A new approach for automated measuring of the melt pool geometry in laser-powder bed fusion

Abstract Additive manufacturing (AM) offers unique possibilities in comparison to conventional processes. For example, complex parts can be manufactured without tools. metals, the most commonly used AM process is laser-powder bed fusion (L-PBF). The L-PBF prone disturbances, hence maintaining a consistent part quality remains an important subject within current research. An established indicator for quantifying changes dimension of melt pools, which depends on energy input and cooling conditions. pool geometry normally measured manually cross sections solidified welding seams. This paper introduces new approach automated visual measuring pools cross-sections by L-PBF. are first segmented images then measured. Since have heterogeneous appearance, segmentation with common digital image processing difficult, deep learning was applied this project. With presented approach, over whole section specimen. Furthermore, remelted only partly visible, evaluated. high number each cross-section measured, allows examination trends build direction specimen results better statistics. deviations estimated via dimensions.