Optimizing laser cleaning quality for composite paint layer on aluminum alloy surface using response surface methodology

This research aims to extend the service life of aircraft skins by thoroughly removing the composite layer from 2A12 aluminum alloy surfaces while preserving the integrity of the oxide layer. The continuous CO2 laser cleaning experiments were conducted to analyze the effects of process parameters on paint removal performance. Using Response Surface Methodology (RSM), a relationship model was developed to link key factors, including paint residue amount, surface roughness, paint removal efficiency, and paint deposition amount, with overall paint removal quality and efficiency. The results indicate that laser power and scanning speed significantly impact the amount of paint residue and the efficiency of paint removal. Furthermore, an increase in Y-line spacing and scanning speed leads to an initial decrease, followed by an increase in surface roughness. Excessively large or small Y-line spacing increases the paint deposition amount, while the laser frequency has minimal impact. The optimized parameter combination markedly enhances paint removal effect, ensuring effective preservation of the oxide layer and substrate. Additionally, dynamic adjustments to quality and efficiency weighting enable scenario-based optimization. These findings provide valuable insights into the laser cleaning of composite paint layers on 2A12 aluminum alloy and contribute to advancements in aluminum alloy surface treatment technology.