Multi-Objective Optimization of Wire Electrical Discharge Machining of AL 2124/SIC Composite
B Sridhar Reddy1, A.B Koteswara Rao2, G Ranga Janardhana3
1B Sridhar Reddy, Mechanical Engineering Department, Gayatri Vidya Parishad College of Engineering (Autonomous), Visakhapatnam, Andhra Pradesh, India.
2A. B. Koteswara Rao, Mechanical Engineering Department, Gayatri Vidya Parishad College of Engineering (Autonomous), Visakhapatnam, Andhra Pradesh, India.
3G Ranga Janardhana, Mechanical Engineering Department, JNTUA University College of Engineering, Anantapur, Andhra Pradesh, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2155-2163 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9687109119/2019©BEIESP | DOI: 10.35940/ijeat.A9687.109119
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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: The growing demand for the use of high strength to weight alloys in industries for manufacturing complex structures challenges the machinability of such advanced materials. In the present investigation, the machinability of SiC particle reinforced Al 2124 composite was studied on Wire electrical discharge machining (WEDM). The process parameters namely pulse on-time (Ton), pulse off time (Toff), peak current (IP), and servo voltage (SV) were optimized by utilizing the central composite design layout. The output responses such as kerf and material removal rate (MRR) were studied in detail. The single and multi-objective optimization was studied for a combination effect using Derringer’s desirability approach and Genetic Algorithm (GA). The experimental and predicted values for each response were validated at the optimized condition. The experimental results were found in line with the predicted values. Multi objective optimization of kerf and MRR by GA showing better result compared to RSM.
Keywords: Metal matrix composite; Wire electric discharge machining; Central Composite Design; Genetic Algorithm; Kerf; Material removal rate.