Open AccessOptimization of Materials EN31, SAE8620 and EN9 using Genetic Algorithm
Author(s) -
Jaspreet Singh,
Onkar Singh Bhatia
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40498
Subject(s) - surface roughness , radius , machining , materials science , genetic algorithm , composite material , surface finish , mechanical engineering , algorithm , computer science , mathematics , metallurgy , engineering , mathematical optimization , computer security
Abstract: The study presents the influence of various process parameters such as machining force, surface roughness, cutting force, material removal rate for three different steel materials EN31, SAE8620 and EN9. The analysis shows that feed rate directly affects the hardness, nose radius/ depth cut or cutting speed effectively. Surface roughness is affected mostly by the feed rate. Genetic algorithm is used as an optimization approach to optimize for both rough as well as finished material. For machine surface analysis XRD process is performed, which is followed by the SEM analysis. Higher heat is observed while cutting material with high speed. White layer depth is increased as the tool nose radius increases, same effect is observed for larger feed. Keywords: Hard Turning, Genetic algorithm, ANOVA, EN31, SAE8620 and EN9.