Journal
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
Volume 27, Issue 7, Pages 2115-2124Publisher
KOREAN SOC MECHANICAL ENGINEERS
DOI: 10.1007/s12206-013-0527-7
Keywords
Genetic algorithm; Kerf taper; Neural network; Optimization; Surface roughness; Titanium alloy
Categories
Ask authors/readers for more resources
Laser cutting of titanium and its alloys is difficult due to it's poor thermal conductivity and chemical reactivity at elevated temperatures. But demand of these materials in different advanced industries such as aircraft, automobile and space research, require accurate geometry with high surface quality. The present research investigates the laser cutting process behavior of titanium alloy sheet (Ti-6Al-4V) with the aim to improve geometrical accuracy and surface quality by minimizing the kerf taper and surface roughness. The data obtained from L-27 orthogonal array experiments have been used for developing neural network (NN) based models of kerf taper and surface roughness. A hybrid approach of neural network and genetic algorithm has been proposed and applied for the optimization of different quality characteristics. The optimization results show considerable improvements in both the quality characteristics. The results predicted by NN models are well in agreement with the experimental data.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available