Abstract
Laser welding, a key and competitive technology for advanced industrial manufacturing is powered by energy. With increasing attention to energy management and environmental protection in manufacturing, reducing energy consumption is imperative. However, the traditional optimization of laser welding has been mainly focused on welding quality without considering the total energy consumption of all components. Thus, this paper researches the relationship between welding quality and energy consumption by optimizing process parameters during the 2 mm thickness 6061 aluminum alloy laser welding. Firstly, a three-factor, three-level experiment using Central Composite Design (CCD) is constructed. Secondly, Kriging models are employed to construct the models between process parameters and objectives. Finally, the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) is utilized to minimize energy consumption while maintaining good welding quality. The study shows that compared to the initial scenario, optimization can reduce energy consumption while increasing welding quality.
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