Optimization of Material Removal Rate in Electric Discharge Machining using Mild Steel
Gaurav Raghav1, B.S. Kadam2, Manjeet Kumar3
1Gaurav Raghav, Department of Mechanical Engineering, Govt. Polytechnic, Manesar, Gurgaon, Haryana, India
2B.S. Kadam, Department of Mechanical Engineering, Govt. Polytechnic, Manesar, Gurgaon, Haryana, India
3Manjeet Kumar, Department of Mechanical Engineering, Govt. Polytechnic, Manesar, Gurgaon, Haryana, India
Manuscript received on May 11, 2013. | Revised Manuscript received on May 15, 2013. | Manuscript published on May 25, 2013. | PP: 42-49 | Volume-1 Issue-7, May 2013. | Retrieval Number: G0312051713/2013©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Published By: 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: This paper aims at achieving the integrated approach to solve the optimization problem of EDM process. At any stage, the dominance factor of the input variables and output variables contained in the constraints and objective functions can be computed. This technique helps in getting the reliable multiobjective decisions under constrained penalties for the constrained optimization of such processes. In the present work, relationships have been developed between the input decision variables and the desired goals by applying the statistical regression analysis of investigations obtained by Electro Discharge machining process for a considerable variation in the crisp sets of variables. The objectives functions were maximized or minimized by using the generalized Genetic Algorithms and the data are stored for a given set of objectives. The results are interpreted with respect to those obtained by using the bi-criterion approach. It is concluded that the results obtained by bi-criterion approach are approximately of the same order of accuracy as calculated experimentally but the computational simplicity of this method makes this methodology favorable to use to solve such mechanical engineering complex problems.
Keywords: EDM, Material removal Rate, Mild Steel, Optimization.