Využití umělé inteligence a strojového učení v aditivních technologiích

Abstract

KUCHARIČ, Lukáš. The Use of Artificial Intelligence and Machine Learning in Additive Technologies. Ostrava, 2026, Bachelor’s Thesis. Ostrava: VSB – Technical University of Ostrava, Faculty of Mechanical Engineering, Department of Machining, Assembly and Engineering Metrology. Thesis supervisor: Assoc. Prof. Ing. Marek Pagáč, Ph.D.

This bachelor’s thesis addresses the integration of artificial intelligence (AI) and machine learning (ML) into additive manufacturing processes, with a specific focus on Laser Powder Bed Fusion (L-PBF) technology. The theoretical part of the thesis defines the key principles of the L-PBF method and identifies critical process defects, such as porosity or insufficient fusion, which negatively affect the mechanical properties of the final components. The main part of the thesis is devoted to the research and analysis of modern methods for in-situ monitoring of the melt pool. The thesis describes in detail the use of neural networks for automated anomaly detection from thermal images and addresses the technological challenges associated with the transmission of large volumes of data. In this context, the thesis introduces a concept of hybrid computing architecture that combines the advantages of Cloud and Edge Computing to achieve ultra-low latency and enhance the cybersecurity of the manufacturing process. The concluding section of the thesis outlines future trends in the field of explainable artificial intelligence (XAI), which are moving toward fully autonomous quality control in additive technologies.