Laser Paint Removal Process Parameter Optimization via Response Surface Methodology

To study the laser cleaning process and optimize process parameters, a nanosecond pulse laser was used to perform laser cleaning experiments on the acrylic resin paint on the surface of a 304 stainless steel substrate. The surface morphology and elemental composition after paint removal were analyzed by using the scanning electron microscopy and X-ray energy dispersive spectroscopy, and the surface roughness was measured by using a laser confocal microscope. Based on the response surface methodology, a Design-Expert software was used to analyze the effects of laser power, number of scans, and spot overlap rate on the surface morphology, elemental composition, and surface roughness after laser paint removal, and the paint removal process parameters were optimized. The results denote that the spot overlap rate considerably affects the surface composition and that the laser power considerably affects the surface roughness. The optimization results denote that the optimal laser paint removal results can be achieved when the laser power is 19.18 W, the spot overlap rate is 46%, and the number of scans is 3. The experiments show that improved cleaning results can be obtained by selecting suitable process parameters.