Experimental Investigation and Optimization of EDM Process Parameters on Al6061 by using TOPSIS and Comparison with Genetic Algorithm
S. Siva Sankar1, M. Vijay Kumar Reddy2
1S.Siva Sankar, Assistant Professors, Department of Mechanical Engineering, Annamacharya Institute of Technology & Sciences, Tirupati, Chittoor (Andhra Pradesh), India.
2M.Vijay Kumar Reddy, Assistant Professors, Department of Mechanical Engineering, Annamacharya Institute of Technology & Science, Tirupati, Chittoor (Andhra Pradesh), India.
Manuscript received on 10 January 2019 | Revised Manuscript received on 20 January 2019 | Manuscript Published on 30 January 2019 | PP: 76-83 | Volume-8 Issue-2S2, January 2019 | Retrieval Number: B10170182S219/19©BEIESP
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© 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: Electro Discharge Machining (EDM) is a nontraditional machining process where complex as well as intricate shapes can be machined. Only electrically semi conductive materials can be machined by this method and is one amongst the necessary machining processes for machining high temperature-resistant, strength alloys. For attaining the most effective performance of the EDM method, it’s crucial to hold out constant style responses like Surface Roughness, Material Removal Rate etc. it’s essential to think about most variety of input parameters to induce the higher result.. In the present work, an investigation of the optimization and influence of process variables on Surface Roughness, Removal Rate of Al6061alloy material with the help of electrical discharge machining. Proper setting of these technique parameters were determined by Taguchi methodology victimization four factors every at three levels to know the behavior of characteristics like removal rate of material , Surface Roughness. Finally TOPSIS( Technique for order of preference by similarity to ideal solution) algorithm has been applied for multi-objective victimization of the responses of EDM method on Al6061 alloy. The best effectiveness of the TOPSIS algorithm is compared with the genetic algorithm (GA). It is found that the TOPSIS algorithm behaves better compared to GA with esteem to best possible process response values.
Keywords: EDM, MRR, Surface Roughness, Al6061 Alloy, TOPSIS.
Scope of the Article: Manufacturing Processes