Process parameter optimization of WC/Inconel 625 metal matrix composites laser cladding based on the Taguchi approach and NSGA-II algorithm

Rafiei, Javad; Soheil Shamaee, Mahsa; Ghasemi, Ahmad Reza

doi:10.1007/s00500-023-09555-1

Cited by 1 publication

(1 citation statement)

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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

View full text Add to dashboard Cite

show abstract

Process parameter optimization of WC/Inconel 625 metal matrix composites laser cladding based on the Taguchi approach and NSGA-II algorithm

Cited by 1 publication

References 57 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

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