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  1. digitalcommons.calpoly.edu

    Laser powder bed fusion (LPBF) remains a predominately open-loop additive manufacturing process with minimal in-situ quality and process control. Some machines feature optical monitoring systems but lack automated analytical capabilities for real-time defect detection. Recent advances in machine learning (ML) and convolutional neural networks (CNN) present compelling solutions to analyze ...
  2. researchgate.net

    This approach was applied to a dataset for SLS powder bed defect detection. The results demonstrated excellent model performance with an accuracy of 98%, comparable to other sate-of-the-art ...
  3. ncbi.nlm.nih.gov

    National Center for Biotechnology Information

    https://www.ncbi.nlm.nih.gov › pmc › articles › PMC9416736

    Although the Mask RCNN with Resent 151 backbone model met the requirements of the system's computational time and detection accuracy, the utilizations of other CNN models such as the EfficientDet and CenterNet to develop a more powerful model for the powder spreading process is still an interesting further research avenue.
    Publication:Materials (Basel). 2022 Aug; 15(16): 5662.
  4. Multi-sensor defect detection technology is a research hotspot for monitoring the powder bed fusion (PBF) processes, of which the quality of the captured defect images and the detection capability is the vital issue. Thus, in this study, we utilize visible information as well as infrared imaging to detect the defects in PBF parts that conventional optical inspection technologies cannot easily ...
  5. researchgate.net

    Sep 4, 2023The quality of the powder layers in the 3D printing process is extremely important and directly corresponds to the quality of the structures made with this technology.
  6. researchgate.net

    Multi-sensor defect detection technology is a research hotspot for monitoring the powder bed fusion (PBF) processes, of which the quality of the captured defect images and the detection capability ...
  7. link.springer.com

    Nov 13, 2023The powder bed fusion (PBF) process is increasingly employed by industry to fabricate complex parts with stringent standard criteria. However, fabricating parts "free of defects" using this process is still a major challenge. As reported in the literature, thermally induced abnormalities form the majority of generated defects, and are mainly the result of thermal evolution. Monitoring ...
  8. link.springer.com

    Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process-property relationships for porosity prediction require many experiments or computationally expensive simulations without considering environmental variations. While efforts that adopt real-time monitoring sensors can only detect porosity after its occurrence ...

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