Strilets R. Methods and means of ensuring quality indicators in automated control systems for photopolymer 3Dprinting additive technologies

Strilets R. Methods and means of ensuring quality indicators in automated control systems for photopolymer 3Dprinting additive technologies – Qualification scientific work presented as a manuscript. Dissertation submitted for the degree of Doctor of Philosophy in specialty 151 Automation and Computer-Integrated Technologies – Kharkiv National University of Radioelectronics, Ministry of Education and Science of Ukraine, Kharkiv, 2025. The dissertation is devoted to solving a relevant scientific and applied problem related to the development of methods and tools for ensuring quality indicators in control systems for photopolymer additive manufacturing technologies. This objective is achieved by developing a control method for photopolymer 3D-printing and real-time monitoring of the technological process, based on research into the technological parameters of photopolymer printing and the design of a control system aimed at improving the efficiency of the photopolymer 3D-printing process. The dissertation continues the line of research conducted at the Department of Computer-Integrated Technologies, Automation, and Robotics (CITAR) of Kharkiv National University of Radioelectronics under the supervision of the Head of the Department, Doctor of Technical Sciences, Professor, Honored Scientist and Technician of Ukraine, and State Prize Laureate in Science and Technology of Ukraine, Ihor Nevlyudov. Object of the research – the process of automated control in photopolymer 3D-printing. Subject of the research – mathematical models, hardware and software control tools, technical equipment, methods, and automated control systems for photopolymer 3D printing processes. Purpose of the dissertation – to increase the productivity and reduce defects in photopolymer 3D-printing by developing methods and tools for automated control of the photopolymer 3D-printing technological process. Research methods. Stochastic mathematical analysis methods were used to process experimental data, in particular: ‒ multifactor regression analysis to determine the influence of technological factors on output quality indicators; ‒ regression analysis to identify the influence of exposure time and horizontal cross-sectional area on the layer’s separation force from the fluoropolymer film. The results of the regression analysis were further used in the development of control software for photopolymer 3D-printing.