研究目的
To address the high uncertainty in the mechanical properties of 3D-printed parts by proposing a new time-efficient microstructure prediction algorithm for the laser powder bed fusion (LPBF) process.
研究成果
A simplified analytical model of the LPBF process was successfully used to develop a grain size and aspect ratio prediction algorithm for a given powder feedstock and a given LPBF system. The model was validated for different alloys and processing conditions, demonstrating its potential for LPBF process simulation and optimization.
研究不足
The model does not take into account the specificities of a given LPBF system related to particular heat transfer and recoating conditions, which influence the final microstructure of manufactured parts. Additionally, the model's applicability is limited to alloys with diffusion-dependent phase transformations.
1：Experimental Design and Method Selection
The study used a combination of melt pool modeling and the design of experiment approaches to predict the microstructure of materials processed by an EOS M280 LPBF system.
2：Sample Selection and Data Sources
Water-atomized iron powder and IN625 alloys were used. The powder batch chemistry was analyzed using various systems including a Spectro ARL 3460 system and LECO systems.
3：List of Experimental Equipment and Materials
EOSINT M280 LPBF system equipped with a 400 W ytterbium fiber laser, SARTORIUS Secura 324-1s scale, LEXT4100 confocal microscope, and Matlab software for data processing.
4：Experimental Procedures and Operational Workflow
Specimens were printed, cut off the building plate, polished, and their densities were measured using the Archimedes technique. Grain size and aspect ratio measurements were conducted using a confocal microscope.
5：Data Analysis Methods
The average grain size and grain aspect ratio were measured using the linear intercept method. Data were processed using Matlab software.
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