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Information × Registration Number 0225U004675, (0124U003279) , R & D reports Title Machine Learning Enhanced Additive Manufacturing popup.stage_title Відпрацювання базових моделей машинного навчання в робочі спрямованим експериментуванням за стратегією Баєсової оптимізації Head Zhalat-Lozynskyi Ostap B., Доктор технічних наук Registration Date 16-12-2025 Organization Frantsevich Institute for Problems of Materials Science National Academy of Science of Ukraine popup.description1 The goal of the project is to develop a new, data-driven approach to the control of the additive manufacturing process through the application of innovative principles based on machine learning. popup.description2 Within the framework of the project, a significant step has been taken towards improving 3D printing technologies for ceramic products using the robocasting method. The primary challenge of this method lies in the difficulty of predicting the ceramic paste's behavior during printing: it may spread or fail to maintain its shape, resulting in defective parts. To replace the traditional resource-intensive "trial-and-error" approach, which consumes significant time and expensive materials, the project team proposed the application of artificial intelligence. Specialized computer models (machine learning) were developed, capable of predicting the quality of the future product prior to the manufacturing process. Particular attention was focused on algorithms that not only provide predictions but also quantify their confidence levels (Bayesian approach). Product Description popup.authors Ostap B. Zhalat-Lozynskyi Nazarii R. Mediukh Vasiliev Oleksandr O. Shevchuk Kateryna S. Naumenko Vladyslav Yu. Krasikov Anton I. Bilyi Vladyslav O. popup.nrat_date 2025-12-16 Close