Arnold C (2023)
Publication Language: English
Publication Type: Thesis
Publication year: 2023
URI: https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-216113
Electron beam powder bed fusion (PBF-EB) is a high-power additive manufacturing technology for the efficient processing of complex metallic materials. The process characteristics like high-temperature and high-vacuum conditions render it suitable for the production of parts in highly demanding industries, e.g., aerospace or the medical technology sector. These application fields are linked to high requirements considering the quality of the manufactured parts. The current PBF-EB process technology cannot ensure full compliance with these requirements. One main reason for this circumstance is the lack of reliable tools for process monitoring due to the harsh conditions inside the PBF-EB build chamber. To overcome this limitation, the current thesis investigates how the in-situ acquisition of electron-optical (ELO) images of the build area may be used to monitor the build process and predict the quality of the manufactured parts. By measuring electrons emitted from the beam-material interaction, spatial information on the status of the build area is gathered, while drawbacks associated with alternative approaches are circumvented. For this purpose, an electron detector was integrated into the PBF-EB build cycle for the layer-wise acquisition of ELO images. The data is analyzed and optimized with respect to imaging accuracy and signal strength. Features of the molten slices are extracted and compared to reference data acquired by post-process X-ray computed tomography (XCT). The investigation reveals that in-situ ELO imaging provides high-quality information about the status of the molten slices, which strongly correlates to the quality of the as-built part. On the one hand, this is shown for surface defects leading to internal porosity, which can be reliably predicted for defects larger than 0.2 mm. On the other hand, also the dimensional accuracy of the manufactured parts is determined with an accuracy of up to 0.1 mm. Stronger deviations and uncertainties of the approach are related to processing parameters and the target geometry and traced back to the spatiotemporal limitations of the imaging principle. The demonstrated prediction capabilities exceed those of any other approach reported so far in metal additive manufacturing. Thus, the investigation provides a solid basis for using ELO imaging as a high-performance tool for effective monitoring of PBF-EB processes.
APA:
Arnold, C. (2023). Fundamental Investigation of Electron-Optical Process Monitoring in Electron Beam Powder Bed Fusion (Dissertation).
MLA:
Arnold, Christopher. Fundamental Investigation of Electron-Optical Process Monitoring in Electron Beam Powder Bed Fusion. Dissertation, 2023.
BibTeX: Download