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An Investigation of the Laser Welding Process for Dual-Phase Steel via Regression Analysis
Author(s) -
Dawei Zhao,
Mikhail Ivanov,
Yuanxun Wang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/969/1/012094
Subject(s) - welding , laser beam welding , electric resistance welding , materials science , mechanical engineering , process (computing) , computer science , composite material , engineering , operating system
In this work, a systematic investigation was undertaken to explore the effects of welding process parameters on the mechanical performances of the welding joints in the laser welding process for DP600. Welding experiments were arranged by a uniform experimental design method with four control factors (laser power, welding speed, focal point position, and side-blowing shield gas flow). The tensile strength of the welding joints was used to quantify the welding quality. A mathematical model based on stepwise regression analysis was employed to correlate the welding process parameters and the tensile strength. The effects of the welding process parameters on the welding quality were discussed. The genetic algorithm was then employed to select the optimum welding parameters. The verification test results proved that the method proposed in this paper could effectively evaluate and optimize the welding quality within the range of process parameters, which could enhance the welding performance in the laser welding process as feasibly and effectively as possible.

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