Applications of machine learning in 3D printing

• Main Authors: Goh, Guo Dong, Yeong, Wai Yee
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Mechanical engineering; Additive Manufacturing; Machine Learning
• Online Access: https://hdl.handle.net/10356/163124
• Institution: Nanyang Technological University

The 4th Industrial Revolution integrates the digital revolution into the physical world, opens up new directions for research in several fields, including artificial intelligence and 3D printing. Data-driven models have been developed thanks to the advancement in computational power and machine learning algorithms, which enables machines to learn and execute a certain task through data without the need to formulate them explicitly. Machine learning have been used in 3D printing to enhance the product quality and productivity through in-situ monitoring, to optimize design and process parameters, and to speed up the prediction microstructure evolution through the development of physic-based data driven surrogate model. This article summarizes the work done by our group on the use of machine learning in 3D printing and provides an outlook on the 3D printing industry.