MATEC Web Conf.
Volume 95, 20172016 the 3rd International Conference on Mechatronics and Mechanical Engineering (ICMME 2016)
|Number of page(s)
|Mechanical Processing Technology
|09 February 2017
Laser Welding Process Parameters Optimization Using Variable-Fidelity Metamodel and NSGA-II
The State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
An optimization methodology based on variable-fidelity (VF) metamodels and nondominated sorting genetic algorithm II (NSGA-II) for laser bead-on-plate welding of stainless steel 316L is presented. The relationships between input process parameters (laser power, welding speed and laser focal position) and output responses (weld width and weld depth) are constructed by VF metamodels. In VF metamodels, the information from two levels fidelity models are integrated, in which the low-fidelity model (LF) is finite element simulation model that is used to capture the general trend of the metamodels, and high-fidelity (HF) model which from physical experiments is used to ensure the accuracy of metamodels. The accuracy of the VF metamodel is verified by actual experiments. To slove the optimization problem, NSGA-II is used to search for multi-objective Pareto optimal solutions. The results of verification experiments show that the obtained optimal parameters are effective and reliable.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.