* Corresponding author. Tel: +381 18500687 Fax: +381 18 588244 E-mail: madic@masfak.ni.ac.rs (M. Madić) © 2014 Growing Science Ltd. All rights reserved. doi: 10.5267/j.ijiec.2014.9.003 International Journal of Industrial Engineering Computations 6 (2015) 33–42 Contents lists available at GrowingScience International Journal of Industrial Engineering Computations homepage: www.GrowingScience.com/ijiec ANN modeling of kerf taper angle in CO 2 laser cutting and optimization of cutting parameters using Monte Carlo method Miloš Madić a* , Miroslav Radovanović a and Marin Gostimirović b a Faculty of Mechanical Engineering, University of Niš, A. Medvedeva 14, Niš, Serbia b Faculty of Technical Science, University of Novi Sad, Trg Dositeja Obradovića 6, Serbia C H R O N I C L E A B S T R A C T Article history: Received June 6 2014 Received in Revised Format September 9 2014 Accepted September 15 2014 Available online September 22 2014 In this paper, an attempt has been made to develop a mathematical model in order to study the relationship between laser cutting parameters such as laser power, cutting speed, assist gas pressure and focus position, and kerf taper angle obtained in CO 2 laser cutting of AISI 304 stainless steel. To this aim, a single hidden layer artificial neural network (ANN) trained with gradient descent with momentum algorithm was used. To obtain an experimental database for the ANN training, laser cutting experiment was planned as per Taguchi’s L 27 orthogonal array with three levels for each of the cutting parameters. Statistically assessed as adequate, ANN model was then used to investigate the effect of the laser cutting parameters on the kerf taper angle by generating 2D and 3D plots. It was observed that the kerf taper angle was highly sensitive to the selected laser cutting parameters, as well as their interactions. In addition to modeling, by applying the Monte Carlo method on the developed kerf taper angle ANN model, the near optimal laser cutting parameter settings, which minimize kerf taper angle, were determined. © 2015 Growing Science Ltd. All rights reserved Keywords: CO 2 laser cutting Kerf taper Modeling Optimization Artificial neural network Monte Carlo method 1. Introduction Laser cutting is a thermal energy based advanced machining process which has many applications in industry where a variety of components in large numbers are required to be machined with high quality and close tolerance at low costs. The wide spectrum of industrial application of the laser cutting is due to its convenience of operation, high precision, small heat-affected zone (HAZ), minimum deformity, low cost, high product quality, high cutting speed, low level of noise, flexibility, ease of automation, etc. (Madić & Radovanović, 2013). Due to many advantages that offer, laser cutting technology is area of continuous research and development. A number of analytic, numerical and experimental modeling studies have been carried out in order to analyze the laser cutting process, and some of the findings and possibilities of this cutting technology are summarized in a comprehensive review paper (Dubey & Yadava, 2008).