首页|Reports Summarize Machine Learning Study Results from Polytechnic University Tor ino (Machine Learning-enabled Real-time Anomaly Detection for Electron Beam Powd er Bed Fusion Additive Manufacturing)
Reports Summarize Machine Learning Study Results from Polytechnic University Tor ino (Machine Learning-enabled Real-time Anomaly Detection for Electron Beam Powd er Bed Fusion Additive Manufacturing)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingout of Turin, Italy, by NewsRx edito rs, research stated, “Despite the many advantages and increasingadoption of Ele ctron Beam Powder Bed Fusion (PBF-EB) additive manufacturing by industry, curren tPBF-EB systems remain largely unstable and prone to unpredictable anomalous be haviours. Additionally,although featuring in-situ process monitoring, PBF-EB sy stems show limited capabilities in terms oftimely identification of process fai lures, which may result into considerable wastage of production timeand materia ls.”
TurinItalyEuropeCyborgsEmerging TechnologiesMachine LearningPolytechnic University Torino
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