Loading

Optimization of Responses MRR and HC in EDM of Al/4.6B4C super alloy using GA
Mahendra Raj Singh1, Pankaj Kumar Shrivastava2
1Mahendra Raj Singh*, Mechanical Engineering Department, AKS University, Satna, Madhya Pradesh, India.
2Pankaj Kumar Shrivastava, Mechanical Engineering Department, AKS University, Satna, Madhya Pradesh, India.
Manuscript received on March 01, 2020. | Revised Manuscript received on March 10, 2020. | Manuscript published on March 15, 2020. | PP: 1-5 | Volume-6, Issue-5, March 2020. | Retrieval Number: D1192036520/2020©BEIESP | DOI: 10.35940/ijisme.D1192.036520
Open Access | Ethics and Policies | Cite
© 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: Aluminium metal matrix super alloy belongs to advanced category of super alloy which finds wide place in numerous important industry such as aerospace, automobile, missiles etc. because of its elevated mechanical, physical and chemical properties. The innovative manufacturing processes have come into existence to machine such kinds of newer super alloys. Electric discharge machining (EDM) is such a process which is comprehensively applied these days for machining of AMMCs. In the present research the EDM experimentation on Al/4.6B4C composites by considering discharge current, Ton and Toff as process performances have been conducted. The material removal rate and micro hardness have been considered as process output parameters. The RSMs has been developed for both the responses and finally single objective optimization of both the response parameters have been done by applying RSM- genetic algorithm-based optimization (GA) approach. It has been observed that GA gives better results.
Keywords: EDM, GA, response surface model, optimization.