Powder bed monitoring via digital image analysis in additive manufacturing

被引:0
|
作者
A. Boschetto
L. Bottini
S. Vatanparast
机构
[1] Sapienza University of Rome,Department of Mechanical and Aerospace Engineering
来源
关键词
Additive manufacturing; Selective laser melting; Powder bed monitoring; Digital image processing;
D O I
暂无
中图分类号
学科分类号
摘要
Due to the nature of Selective Laser Melting process, the built parts suffer from high chances of defects formation. Powders quality have a significant impact on the final attributes of SLM-manufactured items. From a processing standpoint, it is critical to ensure proper powder distribution and compaction in each layer of the powder bed, which is impacted by particle size distribution, packing density, flowability, and sphericity of the powder particles. Layer-by-layer study of the process can provide better understanding of the effect of powder bed on the final part quality. Image-based processing technique could be used to examine the quality of parts fabricated by Selective Laser Melting through layerwise monitoring and to evaluate the results achieved by other techniques. In this paper, a not supervised methodology based on Digital Image Processing through the build-in machine camera is proposed. Since the limitation of the optical system in terms of resolution, positioning, lighting, field-of-view, many efforts were paid to the calibration and to the data processing. Its capability to individuate possible defects on SLM parts was evaluated by a Computer Tomography results verification.
引用
收藏
页码:991 / 1011
页数:20
相关论文
共 50 条
  • [1] Powder bed monitoring via digital image analysis in additive manufacturing
    Boschetto, A.
    Bottini, L.
    Vatanparast, S.
    JOURNAL OF INTELLIGENT MANUFACTURING, 2024, 35 (03) : 991 - 1011
  • [2] Simulation and analysis of powder bed for additive manufacturing
    Xiang Z.
    Yin M.
    Deng Z.
    Mei X.
    Yin G.
    Yin, Ming (mingyin@scu.edu.cn), 1600, Sichuan University (48): : 191 - 197
  • [3] An Image Segmentation Framework for In-Situ Monitoring in Laser Powder Bed Fusion Additive Manufacturing
    Xie, Jason
    Jiang, Tianyu
    Chen, Xu
    IFAC PAPERSONLINE, 2022, 55 (37): : 800 - 806
  • [4] Prediction of microstructural defects in additive manufacturing from powder bed quality using digital image correlation
    Bartlett, Jamison L.
    Jarama, Alex
    Jones, Jonaaron
    Li, Xiaodong
    MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2020, 794
  • [5] Assessment of optical emission analysis for in-process monitoring of powder bed fusion additive manufacturing
    Dunbar, Alexander J.
    Nassar, Abdalla R.
    VIRTUAL AND PHYSICAL PROTOTYPING, 2018, 13 (01) : 14 - 19
  • [6] Additive manufacturing of ceramics via the laser powder bed fusion process
    Ullah, Abid
    Shah, Mussadiq
    Ali, Zulfiqar
    Asami, Karim
    Rehman, Asif Ur
    Emmelmann, Claus
    INTERNATIONAL JOURNAL OF APPLIED CERAMIC TECHNOLOGY, 2025,
  • [7] Redesign and manufacturing of a metal towing hook via laser additive manufacturing with powder bed
    Usera, D.
    Alfieri, V.
    Caiazzo, F.
    Argenio, P.
    Corrado, G.
    Ares, E.
    MANUFACTURING ENGINEERING SOCIETY INTERNATIONAL CONFERENCE 2017 (MESIC 2017), 2017, 13 : 825 - 832
  • [8] In-Situ Monitoring and Modeling of Metal Additive Manufacturing Powder Bed Fusion
    Alldredge, Jocob
    Slotwinski, John
    Storck, Steven
    Kim, Sam
    Goldberg, Arnold
    Montalbano, Timothy
    44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 37, 2018, 1949
  • [9] Understanding powder bed fusion additive manufacturing phenomena via numerical simulation
    Ferro, P.
    Romanin, L.
    Berto, F.
    FRATTURA ED INTEGRITA STRUTTURALE-FRACTURE AND STRUCTURAL INTEGRITY, 2020, Gruppo Italiano Frattura (53): : 252 - 284
  • [10] Measurement of powder bed density in powder bed fusion additive manufacturing processes
    Jacob, G.
    Donmez, A.
    Slotwinski, J.
    Moylan, S.
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2016, 27 (11)