Optimization of Laser Quenching Polishing Composite Process Parameters for ZG45 Cast Steel

TUO Junbo; WANG Chenyang; LIANG Qiang; DU Yanbin; XU Binyuan

doi:10.16490/j.cnki.issn.1001-3660.2025.19.017

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Surface Technology ›› 2025, Vol. 54 ›› Issue (19) : 198-213. DOI: 10.16490/j.cnki.issn.1001-3660.2025.19.017

Surface Strengthening Technology

Optimization of Laser Quenching Polishing Composite Process Parameters for ZG45 Cast Steel

TUO Junbo^1,2, WANG Chenyang¹, LIANG Qiang^1,*, DU Yanbin¹, XU Binyuan¹

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Abstract

The purpose is to simultaneously improve the surface quality of laser polishing and enhance the performance of laser quenching in the context of low-carbon and energy-saving manufacturing. This article proposes a parameter optimization method for the ZG45 cast steel laser quenching and polishing composite process based on the crayfish optimization algorithm (COA). Taking surface roughness, average hardening depth, peak valley difference, and energy consumption during the working process as response objectives, in order to better meet the requirements of machine learning algorithms for dataset uniformity, experiments are designed using Latin hypercube (LHS). Based on Bayesian optimization (BO), a random forest regression model (RF) is used to fit the experimental data, and a prediction model is constructed for the four response objectives. The COA multi-objective optimization algorithm is used to optimize process parameters, to take the minimum values for surface roughness, operating energy consumption, and peak valley difference, as well as the maximum value of the average hardening depth. Under this premise, the response objectives under different parameter combinations are obtained, and the corresponding Parato solution sets are obtained. The TOPSIS method combined with the VIKOR method is used to comprehensively score and rank the Parato solution sets, and the optimal process parameter combination is obtained. After the above evaluation system, the solutions with the highest comprehensive score, namely laser power of 522 W, scanning speed of 12 mm/s, and overlap rate of 70%, are selected for verification experiments in descending order of comprehensive score. The experimental results showed that the error between the predicted value of the model and the actual experimental value does not exceed 11.41%. Moreover, according to the process parameter combination with the highest comprehensive score, the surface roughness Ra after laser quenching polishing decreases from 8.477 μm to 2.585 μm, a decrease of 69.51%; and the surface micro hardness increases from 230HV0.5 to 515.8HV0.5, an increase of 2.24 times; the surface volume wear rate decreases from 24.7×10^-14 m³/(N·m) to 8.7×10^-14 m³/(N·m), a decrease of 64.78%. The energy consumption of laser is mainly related to laser power, scanning speed, and overlap rate, with laser power accounting for the highest proportion. Other parameters mainly affect the overall energy consumption by changing the laser working time. The conventional laser power is determined based on the carbon content of the material. When compared with conventional process parameters (i.e. laser power as a variable) while keeping all other parameters constant, the energy consumption of laser processing under this set of process parameters decreases from 927 J to 864 J, a decrease of 6.8%, the surface roughness is decreased by 9.2%, quenching depth indicated by 7.56%, and the peak valley difference is decreased by 29.89%. Based on the above, the following conclusion can be drawn: the application of COA optimization algorithm can provide reference for the optimization of laser quenching polishing process parameters for other cast steel materials, helping them determine the approximate range of process parameters. And the prediction model based on BO-RF fitting algorithm has good predictive performance for energy consumption in the machining process, high model stability, and can provide model reference for the calculation of carbon emissions in laser processing. The research results can provide strong reference for optimizing the laser quenching polishing composite process parameters of ZG45 cast steel for high-quality and low-energy consumption.

Key words

ZG45 cast steel / laser composite technology / COA multi-objective optimization / Latin hypercube / laser energy consumption / fitting regression

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TUO Junbo, WANG Chenyang, LIANG Qiang, DU Yanbin, XU Binyuan. Optimization of Laser Quenching Polishing Composite Process Parameters for ZG45 Cast Steel[J]. Surface Technology. 2025, 54(19): 198-213 https://doi.org/10.16490/j.cnki.issn.1001-3660.2025.19.017

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Funding

Natural Science Foundation of Chongqing,China (CSTB2025NSCQ-LZX0133); Major Special Fund for Science and Technology in Hubei Province (2023BCA006); Funding for Scientific Research Projects at Chongqing Technology and Business University (1956057, 2156015)