Abstract

In this study, an efficient approach was proposed to systematically model and optimize the laser small hole cutting process parameters using a hybrid approach for the design of experiment and multi-objective genetic algorithm optimization. The central composite design and response surface methodology were used to effectively model the impact of four main factors: cutting speed, laser power, gas pressure and focal distance on the responses. The responses considered were hole diameter circularity tolerance, spattering and cut kerf width, which were used to evaluate the quality of the laser hole cutting. The regression equations were used to model the effect of process parameters and their interactions on the responses. These regression models were then used as objective functions for optimization. The results show that the focal distance and laser power have had a significant influence on the hole diameter circularity tolerance and the variation in size of the cut kerf. In particular, the melted material spattering rate increased threefold when the focal distance increased from 0.4 to 0.8 mm. The optimization results highlighted that the best outcomes in terms of minimum deviation, spatter, and the cut-kerf width were achieved at low power (between 605 and 685 W) and low speeds (in the range of 11.1–12.7 m min−1). The optimal focal distance for all solutions was found to be 0 mm for the gas pressure (between 6.5 and 8 bars) to minimize the objective functions.

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