Journal Article

Study on laser textured surface machining and optimization of process parameters

Li, Zichen, Zhang, Yuxuan, Wang, Linyuan, Zheng, Jingyang, Shi, Shaolin, Mao, Yazhou

2025

Overview

Laser processing parameters are an important factor determining the surface quality during the process of micro pit surface texture forming. Box-Behnken (BBD) and orthogonal method were used to design the parameters of laser machining, as well as the relationship between energy, frequency, pulse width and repetition times on micro pit forming were studied. The response surface method (RSM) model and BP neural network model optimized by gray wolf algorithm (GWO) were established respectively, and the processing parameters were predicted and optimized. The optimal laser processing parameters obtained by GWO-BP model were 333.5 μm and 28.8 μm, which are higher than 254.2 μm and 21.4 μm obtained by RSM model. The results showed that the prediction and optimization ability of the GWO-BP model was better than that of the RSM model, and the BP model optimized by GWO could provide a more effective prediction method for realizing the optimal laser micro pit machining.

• Publisher: Springer Nature B.V
• Subject: Accuracy / Back propagation networks / Efficiency / Experiments / Genetic algorithms / Laser beam texturing / Laser etching / Laser machining / Laser processing / Manufacturing / Morphology / Neural networks / Optimization / Optimization algorithms / Process parameters / Pulse duration / Response surface methodology / Silicon wafers / Simulation / Surface layers / Surface properties / Taguchi methods / Titanium alloys