Hendriks, Adriaan JRamokolo, Lesiba RNgobeni, Christopher MMoroko, Matome CNaidoo, Darryl2019-10-252019-10-252019-03Hendriks, A.J., Ramokolo, L.R., Ngobeni, C.M., Moroko, M.C. & Naidoo, D. 2019. Layer-wise powder deposition defect detection in additive manufacturing. In: Proceedings of SPIE 10909, Laser 3D Manufacturing VI, 109090O, San Francisco, California, USA, March 2019978-1-510-62460-3978-1-510-6246-10https://doi.org/10.1117/12.2509571https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10909.toc?SSO=1https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10909/109090O/Layer-wise-powder-deposition-defect-detection-in-additive-manufacturing/10.1117/12.2509571.full9http://hdl.handle.net/10204/11183Presented in: Proceedings of SPIE 10909, Laser 3D Manufacturing VI, 109090O, San Francisco, California, USA, March 2019. Due to copyright restrictions, the attached PDF file contains the abstract of the full-text item. For access to the full-text item, please consult the publisher's website.Additive manufacturing applications, in areas such as aerospace and medicine, are limited due to the lack of process stability and quality management. In particular, geometrical inaccuracies and the presence of mechanical defects hinder repeatability of the process1. A great disadvantage of AM is that verifying the quality of AM produced parts are mainly done after part fabrication which does not allow the operator to act upon defects observed during the actual build. To break into industries with very high quality standards, an important issue to be addressed is in-situ quality control during a build2, 3. If defects on a new powder layer can be detected before laser melting occurs, a new layer may be suitably recoated or the process can be paused for user controlled rectification. The work which will be presented here is focused on image based process monitoring of a powder bed additive manufacturing system using a shadow casting method. As a proof of principle, a few main defects during recoating will be identified and analyzed to establish the severity and possible impact of the defects on metal powder consolidation. Preliminary results of defects identified before and after material consolidation will be shown. For this, a software package is in development to automatically detect defects. This is aimed towards developing a system which in the future will contribute to quality assurance.enHigh resolution imagingImage processingIn-line quality controlIn situ process monitoringPowder deposition defectsConference PresentationHendriks, A. J., Ramokolo, L. R., Ngobeni, C. M., Moroko, M. C., & Naidoo, D. (2019). Layer-wise powder deposition defect detection in additive manufacturing. SPIE. http://hdl.handle.net/10204/11183Hendriks, Adriaan J, Lesiba R Ramokolo, Christopher M Ngobeni, Matome C Moroko, and Darryl Naidoo. "Layer-wise powder deposition defect detection in additive manufacturing." (2019): http://hdl.handle.net/10204/11183Hendriks AJ, Ramokolo LR, Ngobeni CM, Moroko MC, Naidoo D, Layer-wise powder deposition defect detection in additive manufacturing; SPIE; 2019. http://hdl.handle.net/10204/11183 .TY - Conference Presentation AU - Hendriks, Adriaan J AU - Ramokolo, Lesiba R AU - Ngobeni, Christopher M AU - Moroko, Matome C AU - Naidoo, Darryl AB - Additive manufacturing applications, in areas such as aerospace and medicine, are limited due to the lack of process stability and quality management. In particular, geometrical inaccuracies and the presence of mechanical defects hinder repeatability of the process1. A great disadvantage of AM is that verifying the quality of AM produced parts are mainly done after part fabrication which does not allow the operator to act upon defects observed during the actual build. To break into industries with very high quality standards, an important issue to be addressed is in-situ quality control during a build2, 3. If defects on a new powder layer can be detected before laser melting occurs, a new layer may be suitably recoated or the process can be paused for user controlled rectification. The work which will be presented here is focused on image based process monitoring of a powder bed additive manufacturing system using a shadow casting method. As a proof of principle, a few main defects during recoating will be identified and analyzed to establish the severity and possible impact of the defects on metal powder consolidation. Preliminary results of defects identified before and after material consolidation will be shown. For this, a software package is in development to automatically detect defects. This is aimed towards developing a system which in the future will contribute to quality assurance. DA - 2019-03 DB - ResearchSpace DP - CSIR KW - High resolution imaging KW - Image processing KW - In-line quality control KW - In situ process monitoring KW - Powder deposition defects LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-510-62460-3 SM - 978-1-510-6246-10 T1 - Layer-wise powder deposition defect detection in additive manufacturing TI - Layer-wise powder deposition defect detection in additive manufacturing UR - http://hdl.handle.net/10204/11183 ER -