Optimization Techniques in Turning Operation by using Taguchi Method
S. Mohan Kumar1, K. Kiran Kumar2

1Mr. S Mohan Kumar, Ph.D. Scholar, Department of Mechanical Engineering, Shri JJT University, Jhunjhunu (Rajasthan), India.
2Mr. K Kiran Kumar, Ph.D, Asst. Professor, Department of Mechanical Engineering, AVN Institute of Engineering & Technology, Hyderabad (Telangana), India.

Manuscript received on 10 August 2017 | Revised Manuscript received on 18 August 2017 | Manuscript Published on 30 August 2017 | PP: 57-64 | Volume-6 Issue-6, August 2017 | Retrieval Number: F5120086617/17©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Manufacturing of any product requires different machining processes to get desired finished component. This project refers to the optimization of process parameters in turning process using Taguchi method (L9) in order to obtain efficient Material Removal Rate (MRR). EN 24 is used as workpiece for carrying out experiment to optimize Material Removal Rate which is influenced by three machining parameters namely spindle speed, feed rate and depth of cut. Different experiments are done by varying one parameter and keeping other two fixed so that optimized value of each parameter can be obtained. In this project dry turning operation of EN 24 graded steel is performed using HSS tool. The range of cutting parameters at three levels are spindle speed (200, 350 and 500 rpm), feed rate (0.1, 0.15 and 0.2 mm/rev), depth of cut (1.0, 1.5 and 2.0 mm) respectively. Taguchi method is a good method for optimization of various machining parameters as it reduces number of experiments. Taguchi orthogonal array is designed with three levels of process parameters and ANOVA is applied to know the influence of each parameter on Material Removal Rate. For the given set of conditions, spindle speed influences more on Material Removal Rate followed by feed rate and depth of cut
Keywords: (L9), (MRR), (1.0, 1.5 and 2.0 mm), ANOVA, (200, 350 and 500 rpm), rate (0.1, 0.15 and 0.2 mm/rev),

Scope of the Article: Design Optimization of Structures