Open AccessDesign and Optimization of EDM using Metal Matrix Composite by Genetic algorithm and Jaya Algorithm
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d1109.029420
Subject(s) - algorithm , spark (programming language) , electrical discharge machining , machining , metal matrix composite , genetic algorithm , response surface methodology , computer science , composite number , matrix (chemical analysis) , boron carbide , mechanical engineering , materials science , engineering , composite material , machine learning , programming language
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.