首页|Louisiana Tech University Researcher Provides New Study Findings on Machine Lear ning (A Machine Learning Framework for Melt-Pool Geometry Prediction and Process Parameter Optimization in the Laser Powder-Bed Fusion Process)
Louisiana Tech University Researcher Provides New Study Findings on Machine Lear ning (A Machine Learning Framework for Melt-Pool Geometry Prediction and Process Parameter Optimization in the Laser Powder-Bed Fusion Process)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ar tificial intelligence. According to news reportingfrom Louisiana Tech Universit y by NewsRx journalists, research stated, “This study presents a cost-effectiveand high-precision machine learning (ML) method for predicting the melt-pool geo metry and optimizingthe process parameters in the laser powder-bed fusion (LPBF ) process with Ti-6Al-4V alloy. Unlike manyML models, the presented method inco rporates five key features, including three process parameters (laserpower, sca nning speed, and spot size) and two material parameters (layer thickness and pow der porosity).”Funders for this research include Louisiana Board of Regents; National Science F oundation.
Louisiana Tech UniversityCyborgsEmer ging TechnologiesMachine Learning
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