Modeling and Optimization of EDM of Metal Matrix Composite using Black Hole Algorithm
Shrihar Pandey1, Pankaj Kumar Shrivastava2, Pushpendra Singh3
1Shrihar Pandey, Mechanical Engineering Department, AKS University, Satna – 485001, Madhya Pradesh, India.
2Pankaj Kumar Shrivastava, Mechanical Engineering Department, AKS University, Satna – 485001, Madhya Pradesh, India.
3Pushpendra Singh, Electrical Engineering Department, Rajkiya Engineering College, Banda-210201, Uttar Pradesh, India.
Manuscript received on 13 August 2019. | Revised Manuscript received on 19 August 2019. | Manuscript published on 30 September 2019. | PP: 8094-8100 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6439098319/2019©BEIESP | DOI: 10.35940/ijrte.C6439.098319
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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: Many advanced materials have been developed in the recent past to meet the present day technological demands. Aluminum-boron-carbide (Al-B4C) metal matrix composite (MMCs) is such a material slowly gaining popularity among researchers. The advanced machining processes (AMPs) are best manufacturing method to shape these types of innovative materials. The experimental investigations on Al-B4C MMC using one such AMP known as electrical discharge machining (EDM) have been carried out in the present work. Important electrical parameters of EDM have been considered as input control factors to evaluate two of the most important responses. Four evolutionary optimization techniques; black hole, differential evolution, shuffled frog leaping algorithm and coordinated aggregation based particle swarm optimization is applied to get best out of the process. Finally all the evolutionary optimization techniques have been compared for their performances.
Keywords: Black Hole, Differential Evolution, EDM, MMC
Scope of the Article: Discrete Optimization