Miloš Madić, Marko Kovačević, Miroslav Radovanović, Vladislav Blagojević

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Laser cutting is one of the leading non-conventional machining technologies with a wide spectrum of application in modern industry. It order to exploit a number of advantages that this technology offers for contour cutting of materials, it is necessary to carefully select laser cutting conditions for each given workpiece material, thickness and desired cut qualities. In other words, there is a need for process control of laser cutting. After a comprehensive analysis of the main laser cutting parameters and process performance characteristics, the application of the developed software tool “BRUTOMIZER” for off-line control of CO2 laser cutting process of three different workpiece materials (mild steel, stainless steel and aluminum) is illustrated. Advantages and abilities of the developed software tool are also illustrated.


CO2 Laser Cutting, Process Control, Software Tool, Mild Steel, Stainless Steel, Aluminum, Cut Quality

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Madić, M., 2013, Mathematical Modeling and Optimization of Laser Cutting Process Using Artificial Intelligence Methods, (in Serbian), PhD Thesis, Faculty of Mechanical Engineering in Niš, University of Niš.

Ion, J., 2005, Laser Processing of Engineering Materials Principles, Procedure and Industrial Application, Butterworth-Heinemann.

Madić, M., Radovanović, M., Blagojević, V., Kovačević, M., 2014, Off-line control of CO2 laser cutting process using software prototype, XII International SAUM Conference on Systems, Automatic Control and Measurements, Niš, Serbia, November 12th-14th, pp. 124-127.

Rao, R.V., Pawar, P.J., 2009, Modelling and optimization of process parameters of wire electrical discharge machining, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(11), pp. 1431-1440.

Ciurana, J., Arias, G., Özel, T., 2009, Neural network modelling and particle swarm optimization (PSO) of process parameters in pulsed laser micromachining of hardened AISI H13 steel, Materials and Manufacturing Processes, 24(3), pp. 358-368.

Adelmann, B., Hellmann, R., 2011, Fast laser cutting optimization algorithm, Physics Procedia, 12(1), pp.


Pandey, A.K., Dubey, A.K., 2012, Simultaneous optimization of multiple quality characteristics in laser cutting of titanium alloy sheet, Optics and Laser Technology, 44(6), pp. 1858-1865.

Wahab, H., Gröninger, J., 2014, Optimization of laser cutting quality with design of experiments, Laser Technik Journal, 11(5), pp. 27-31.

Gadallah, M.H., Abdu, H.M. 2015, Modeling and optimization of laser cutting operations, Manufacturing Review, 2(1), pp.1-20.

Childs, T., Maekawa, K., Obikawa, T., Yamane, Y., 2000, Metal Machining: Theory and Applications, Butterworth-Heinemann.

Dahotre,N. B., Harimkar, S. P., 2008, Laser Fabrication and Machining of Materials, Springer.

Han, A., Gubencu, D., Pillon, G., 2005, A generalized structure based on systemic principles of the characteristic variables of material laser processing, Optics and Laser Technology, 37(7), pp. 577-581.

Duflou, J.R., Kellens, K., Devoldere, T., Deprez, W., Dewulf, W., 2010, Energy related environmental impact reduction opportunities in machine design: case study of a laser cutting machine, International Journal of Sustainable Manufacturing, 2(1), pp. 80-98.

Madić, M., Radovanović, M., 2013, Application of RCGA-ANN approach for modeling kerf width and surface roughness in CO2 laser cutting of mild steel, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 35(2), pp. 103-110.

Madić, M., Radovanović, M., Kovačević, M., Modeling and optimization of kerf width obtained in CO2 laser cutting of aluminum alloy using discrete Monte Carlo method, Journal of Production Engineering, 18(1), pp. 39-42.



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ISSN: 0354-2025 (Print)

ISSN: 2335-0164 (Online)

COBISS.SR-ID 98732551

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