Date of Award
2024-12-01
Degree Name
Master of Science
Department
Engineering
Advisor(s)
Ryan B. Wicker
Abstract
This thesis addresses the widely neglected topic of powder management in the context of laser powder bed fusion (LPBF) additive manufacturing (AM). In LPBF AM, powder represents besides its direct impact on manufacturing and final part quality a significant AM cost factor, and the minimization of waste is of paramount importance to deliver the AM promise of most effective usage of input material. The reuse of powder is a necessary practice, but it requires proper calibration to ensure that it does not deviate substantially from the original composition in order to provide equivalent powder conditions to maintain desired manufacturing quality. Furthermore, consideration is given to the comparability of powders utilized in disparate studies. It is inevitable that differences occur in particle size distribution (PSD) between manufacturers, batches, and lots, which gives rise to concerns about the potential impact on the manufacturing process. While considerable attention has been devoted machine parameter setup, machine-to-machine comparability and process repeatability, less emphasis has been placed on the analytical characterization of powder and the course of action to customize powder composition job specific and thus enabling an accurate powder coating process in the powder bed, parts additively manufactured of utmost quality and at predefined costs.Moreover, powder blending is becoming increasingly crucial for in-situ alloying, the development of novel alloys, and multi-material processes, particularly in the context of high-performance applications. The development of efficient and analytical approaches to powder blending, whether for upcycling or pure PSD comparability and development, is currently lacking. This work introduces a novel approach, the Rosin-Rammler Prediction Method (RRPM), for the description and further analysis of PSD. This approach and the corresponding methodology has been transferred into software code, extensively tested and already statistically validated targeted for analytical PSD modifications. The thesis presents a method for powder sampling that is both repeatable and structured, and thus provides a defined and solid base to explore the influence of dosing factors and the creation of a two-dimensional map of powder characteristics across the entire substrate plate. Furthermore the influence and impact of well predefined PSD variations on manufacturing/part quality was explored by deploying a customized experimental set-up, designed, engineered and manufactured as part of this thesis. The PSD deviations were purposely predefined to reflect industrial operating conditions realistically, mostly challenged, by the use of different powder lots and the powder recoating process itself. The RRPM approach and its implementation allows for nearly full coverage of realistic PSD differences via analytically determined blending instructions. Comprehensive and thorough investigations confirmed the validity of the analytical model developed and its ability to deliver precise results. PSD differences due to lot variations and coating processes were found to be significant, with different PSD zones on the substrate plate identified. An additional impact factor not yet represented in current literature, the substrate plate geometry, was identified. PSD changes were found to lead to measurable differences in energy absorption, process parameter windows, melt pool geometry, and hardness of the manufactured part. In general, finer powder resulted in a more stable and broader process window and elevated hardness values. The key findings of this thesis are: â?¢ A repeatable areal powder sampling approach established, relevant powder characteristics are mappable â?¢ Overdosing leads to a measurable particle size refinement across the substrate plate â?¢ PSD differences across the substrate plate result in different energy absorptivity (â??6.4 %) â?¢ Refined powder shows a more stable/wider process parameter window â?¢ Refined powder displays higher hardness values (â??>9 %) â?¢ PSD affects geometrical melt pool properties â?¢ RRPM calculations are highly accurate (goodness of fit >97 %) Given the central role of the RRPM tool in the work and its demonstrated accuracy in the investigations conducted thus far, it is imperative that future investigations prioritize an in-depth examination of the limitations inherent to the underlying Rosin-Rammler approach. In particular, the RRPM description of geometrically irregular particles, as well as bi- and multimodal distributions, should be characterized in order to address the conditions of an industrial application of RRPM in an optimal manner. Moreover, it is essential to conduct comprehensive research into the impact and significance of particle size distribution (PSD) on the manufacturing process and, subsequently, the quality of the final component. In light of the findings presented here, it is recommended that additional factors (e.g., coating speed, coating principle, coating thickness) be subjected to analysis in the context of powder application with a view to characterizing their influence on the resulting PSD distribution over the substrate plate. With regard to the determined PSD-related hardness differences, it is advisable to carry out further EBSD investigations with a view to analyzing the probable influence of the PSD on the resulting microstructure.
Language
en
Provenance
Recieved from ProQuest
Copyright Date
2024-12-01
File Size
442 p.
File Format
application/pdf
Rights Holder
Nicolas Andreas Pielczyk
Recommended Citation
Pielczyk, Nicolas Andreas, "Development Of Advanced And Practical Powder Composition Characterization And Analysis Techniques For Powder Bed Based Additive Manufacturing" (2024). Open Access Theses & Dissertations. 4287.
https://scholarworks.utep.edu/open_etd/4287