In-process powder bed monitoring with angular illumination

Thomas Milde; Alexander Freytag; Ghazal Ghazaei

doi:10.1117/12.2675824

15 August 2023 In-process powder bed monitoring with angular illumination

Thomas Milde, Alexander Freytag, Ghazal Ghazaei

Proceedings Volume 12618, Optical Measurement Systems for Industrial Inspection XIII; 1261806 (2023) https://doi.org/10.1117/12.2675824
Event: SPIE Optical Metrology, 2023, Munich, Germany

Abstract

Laser powder bed fusion (LPBF) is an emerging technology that is gaining more and more market share in the overall additive manufacturing market. One crucial component of the manufacturing process is a possibly perfect flat and homogeneous powder bed. If the powder recoating runs into problems, e.g., because of recoater defects or missing powder, or if the previously printed layers generate powder bed defects, this requirement cannot be fulfilled. Defects in the powder bed can lead to defects in the final part. Hence, the powder bed for each new layer should be inspected for anomalies. Doing so, the generation of defects, e.g., de-lamination, can be detected in early stages. We present a specialized machine vision system which is capable to detect and partly classify all powder bed anomalies. Machine vision in the building chamber of LPBF machines is challenging. One needs oblique observation because the centered view is blocked by the laser(s). One needs many pixels and optimized imaging to catch all the defects. The field of view is large. In order not to increase the production time of a layer, the imaging and powder bed assessment should work fast. All relevant information about the defects must be captured by the imaging process. The main advantage of our approach is, that we acquire not only one image, but four images, each illuminated with an individual light source at the ceiling of the building chamber. We will show, how these four images can be used to find, distinguish, and classify defects. This includes classical image processing as well as machine learning techniques.

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Thomas Milde, Alexander Freytag, and Ghazal Ghazaei "In-process powder bed monitoring with angular illumination", Proc. SPIE 12618, Optical Measurement Systems for Industrial Inspection XIII, 1261806 (15 August 2023); https://doi.org/10.1117/12.2675824

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KEYWORDS

Light sources and illumination

Image processing

Machine learning

Printing

Cameras

Inspection

Feedback loops

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