Multi-Objective Optimization of Laser Cleaning Quality of Composite Paint Layers Based on Response Surface

To improve the laser cleaning surface quality of composite layers on Al alloy surfaces, a method of determining the optimal cleaning parameters is proposed that is based on the response surface methodology. It involves constructing a mathematical model of the input variables (laser power, scanning speed, repetition frequency, and defocusing amount). Laser cleaning experiments were conducted to analyze the effects of process parameters on paint removal performance. Using the response surface methodology (RSM), a relationship model was developed to link key factors, including paint layer removal thickness and surface roughness. The results indicate that the optimal process parameters are as follows: a laser power of 291 W, frequency of repetition of 166 kHz, scanning speed of 8425 mm/s, and defocusing amount of −17 mm. A verification test was performed to confirm the optimal parameters for the process. The error ranges for the thickness and roughness of the laser paint removal were within 1.9 μm~3.8 μm and −0.573 μm~−0.419 μm, respectively, indicating that the response surface method can be used to predict and optimize the quality of laser paint removal. These findings provide valuable insights into the laser treatment of composite paint layers on Al alloys and contribute to advances in surface treatment technology for Al alloys.