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The interplay between vapour, liquid, and solid phases in laser powder bed fusion
I Bitharas1, N Parab2,3, C Zhao2,4
1Institute of Photonics and Quantum Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, UK. i.bitharas@hw.ac.uk.
Nature Communications
|May 26, 2022
Summary
Understanding laser-material interactions in laser powder bed fusion (LPBF) is key. This study reveals how melt pool dynamics and vapor plume behavior affect process stability and part quality, identifying new thresholds for optimization.
Area of Science:
- Materials Science
- Physics
- Engineering
Background:
- Laser powder bed fusion (LPBF) is a key additive manufacturing technology for high-performance metal parts.
- Optimizing LPBF requires a deeper understanding of laser-material interactions and melt pool dynamics.
- Current process control lacks detailed insights into the fluid mechanics governing LPBF.
Purpose of the Study:
- To investigate the fluid dynamics of the vapor jet and melt pool depression during LPBF.
- To correlate these dynamics with process stability and identify key parameters influencing performance.
- To establish a foundation for improved process control and defect reduction in LPBF.
Main Methods:
- Simultaneous in-situ synchrotron X-ray and schlieren imaging were employed to visualize LPBF processes.
- Analysis focused on keyhole and vapor plume morphologies under various parameter settings.
- The influence of the powder layer on process stability was systematically explored.
Main Results:
- Stable plume and surface depression formation were observed under specific conditions, transitioning to chaotic behavior with full keyhole formation.
- A previously unreported energy input threshold for stable line scans was identified.
- Unfavorable process dynamics linked to porosity were directly visualized, correlating with specific plume and keyhole morphologies.
Conclusions:
- High-speed visualization of fluid mechanics provides critical insights into LPBF process stability.
- Understanding these dynamics aids in designing optimized process windows for higher power and speed.
- This research enables potential in-process monitoring of process stability and defect formation in additive manufacturing.
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