Publication: A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization
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Date
2016
Authors
Ahmad N.
Janahiraman T.V.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
AISI 1045 steel is one of the most widely used steel in the manufacturing industry. In order to have the best quality of turned AISI 1045 steel product, surface roughness is being considered as output parameter. The two purposes of this research are to model the surface roughness using response surface methodology and to compare the different types of optimization approaches in order to identify the optimum surface roughness with particular combination of cutting parameters in turning operation. The result obtained from this study showed that the values from RSMs' prediction are 99.3% similar to the experimental values. While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm. � 2015 IEEE.
Description
Genetic algorithms; Optimization; Particle swarm optimization (PSO); Process control; Taguchi methods; Turning; Aisi 1045 steels; Cutting parameters; Experimental values; Genetic algorithm and particle swarm optimizations; Manufacturing industries; Optimization approach; Response surface methodology; Turning operations; Surface roughness