Experimental Investigations of Oxidation Formation During Pulsed Laser Surface Structuring on Stainless Steel AISI 304

Laser surface texturing (LST) structures or laser-induced periodic surface structures (LIPSS) are typically created using laser pulses with durations ranging from femtoseconds to nanoseconds. However, nanosecond pulsed lasers, as cost-effective and more productive alternatives, can also be used to generate LST structures on stainless steel (SS) surfaces, making these structures more suitable for industrial applications. In this study, pulsed laser processing is employed to create LST structures on SS (AISI 304), with varying pulse and accumulated fluences, effective pulse counts, and scan parameters, such as pulse-to-pulse distance (pitch) and hatch spacing between scanning lines. A methodology for calculating oxidation density on processed AISI 304 surfaces is presented. Oxidation density, defined as the ratio of the oxidized area to the total processed area, is determined as a function of accumulated fluence, laser power, pulse-to-pulse distance, and hatch spacing. Optical images of the surfaces are analyzed, and oxidation regions are identified using machine learning techniques. The images are converted to grayscale, and machine learning algorithms are applied to classify the images into oxidation and non-oxidation regions based on pixel intensity values. This approach identifies the optimal threshold for separating the two regions by maximizing inter-class variance. Experimental modeling using response surface methodology is applied to experimentally generated data. Optimization algorithms are then employed to determine the process parameters that maximize pulsed laser irradiation performance while minimizing surface oxidation and processing time. This paper also presents a novel method for characterizing oxidation density using image segmentation and machine learning. The results provide a comprehensive understanding of the process and offer optimized models, contributing valuable insights for practical applications.