A MATHEMATICAL MODEL AND PERFORMANCE OF LASER BEAM MACHINING PARAMETERS FOR AUSTENITIC STAINLESS STEEL

Abstract: Laser Beam Machining (LBM) is a high-precision, non-contact material removal process that offers exceptional adaptability and control, especially suited for advanced manufacturing applications. This study investigates the micromachining behavior of Austenitic Stainless Steel (316L) using a pulsed fiber laser to develop a mathematical model that correlates key process parameters, laser power, laser scanning speed, and laser line distance, with machining performance. The primary research question addresses how these parameters influence both process efficiency, represented by material removal rate (MRR), machining time, and product quality, measured through surface roughness, lattice strain, and residual stresses. A series of controlled experiments was conducted in which the parameters above were systematically varied, and the machined surfaces were analyzed using a laser confocal microscope and X-ray diffraction techniques. Regression analysis and response surface methodology were employed to derive predictive equations that model the relationships between input settings and output responses. The results indicate that laser power and scanning speed are the dominant factors influencing MRR and surface finish, while line distance plays a moderate yet significant role. The developed model exhibited high predictive accuracy (R² > 96.31%) across both efficiency and quality metrics, highlighting its robustness. Interaction effects between parameters were also found to be statistically significant, emphasizing the need for multi-variable optimization. This mathematical framework offers valuable insights into process control and optimization, enabling manufacturers to fine-tune LBM operations for enhanced precision and repeatability. The study contributes to the broader field of laser micromachining by providing a validated predictive tool tailored to 316L stainless steel applications.