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dc.contributor.authorGoh, Guo Dongen_US
dc.contributor.authorYeong, Wai Yeeen_US
dc.identifier.citationGoh, G. D. & Yeong, W. Y. (2022). Applications of machine learning in 3D printing. Materials Today: Proceedings.
dc.description.abstractThe 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.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.relation.ispartofMaterials Today: Proceedingsen_US
dc.rights© 2022 Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Mechanical engineeringen_US
dc.titleApplications of machine learning in 3D printingen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.researchSingapore Centre for 3D Printingen_US
dc.subject.keywordsAdditive Manufacturingen_US
dc.subject.keywordsMachine Learningen_US
dc.description.acknowledgementThis research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme.en_US
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