Reports Summarize Machine Learning Study Results from University of Waterloo (A Novel Machine Learning-based Approach for In-situ Surface Roughness Prediction I n Laser Powder-bed Fusion)

Robotics & Machine Learning Daily News2024，Issue(Sep.18) ：19-20.

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Reports Summarize Machine Learning Study Results from University of Waterloo (A Novel Machine Learning-based Approach for In-situ Surface Roughness Prediction I n Laser Powder-bed Fusion)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news originating from Waterloo, Canada, by NewsRx corre spondents, research stated, “Controlling and optimizing surface roughness remain a significant challenge in laser powder bed fusion (LPBF). Surface roughness af fects printed part quality, particularly fatigue life, leading to costly post-pr ocessing.” Funders for this research include Natural Sciences and Engineering Research Coun cil of Canada (NSERC), Canada Research Chairs.

Key words

Waterloo/Canada/North and Central Amer ica/Cyborgs/Emerging Technologies/Machine Learning/University of Waterloo

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出版年

2024

Robotics & Machine Learning Daily News

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