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Prediction of Laser Cutting Quality Based on an Improved Pareto Genetic Algorithm
H-J. Hao, J-Y. Xu and J. Li

The prediction of laser cutting quality has great significance to improve the precision of a laser cutting machine. An improved Pareto genetic algorithm is proposed in this paper and applied to predict kerf width and material removal rate. pulsed Nd: YAG laser cutting. The theoretical analysis and experimental results show that the new method can be used for prediction of kerf width and material removal rate in pulsed Nd: YAG laser cutting. The study also shows that kerf width and material removal rate are not sensitive to change of single cutting parameter. In the combined parameters, two combination kinds (gas pressure with cutting speed and gas pressure with pulse width) have more obvious effect on kerf width, while the effect of combination of gas pressure with pulse frequency, and gas pressure with cutting speed is more important on material removal rate. This research not only can provide theoretical guidance for prediction and optimization of laser cutting quality, but also can provide parameters for production of high precision machine based on quality prediction.

Keywords: Nd:YAG laser, laser cutting, cut quality, Pareto genetic algorithm, Pareto solution filter, kerf width, material removal rate

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