首页|Research on Machine Learning Described by Researchers at Singapore University of Technology and Design (Feature-Driven Density Prediction of Maraging Steel Addi tively Manufactured Samples Using Pyrometer Sensor and Supervised Machine Learni ng)
Research on Machine Learning Described by Researchers at Singapore University of Technology and Design (Feature-Driven Density Prediction of Maraging Steel Addi tively Manufactured Samples Using Pyrometer Sensor and Supervised Machine Learni ng)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on artificial intelligen ce have been presented. According to newsreporting out of Tampines, Singapore, by NewsRx editors, research stated, “Laser Powder Bed Fusion(LPBF) is a revolut ionizing additive manufacturing (AM) that melts the powder particles to create innovative products, but it faces substantial challenges in monitoring and predic ting the quality of theprinted samples. Traditional density measurement methods , like the Archimedes technique, have been employed to determine the density of maraging steel samples produced under varying machine settings(MACH-S) process parameters, including laser power and scan speed.”
Singapore University of Technology and D esignTampinesSingaporeAsiaCyborgsEmerging TechnologiesMachine Learni ng
NETL
NSTL
