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Title: Multi-objective optimization of cut quality characteristics in CO<inf>2</inf> laser cutting of stainless steel
Authors: Madic, Milos
Radovanović M.
Nedic, Bogdan
Marušić V.
Journal: Tehnicki Vjesnik
Issue Date: 1-Aug-2015
Abstract: © 2015, Strojarski Facultet. All rights reserved. In this paper, multi-objective optimization of the cut quality characteristics in CO2 laser cutting of AISI 304 stainless steel was discussed. Three mathematical models for the prediction of cut quality characteristics such as surface roughness, kerf width and heat affected zone were developed using the artificial neural networks (ANNs). The laser cutting experiment was planned and conducted according to the Taguchi’s L27 orthogonal array and the experimental data were used to train single hidden layer ANNs using the Levenberg-Marquardt algorithm. The ANN mathematical models were developed considering laser power, cutting speed, assist gas pressure, and focus position as the input parameters. Multi-objective optimization problem was formulated using the weighting sum method in which the weighting factors that are used to combine cut quality characteristics into the single objective function were determined using the analytic hierarchy process method.
Type: Article
DOI: 10.17559/TV-20140211234150
ISSN: 13303651
SCOPUS: 84938882647
Appears in Collections:Faculty of Engineering, Kragujevac
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