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Powder bed monitoring via digital image analysis in additive manufacturing

Author

Listed:
  • A. Boschetto

    (Sapienza University of Rome)

  • L. Bottini

    (Sapienza University of Rome)

  • S. Vatanparast

    (Sapienza University of Rome)

Abstract

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.

Suggested Citation

  • A. Boschetto & L. Bottini & S. Vatanparast, 2024. "Powder bed monitoring via digital image analysis in additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 35(3), pages 991-1011, March.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:3:d:10.1007_s10845-023-02091-7
    DOI: 10.1007/s10845-023-02091-7
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    References listed on IDEAS

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    1. Aiden A. Martin & Nicholas P. Calta & Saad A. Khairallah & Jenny Wang & Phillip J. Depond & Anthony Y. Fong & Vivek Thampy & Gabe M. Guss & Andrew M. Kiss & Kevin H. Stone & Christopher J. Tassone & J, 2019. "Dynamics of pore formation during laser powder bed fusion additive manufacturing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    2. Chenang Liu & Zhenyu (James) Kong & Suresh Babu & Chase Joslin & James Ferguson, 2021. "An integrated manifold learning approach for high-dimensional data feature extractions and its applications to online process monitoring of additive manufacturing," IISE Transactions, Taylor & Francis Journals, vol. 53(11), pages 1215-1230, November.
    3. Jie Yang & Shaowen Lu & Liangyong Wang, 2020. "Fused magnesia manufacturing process: a survey," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 327-350, February.
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