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Optimization of welding process parameters by combining Kriging surrogate with particle swarm optimization algorithm

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Abstract

Laser brazing (LB) provides a promising way to join the galvanized steels in automotive industry. The process parameters of LB have significant effects on the bead profile and hence the quality of joint. Since the relationships between the process parameters and bead profiles cannot be expressed explicitly, it is impractical to determine the optimal process parameters intuitively. This paper proposes an optimization methodology by combining Kriging surrogate and particle swarm optimization (PSO) to address the process parameters optimization of the bead profiles in LB with crimping butt of 0.8-mm-thick galvanized steel. Firstly, an experiment using Taguchi L 25 orthogonal array is conducted where welding speed (WS), wire speed rate (WF), and gap (GAP) are taken into consideration as the input parameters, while the bead profiles are the output responses. Secondly, the relationships between the inputs and outputs are established using the Kriging model. Thirdly, the effects of the input parameters on the bead profiles are analyzed, and the global process parameters are obtained by the presented Kriging-PSO approach. At last, the verification experiments were conducted to verify the effectiveness of the optimal values. On the whole, the proposed hybrid method, Kriging-PSO, shows great promise for improving the effectiveness and stability of LB welding process.

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Authors and Affiliations

  1. The State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China

    Ping Jiang, Longchao Cao, Qi Zhou, Zhongmei Gao, Youmin Rong & Xinyu Shao

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  1. Ping Jiang
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  2. Longchao Cao
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  3. Qi Zhou
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Correspondence to Qi Zhou.

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Jiang, P., Cao, L., Zhou, Q. et al. Optimization of welding process parameters by combining Kriging surrogate with particle swarm optimization algorithm. Int J Adv Manuf Technol 86, 2473–2483 (2016). https://doi.org/10.1007/s00170-016-8382-1

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