Multi-criteria optimization of laser polishing treatment: Experimentation and RSM – TOPSIS modelling

Laser Surface Polishing (LSP) enhances surface characteristics, yet optimizing parameters for desired outcomes remains challenging. This study emphasizes the crucial role of surface gloss alongside roughness, noting their relationship is not always inverse, which underscore the need for precise parameter control. Prediction and optimization models for gloss and roughness were developed using Response Surface Methodology (RSM) based on a Box-Behnken Design (BBD) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). According to this model, 25 experiments with various combination of laser power, speed, hatching and frequency were conducted on annealed high-chromium stainless steel revealed non-linear relationships. Roughness generally decreased with higher hatching, speed, and frequency but increased with power. In the series of 25 experiments, the optimal combination of laser parameters—70% hatching, 6 W power, 900 mm/s speed, and 120 kHz frequency—was identified in Run 20. This specific experiment achieved both maximum gloss and minimal roughness. In contrast, suboptimal combinations, such as those in Run 5, severely degraded surface quality. The predictive models developed from these experiments demonstrated reasonable accuracy. Selected laser-treated surfaces (Runs 20, 12, 5) and the base material underwent comprehensive mechanical, chemical, and tribological analyses. Hardness varied with processing, with Run 5 showing the highest and Run 20 the lowest hardness. Tribological tests showed that wear rate on optimal laser-polished surfaces was significantly higher (106-205%) in the parallel direction than the perpendicular direction relative to the laser lines. Furthermore, the highest wear rate was not consistently coupled with the highest coefficient of friction. This suggests different wear mechanisms depending on wear direction relative to laser lines and surface characteristics, even with dominant abrasive wear. This research underscores the complexity of LSPT optimization and provides valuable models for achieving superior aesthetic and functional surface finishes. • Investigated laser parameters' effect on gloss and surface roughness. • Developed predictive models using RSM-BBD and TOPSIS for gloss and roughness. • Identified non-linear relationships for both gloss and roughness, and ranked surfaces. • Conducted mechanical, chemical, and tribological analyses on selected surfaces. • The highest wear rate occurring in the parallel direction to laser lines.