of ANOVA analysis have shown that feed has most significant factor on material removal rate (MRR) compare to depth of cut and speed for steel. The confirmation experiments have conducted to validate the optimal parameters and improvement of MRR from initial conditions is 347.2% Index Terms—Taguchi method, Turning, Cutting parameters, ANOVA, MRR
Cite: Sujit Kumar Jha, "Optimization of Process Parameters for Optimal MRR during Turning Steel Bar Using Taguchi Method and Anova," International Journal of Mechanical Engineering and Robotics Research, Vol. 3, No. 3, pp. 231-243, July 2014.
