Multi-objective numerical simulation of geometrical characteristics of laser cladding of cobalt-based alloy based on response surface methodology

Abstract

The objectives of this study are to optimize the key process parameters of laser cladding remanufacturing parts, improve the sealing quality of the hemispherical valve and prolong and improve its service life and reliability. A high-power fiber-coupled semiconductor laser was used to fabricate a single Co-based alloy cladding layer on the pump valve material ZG45 plate. The key process parameters of laser power, scanning speed and powder feeding rate in the process of laser remanufacturing are taken as optimization variables, and the coating width, coating height, coating depth, aspect ratio and dilution rate are taken as response indexes. Based on the response surface analysis method, the central compound experiment is designed using Design-Expert software. The variance analysis of the experimental results is performed, and the regression prediction model of the process parameters relative to the corresponding index is established. Through analysis of the established perturbation diagram and three-dimensional response surface, it is concluded that the main influence factors of melting width and penetration depth are laser power and positive effect, and the main influence factors of melting height are scanning speed and negative effect. The average error of each regression prediction model is lower than 10%. The above research work has important guiding significance for optimizing the process parameters and improving the cladding quality of cobalt-based alloy on ZG45.

Optimization of Repair Process Parameters for Open-Arc Surfacing Welding of Grinding Rolls Based on the Response Surface Method

“…The p values of AB, BC, A 2 , and C 2 were 0.10, 0.14, 0.94, and 0.22, respectively, which are nonsignificant influencing factors, so were removed from the table to ensure the accuracy of the model; in addition, in the expression of the bead height model, A, B, C, AC, and B 2 were found to be significant influencing factors, with p values of AB, BC, A 2 , and C 2 are 0.59, 0.41, 0.12, and 0.09, respectively, making them nonsignificant influencing factors. To ensure the accuracy of the model, these factors were also removed from the model [22]. Thus, the coded value regression equations with the surfacing speed, surfacing voltage, and surfacing current as the variables, and the bead height and the dilution rate as the response values were obtained, namely,…”

An Overview of Technological Parameter Optimization in the Case of Laser Cladding

“…Among them, the three process parameters of laser power, scanning speed, and powder feeding rate are more studied [81]. Cui et al [82] used the response surface methodology to optimize a cobaltbased alloy coating's process parameters. Their work laid the foundation for the setup of the laser cladding processing parameters for multi-track coatings made from cobalt.…”

Effect of Laser Parameters on Surface Texture of Polyformaldehyde and Parameter Optimization

“…During the laser processing, the POM workpiece is placed on a high-precision motion platform, and the pulse laser with high repetition frequency and high energy density is applied to the surface of the workpiece using different laser processing parameters [26], which is radiated on the surface of the specimen according to the set scanning path and causes it to melt and vaporize [27], thus processing the elliptical texture with a certain depth. The ultrasonic cleaning device was used to clean the processed samples.…”

“…They analysed the impact of process parameters on various response variables, and experimental results showed that the predictive model had good accuracy. Cui et al [26] established regression prediction models between process parameters and coating width, coating height, coating depth, aspect ratio and dilution rate. The average error between the predicted values of each regression prediction model and the experimentally measured values is less than 10 %.…”