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

Luo, Dianyu; Liu, Chunjing; Wang, Chao; Wang, Yunlong; Wang, Xiancai; Zhao, Jing; Jiang, Shichun

doi:10.1016/j.optlastec.2024.111025

Cited by 4 publications

(1 citation statement)

References 28 publications

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“…In practice, NSGA-II combines binary tournament selection, crossover, and mutation to generate new populations and employs an elite strategy to maintain the propagation of superior solutions. It is suitable for finding the Pareto-optimal solution sets and has been widely used to solve complex multi-objective optimization problems [30][31][32]. NSGA-II has several significant advantages over particle swarm optimization [33,34] and other genetic algorithms [35].…”

Section: Optimization Of Surface Quality Characteristics After Cleani...mentioning

confidence: 99%

Multi-Objective Optimization of Laser Cleaning Quality of Q390 Steel Rust Layer Based on Response Surface Methodology and NSGA-II Algorithm

Wang,

Deng,

Lei

et al. 2024

Materials

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To improve the laser cleaning surface quality of rust layers in Q390 steel, a method of determining the optimal cleaning parameters is proposed that is based on response surface methodology and the second-generation non-dominated sorting genetic algorithm (NSGA-II). It involves constructing a mathematical model of the input variables (laser power, cleaning speed, scanning speed, and repetition frequency) and the objective values (surface oxygen content, rust layer removal rate, and surface roughness). The effects of the laser cleaning process parameters on the cleaning surface quality were analyzed in our study, and accordingly, NSGA-II was used to determine the optimal process parameters. The results indicate that the optimal process parameters are as follows: a laser power of 44.99 W, cleaning speed of 174.01 mm/min, scanning speed of 3852.03 mm/s, and repetition frequency of 116 kHz. With these parameters, the surface corrosion is effectively removed, revealing a distinct metal luster and meeting the standard for surface treatment before welding.

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Section: Optimization Of Surface Quality Characteristics After Cleani...mentioning

confidence: 99%

Multi-Objective Optimization of Laser Cleaning Quality of Q390 Steel Rust Layer Based on Response Surface Methodology and NSGA-II Algorithm

Wang,

Deng,

Lei

et al. 2024

Materials

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Analysis and optimization of laser cladding Ti-B4C composite coatings based on the interaction and GABP-NSGAII algorithm

Xiang,

Wang,

Wang

et al. 2024

Surface and Coatings Technology

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Numerical and experimental study of temperature, residual stresses, and microstructural evolution on multi-layer and multi-pass laser cladding of 6061Al alloy

Tang,

Liu,

Song

et al. 2024

Mater. Res. Express

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Multi-layer and multi-pass laser cladding is a promising and important process for repairing and strengthening Al alloy parts, whereas the temperature and residual stresses have a great influence on the properties of the laser cladding layer. In this paper, a nonlinear transient thermo-mechanical coupling finite element model of multi-layer and multi-pass cladding of 6061Al alloy was established. Meanwhile, the DFLUX user subroutine was developed using Fortran code to define the movement of the three-dimensional heat source model. From there, the distribution and evolution of temperature and stresses at different times were investigated. In addition, the micro-morphology and micro-hardness after cladding were also analyzed in detail. The results show that both the maximum residual tensile and compressive stresses decrease with increasing the number of cladding passes. At the same time, due to the reheating effect of each cladding on the previous cladding, a few bubbles appear at the top, middle and bottom of the overlap surfaces. Moreover, the micro-hardness of the overlap surfaces decreases slightly. This study can provide a theoretical basis for further research into multi-layer and multi-pass laser cladding of 6061Al alloy.

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

Cited by 4 publications

References 28 publications

Multi-Objective Optimization of Laser Cleaning Quality of Q390 Steel Rust Layer Based on Response Surface Methodology and NSGA-II Algorithm

Multi-Objective Optimization of Laser Cleaning Quality of Q390 Steel Rust Layer Based on Response Surface Methodology and NSGA-II Algorithm

Analysis and optimization of laser cladding Ti-B4C composite coatings based on the interaction and GABP-NSGAII algorithm

Numerical and experimental study of temperature, residual stresses, and microstructural evolution on multi-layer and multi-pass laser cladding of 6061Al alloy

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