Open AccessOptimization of aluminum alloy by CO2 laser cutting using genetic algorithm to achieve surface quality
Author(s) -
V. Senthilkumar,
Anbazhagan Nagadeepan,
L. Hubert Tony Raj,
P. Sabarish,
Albert Alexander Stonier
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1055/1/012123
Subject(s) - aerospace , genetic algorithm , surface roughness , aluminium , materials science , laser , thermal , mechanical engineering , surface finish , process (computing) , alloy , machining , laser cutting , quality (philosophy) , multi objective optimization , computer science , metallurgy , engineering , composite material , optics , aerospace engineering , machine learning , physics , meteorology , operating system , philosophy , epistemology
The cutting tool process became one of the uncommon thermal energy-based manufacturing methods used in aerospace and different electronics industries to create complex shapes on different metals and their alloys. This paper presents a genetic algorithm for optimizing wear rate and kerf width mostly during cutting tools of aluminum 6351 CO2. The experiments were based on the design of Box Behnken, which took into account three laser specifications for cutting process. Control of laser beams, cutting speeds and gas pressure. By reducing the surface roughness and kerf width, the optimum parameters for the laser cutting were determined. Our test results reveal that in solving optimization problems, the suggested genetic algorithm is efficient and efficient and can be incorporated into the intelligent production environment.