Senvol, New York City, USA, is set to co-present with the US Air Force on machine learning for Additive Manufacturing at Rapid + TCT 2023, scheduled to take place May 2-4 in Chicago, Illinois, USA.
“Machine Learning for AM: A Case Study of How it is Being Used by the Department of Defense,” presented by Senvol President Zach Simkin and Dr Mark Benedict, Materials Scientist and Program Manager at Air Force Research Lab, will be a briefing on the technical results of a programme jointly funded by The Office of Naval Research, Air Force Research Lab, NAVAIR, and NAVSEA.
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The programme was focused on developing and demonstrating a machine learning capability known as Transfer Learning. With Transfer Learning, data from prior machines and prior materials can be used to help predict performance on a new machine and/or new material. Transfer Learning can significantly reduce the time and cost of process development or qualifying a new Additive Manufacturing machine or material if used properly.
In the programme, 316L data was generated on four different AM machines: 3D Systems ProX 320, EOS M270, EOS M290, and Additive Industries MetalFAB1. Using the Transfer Learning capability, data from some of the machines was used to help predict performance on the other machines. Transfer Learning was validated to work extremely well, with the resulting predictive models reportedly very useful and significantly improved.
The presentation will take place May 2, at 3.00 pm.