Physics-added neural networks: An image-based deep learning for material printing system

Professor Joon Sang Lee's the division of inkjet printing solution research team in the Department of Mechanical Engineering proposed the physics-added neural networks (PANNs) to improve training efficiency and accuracy by adding physics in inkjet printing system. The research paper is published in the journal of 'Additive Manufacturing' (Impact factor: 13.632, top 0.98%, Volume 73) in July 2023. In this paper, PANNs was adopted in inkjet printing optimization where thermal effect is applied.

The link: https://authors.elsevier.com/a/1hJls7tcTWlNh0, DOI: doi.org/10.1016/j.addma.2023.103668