首页|South China University of Technology Reports Findings in Machine Learning (A lay er-wise melting defects mitigation method in laser powder bed fusion process bas ed on machine learning and fuzzy inference)
South China University of Technology Reports Findings in Machine Learning (A lay er-wise melting defects mitigation method in laser powder bed fusion process bas ed on machine learning and fuzzy inference)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Machine Learning is the subject o f a report. According to news originating fromGuangzhou, People’s Republic of C hina, by NewsRx correspondents, research stated, “Melting defects inLaser Powde r Bed Fusion (LPBF) processes, such as lack of fusion (LOF) or over-melting (OM) , cancause significant deterioration in mechanical properties and surface rough ness of printed parts, potentiallyleading to process failure. Previous attempts to utilize local melt pool-related information for LPBF processcontrol have fa ced limitations due to the high requirements on sensors and data processing, as well as thelack of representativeness of local melt pool information.”
GuangzhouPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesFuzzy LogicMachine Learning
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