• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2023, Vol. 59 ›› Issue (19): 253-276.doi: 10.3901/JME.2023.19.253

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Research Progress and Challenges in Process Intelligent Monitoring of Laser Powder Bed Fusion Additive Manufacturing

ZHAO Zhibin1, WANG Chenxi1, ZHANG Xingwu1, CHEN Xuefeng1, LI Yinghong2   

  1. 1. School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049;
    2. National Key Lab of Aerospace Power System and Plasma Technology, Air Force Engineering University, Xi'an 710038
  • Received:2023-07-04 Revised:2023-09-11 Online:2023-10-05 Published:2023-12-11

Abstract: Laser powder bed fusion (LPBF) has gradually become a "potential stock" for fast, low-cost, high-performance, and short-cycle manufacturing of difficult-to-machine metal components. It is considered to be one of the most widely used metal additive manufacturing technologies, and has been widely used in aviation, aerospace and other industrial fields. However, the stability and consistency of additive manufacturing process and forming quality is a challenging problem for the industry and has become a "blocker" for LPBF to embrace the mass production. The current LPBF additive manufacturing monitoring system mainly focuses on "measuring", that is, measuring of various process information. Its quality evaluation and control technology are not mature enough, and intelligent monitoring combined with advanced sensing technology and artificial intelligence methods is expected to become a "sharp edge" for mass production of LPBF additive manufacturing. Following the trend, this paper summarizes the research progress and development status of intelligent monitoring in LPBF additive manufacturing from four aspects:LPBF defect types, process information perception, process quality intelligent evaluation, process parameter optimization and quality control. Some challenges in developing a mature intelligent monitoring system for mass production of LPBF additive manufacturing are pointed out. Finally, solutions and future prospects for addressing these challenges are discussed.

Key words: additive manufacturing, laser powder bed fusion, quality evaluation, intelligent monitoring

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