Optimization of multilayer laser cladding process parameters based on NSGA-II-MOPSO algorithm

被引:12
作者
Luo, Dianyu [1 ,3 ]
Liu, Chunjing [2 ,3 ,4 ]
Wang, Chao [3 ,4 ]
Wang, Yunlong [3 ,4 ]
Wang, Xiancai [3 ,4 ]
Zhao, Jing [3 ,4 ]
Jiang, Shichun [2 ,5 ]
机构
[1] Anhui Sci & Technol Univ, Coll Mech Engn, Bengbu 233000, Peoples R China
[2] Wenzhou Polytech, Coll Intelligent Mfg, Wenzhou 325035, Peoples R China
[3] Anhui Prov Addit Mfg Engn Res Ctr, Bengbu 233030, Peoples R China
[4] Bengbu Univ, Coll Mech & Vehicle Engn, Bengbu 233030, Peoples R China
[5] Anhui Yucheng Laser Technol Co Ltd, Bengbu 233030, Peoples R China
关键词
17-4PH stainless steel; Multilayer laser cladding; Multi-objective optimization; Hybrid algorithm; Microstructure; PREDICTION;
D O I
10.1016/j.optlastec.2024.111025
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Laser cladding, a surface treatment technique for metals renowned for its combination of high material properties and superior corrosion resistance, is commonly utilized in laser repair processes. However, heat accumulation and rapid heating and cooling will lead to the formation of defects, such as cracks, pores, and thermal stress concentrations in the clad layer. Multi-objective optimization of the process parameters of 17-4PH/B4C coating through multilayer laser cladding was performed with a hybrid approach of RSM-NSGA-II-MOPSO to optimize the efficiency and performance of laser cladding. Numerical investigations arranged using the Box-Behnken design are performed to optimize the design variables, including laser power (A), scanning speed (B), powder feeding speed (C), and lap ratio (D), on the objective functions, including heat-affected zone depth (Z(1)), clad layer thickness (Z(2)), and microhardness (Z(3)). The analysis of correlation and variance demonstrates that the response surface models are sufficiently accurate to predict the objective responses, and the order of influence of each factor on the depth of HAZ is A > B > D > C, that for clad layer thickness is B > D > C > A, and that for microhardness is C > D > A > B. With the regression models constructed by RSM, the NSGA-II-MOPSO is adopted to obtain the Pareto-optimal fronts. Technique for Order of Preference by Similarity to Ideal Solution was used to obtain the optimum solution from Pareto-optimal space. The optimum objective functions are as follows: a HAZ depth of 5.97 mm, a clad layer thickness of 1.20 mm, and a microhardness of 779.2 HV0.2. Meanwhile, the corresponding design variables include a laser power of 1977 W, a scanning speed of 649 mm/min, a powder feeding speed of 0.4 r/min, and a lap rate of 40 %. The validation test showed good agreement between the optimized results and the actual measured values for clad layer HAZ depth, clad layer thickness, and microhardness. The tissue analysis revealed that the grains develop in alignment with the solidification trajectory of the laser cladding, and the cladding interface evolves from dendritic and coarse columnar crystals to fine, nondirectional equiaxed grains. This work offers significant references to laser cladding utilized in laser repair processes.
引用
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页数:14
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