| Issue |
MATEC Web Conf.
Volume 144, 2018
International Conference on Research in Mechanical Engineering Sciences (RiMES 2017)
|
|
|---|---|---|
| Article Number | 03006 | |
| Number of page(s) | 8 | |
| Section | Manufacturing Engineering | |
| DOI | https://doi.org/10.1051/matecconf/201814403006 | |
| Published online | 09 January 2018 | |
Surface roughness optimization in machining of AZ31 magnesium alloy using ABC algorithm
NMAM Institute of technology, Nitte - 574110, Karnataka, India
* Corresponding author: gouthamahebbar@nitte.edu.in
Magnesium alloys serve as excellent substitutes for materials traditionally used for engine block heads in automobiles and gear housings in aircraft industries. AZ31 is a magnesium alloy finds its applications in orthopedic implants and cardiovascular stents. Surface roughness is an important parameter in the present manufacturing sector. In this work optimization techniques namely firefly algorithm (FA), particle swarm optimization (PSO) and artificial bee colony algorithm (ABC) which are based on swarm intelligence techniques, have been implemented to optimize the machining parameters namely cutting speed, feed rate and depth of cut in order to achieve minimum surface roughness. The parameter Ra has been considered for evaluating the surface roughness. Comparing the performance of ABC algorithm with FA and PSO algorithm, which is a widely used optimization algorithm in machining studies, the results conclude that ABC produces better optimization when compared to FA and PSO for optimizing surface roughness of AZ 31.
Key words: Surface roughness / optimization / Artificial Bee colony (ABC) / Firefly algorithm (FA) / Particle swarm optimization (PSO)
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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