Tehnički vjesnik, Vol. 22 No. 4, 2015.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20140211234150
Multi-objective optimization of cut quality characteristic in CO2 laser cutting stainless steel
Miloš Madić
orcid.org/0000-0002-2310-2590
; Faculty of Mechanical Engineering, University of Niš, Aleksandra Medvedeva 14, 18000 Niš, Serbia
Miroslav Radovanović
; Faculty of Mechanical Engineering, University of Niš, Aleksandra Medvedeva 14, 18000 Niš, Serbia
Bogdan Nedić
orcid.org/0000-0002-4236-3833
; Faculty of Engineering, University of Kragujevac, Sestre Janjić 6, 34000 Kragujevac, Serbia
Vlatko Marušić
; Mechanical Engineering Faculty in Slavonski Brod, J. J. Strossmayer University of Osijek, Trg Ivane Brlić Mažuranić 2, 35000 Slavonski Brod, Croatia
Sažetak
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.
Ključne riječi
analytic hierarchy process; artificial neural networks; CO2 laser cutting; cut quality characteristics; genetic algorithm; multi-objective optimization
Hrčak ID:
143116
URI
Datum izdavanja:
8.8.2015.
Posjeta: 2.664 *