首页|Study Data from QILU University of Technology Update Knowledge of Machine Learni ng (Predicting 4d Hardness Property From 3d Datasets for Performance-tunable Mat erial Extrusion Additive Manufacturing)
Study Data from QILU University of Technology Update Knowledge of Machine Learni ng (Predicting 4d Hardness Property From 3d Datasets for Performance-tunable Mat erial Extrusion 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 reportingfrom Jinan, People’s Republic of Chi na, by NewsRx journalists, research stated, “This study exploresthe application of machine learning in predicting the hardness of a quaternary polymer blends d uring3D printing, aiming to reduce the development and experimental costs of mi xing extrusion head and toexpedite the realization of multi -material co -blend ing printing technology. We selected four types ofpolymer materials: polylactic acid (PLA), thermoplastic polyurethane (TPU), polyethylene terephthalateglycol (PETG), acrylonitrile butadiene styrene (ABS), and obtained composite materials of various hardnessvalues through random combinations of three (from four) mat erials.”
JinanPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningQILU University of Technology
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