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Title: An artificial intelligence approach for the prediction of surface roughness in Co<inf>2</inf> laser cutting
Authors: Madić, Miloš 
Radovanović, Miroslav 
Issue Date: 1-Dec-2012
Journal: Journal of Engineering Science and Technology
Abstract: In laser cutting, the cut quality is of great importance. Multiple non-linear effects of process parameters and their interactions make very difficult to predict cut quality. In this paper, artificial intelligence (AI) approach was applied to predict the surface roughness in CO2 laser cutting. To this aim, artificial neural network (ANN) model of surface roughness was developed in terms of cutting speed, laser power and assist gas pressure. The experimental results obtained from Taguchi's L25 orthogonal array were used to develop ANN model. The ANN mathematical model of surface roughness was expressed as explicit nonlinear function of the selected input parameters. Statistical results indicate that the ANN model can predict the surface roughness with good accuracy. It was showed that ANNs may be used as a good alternative in analyzing the effects of cutting parameters on the surface roughness. © School of Engineering, Taylor's University.
ISSN: 18234690
Appears in Collections:Naučne i umetničke publikacije

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