Robust optimization for reducing welding-induced angular distortion in fiber laser keyhole welding under process parameter uncertainty
| Autor: | Zhongmei Gao, Yan Wang, Longchao Cao, Seung-Kyum Choi, Qi Zhou |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Engineering Engineering drawing business.industry Monte Carlo method Energy Engineering and Power Technology Laser beam welding Robust optimization 02 engineering and technology Process variable Welding 021001 nanoscience & nanotechnology Industrial and Manufacturing Engineering law.invention symbols.namesake 020901 industrial engineering & automation Control theory law Distortion symbols Uncertainty quantification 0210 nano-technology business Gaussian process |
| Zdroj: | Applied Thermal Engineering. 129:893-906 |
| ISSN: | 1359-4311 |
| DOI: | 10.1016/j.applthermaleng.2017.10.081 |
| Popis: | Welding-induced angular distortion is a typical out-of-plane distortion, which brings negative effects on the joints’ quality. Therefore, the selection of appropriate process parameters to minimize or control welding-induced distortion under uncertainty has become of critical importance. In this paper, a robust process parameter optimization framework is proposed to reduce welding-induced distortion in fiber laser keyhole welding under parameter uncertainty. Firstly, a three-dimensional thermal-mechanical finite element model (FEM) for simulating the welding-induced distortion is developed and validated by laser welding experiment. Secondly, a Gaussian process (GP) model is constructed to build the relationship between the input process parameters and output responses. Finally, uncertainty quantification of both process parameter uncertainty and GP model uncertainty is derived. The obtained uncertainty quantification formulas are used in the robust optimization problem to minimize welding-induced distortion. The effectiveness and reliability of the obtained robust optimum are verified by the Monte Carlo method. |
| Databáze: | OpenAIRE |
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