Design and Optimization of EDM using Metal Matrix Composite by Genetic algorithm and Jaya Algorithm
Mahendra Raj Singh1, Pushpendra Singh2, Pankaj Kumar Shrivastava3

1Mahendra Raj Singh, Mechanical Engineering Department, AKS University, Satna, Madhya Pradesh, India.
2Pankaj Kumar Shrivastava*, Mechanical Engineering Department, AKS University, Satna, Madhya Pradesh, India.
3Pushpendra Singh, Electrical Engineering Department, Rajkiya Engineering College, Banda, Uttar Pradesh, India.
Manuscript received on January 17, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 3216-3221 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1109029420/2020©BEIESP | DOI: 10.35940/ijitee.D1109.029420
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Abstract: Aluminum Boron carbide (Al-B4C) is a form of metal matrix composite (MMC) belongs to advanced category of material which is gaining popularity now-a-days because of its excellent mechanical and physical properties. Unconventional machining processes (UMPs) are now day’s best options to machine such kinds of modern materials. Electro discharge machining (EDM) process now days the best UMP whichever utilizes thermic energy power of spark for material removal. In present research the EDM has been carried out in Al-B4C MMC by varying different EDM parameters to evaluate material removal rate (MRR) and tool wear rate (TWR). The response surface model (RSM) has been developed for both the MRR and TWR. The developed RSM has been utilized during optimization. Optimizations of responses the MRR and or TWR have been done by using genetic algorithm and jaya algorithm. Finally both the algorithms have been compared with respect to current manufacturing paradigm. 
Keywords: Electric Discharge Machining, Genetic Algorithm, Jaya Algorithm, Metal Matrix Composite.
Scope of the Article: Discrete Optimization