The article discusses the problems and solutions of 3D printing and additive manufacturing in the context of the integration of artificial intelligence. With increasing demands for quality and efficiency, artificial intelligence is becoming a key element of process optimization. The factors influencing the suitability of models for 3D printing, including time, cost and materials, are analyzed. Optimization methods such as genetic algorithms and machine learning can simplify testing and evaluation tasks. Genetic algorithms provide flexibility in solving complex problems, improve quality, and reduce the likelihood of errors. In conclusion, the importance of further research on artificial intelligence for improving the productivity and quality of additive manufacturing is emphasized.

Keywords: artificial intelligence, 3D printing, additive manufacturing, machine learning, process optimization, genetic algorithms, product quality, automation, productivity, geometric complexity