Optimization of Steel Laser Cutting Processes Using the Roughness Parameter Sq and Response Surface Methodology (RSM)

Abstract

Laser cutting of steel is among the most advanced and competitive technologies in metal processing, widely employed in the automotive, aerospace, construction, and electronics industries, as well as in the production of precision components. Its advantages over traditional methods stem from its high precision, cutting speed, and ability to process complex geometries without requiring any subsequent finishing operations. This study presents research on the influence of fiber laser control parameters on the surface quality of S355J2C+N steel cuts. The primary objective is to identify which laser cutting parameters significantly affect the surface roughness of the cut. The response surface methodology (RSM) was employed for modeling. The Sq roughness parameter was selected as the primary metric to assess surface quality. The investigated process control parameters affecting surface roughness included feed rate, focal point position, and peak power. A 2-level split-plot experimental design was used for data analysis, with the focal point position designated as a hard-to-change factor due to the mechanical complexity of optical realignment. A mathematical model of the cutting process was generated. Based on analysis of variance (ANOVA), the model was found to fit the experimental data with an accuracy exceeding 98%. The results indicated that achieving low surface roughness (Sq) requires cutting with the lowest possible feed rate, lowest focal point position, and minimal peak power. The use of RSM facilitates the optimization of control parameter selection, contributing to improved surface quality and process efficiency.