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Dinakaran, D.
- Multi Objective Optimization Technique for EDM of INCONEL 718 Alloy
Authors
1 Department of Mechanical Engineering, Hindustan University, Chennai - 603103, Tamilnadu, IN
2 Department of Mechanical Engineering, St. Joseph College of Engineering, Chennai - 603103, Tamilnadu, IN
3 Department of Mechanical Engineering, Hindustan University, Chennai - 603103, Tamilnadu, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 3, No 13 (2011), Pagination: 853-858Abstract
Inconel 718 is a high nickel content super alloy having high strength at elevated temperatures and resistance to oxidation and corrosion. It is very difficult to machine this super alloy by conventional machining technique due to its properties. The nontraditional manufacturing process of Electrical Discharge Machining (EDM) possesses many advantages over traditional manufacturing process due to non contact between cutting tool and work piece. In this study, experiments were conducted on EDM machining of inconel 718work piece material using pure copper 99.9% (Cu) electrode tool material with kerosene as a dielectric fluid.
The objective of this work is to determine individual contribution of process parameters on material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) and to find out the optimum machining parameters of inconel 718 material using desirability approach. The EDM process parameters are Pulse on time(TON),pulse off time(TOFF),peak current (A),flushing pressure(P) along with tool geometry parameters having circle(C), square(S), rectangle(R) and triangle (T) shapes at four levels of L16 orthogonal array are considered as EDM input parameters. Experimental results show that the current is the most influencing factor followed by pulse on time and pulse of time compared to other EDM process parameter. In MRR and SR the pulse on time and peak current are the most influencing EDM parameter where as the pulse off time also important parameter influencing TWR. The single objective optimization used in previous studies gives optimized output among three required outputs. But the multi objective function presented in this work considers all the outputs and is optimized. It is also noted that the rectangular tool geometry gives better results compared with other tool geometry.
