Markl M, Azadi Tinat MR, Berger T, Renner J, Körner C (2024)
Publication Language: English
Publication Type: Journal article
Publication year: 2024
Book Volume: 10
Article Number: 100220
DOI: 10.1016/j.addlet.2024.100220
Electron beam powder bed fusion offers the unique opportunity to observe the process by measuring scattered electrons on a metal detector. This technique is the state of the art in generating electron optical images of the build area after melting using single- or multi-detector setups. The images enable the detection of surface defects like porosity or material transport by reconstructing the surface topography. Internal defects such as layer-bonding defects cannot be identified. Many of these defects, particularly layer-bonding defects, often originate from an irregular distribution of the powder bed. This work introduces an additional process step by recording an electron optical image after the distribution of the powder bed. Combining this with an electron optical image after melting the previous layer enables extraction of powder bed features such as the current powder bed height. The underlying method bases on the correlation of experimental measurements and numerical simulations of the intensity of the electron optical signal for different powder bed heights. With this approach, it is possible to identify irregular powder distributions, such as uncovered areas of previously molten material or locally varying powder bed heights. This information is crucial for online monitoring and real time process control. Exemplary, this opens the opportunity of healing the powder bed by an additional raking step.
APA:
Markl, M., Azadi Tinat, M.R., Berger, T., Renner, J., & Körner, C. (2024). Extracting powder bed features via electron optical images during electron beam powder bed fusion. Additive Manufacturing Letters, 10. https://doi.org/10.1016/j.addlet.2024.100220
MLA:
Markl, Matthias, et al. "Extracting powder bed features via electron optical images during electron beam powder bed fusion." Additive Manufacturing Letters 10 (2024).
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