DOI: 10.22184/1993-7296.FRos.2026.20.2.138.149
This article proposes an approach to developing an intelligent decision-­making system for optimizing the laser processing conditions for titanium alloys to achieve a specified surface microgeometry. The need to obtain a unified structured database of laser-­material interaction results is substantiated. An approach to the automated experimental data collection and analysis based on the machine vision and image segmentation algorithms is proposed. The initial results of the system’s operation for automatic labeling of data obtained by the nanosecond laser irradiation of VT1-0 titanium alloy samples are given. It is shown that the automated system enables highly accurate classification of the impact areas, while distinguishing between the heat-affected zone and undamaged material and measuring their geometric parameters. The proposed approach opens up potential for developing the intelligent systems capable of quickly and efficiently predicting laser processing results and recommending the optimal process modes.