首页|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)

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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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.

WaterlooCanadaNorth and Central Amer icaCyborgsEmerging TechnologiesMachine LearningUniversity of Waterloo

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Sep.18)