3D printing company Senvol has been awarded a grant by the US National Institute of Standards and Technology (NIST) for a project entitled ‘Continuous Learning for Additive Manufacturing Processes Through Advanced Data Analytics.’
According to Senvol, the project will focus on demonstrating that data analytics can be applied to additive manufacturing (AM) data to establish process-structure-property (PSP) relationships. Senvol ML, Senvol’s data-driven machine learning software for AM, will be used to conduct the analyses. The data to be analyzed will come from NIST’s various round robin test studies as well as from its AM Benchmark Test Series.
‘The work in this project will demonstrate the power of a data-driven machine learning approach for additive manufacturing process understanding and material characterization,’ said Yan Lu, senior research scientist at NIST. ‘Furthermore, Senvol will showcase hybrid modeling, whereby physics-based models and data-driven models are joined under a single framework.’
This story is reprinted from material from Senvol, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier.