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Journal of Mechanical Engineering. 2019, (15) Core

Machine Learning Algorithms on Density Prediction of Electron Beam Selective Melted PartsChinese Full Text

QI Xinbo;LI Changpeng;LI Yang;LIN Feng;LI Yong;CHENG Xuan;CHEN Guofeng;State Key Laboratory of Tribology, Tsinghua University;Corporate Technology,Siemens Ltd.;Bio-manufacturing and Rapid Forming Technology Key Laboratory of Beijing,Tsinghua University;

Abstract: Electron Beam Selective Melting（EBSM） is a novel additive manufacturing technology, which is developing very fast nowadays. It has many advantages: building up parts with complex morphology; processing under vacuum to get rid of the impurity; its manufactured part with small residual stress and powder recycling. However, it is difficult to establish the relationship between EBSM’s processing parameters and parts’ properties. Here a series of Inconel 718 cubic specimens are manufactured through a... More
Keywords：

machine learning; electron beam selective melting; additive manufacturing; density; prediction;

  • Series：

    (C) Architecture/ Energy/ Traffic/ Electromechanics, etc; (B) Chemistry/ Metallurgy/ Environment/ Mine Industry; (I) Electronic Technology ＆ Information Science

  • Subject：

    Metallurgy Industry; Automation Technology

  • Classification Code：

    TP181;TF124

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