首页|Studies from University of Waterloo Yield New Data on Machine Learning (An Integ rated Fuzzy Logic and Machine Learning Platform for Porosity Detection Using Opt ical Tomography Imaging During Laser Powder Bed Fusion)
Studies from University of Waterloo Yield New Data on Machine Learning (An Integ rated Fuzzy Logic and Machine Learning Platform for Porosity Detection Using Opt ical Tomography Imaging During Laser Powder Bed Fusion)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Research findings on Machine Learning are discuss ed in a new report. According to news reportingoriginating in Waterloo, Canada, by NewsRx journalists, research stated, “Traditional methods such asmechanical testing and x-ray computed tomography (CT), for quality assessment in laser pow der-bed fusion(LPBF), a class of additive manufacturing (AM), are resource-inte nsive and conducted post-production.Recent advancements in in-situ monitoring, particularly using optical tomography (OT) to detect nearinfraredlight emissio ns during the process, offer an opportunity for in-situ defect detection.”
WaterlooCanadaNorth and Central Amer icaCyborgsEmerging TechnologiesFuzzy LogicMachine LearningUniversity o f Waterloo
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