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Quantification of Interdependent Dynamics during Laser Additive Manufacturing Using X-Ray Imaging Informed

Chu Lun Alex Leung1,2, Dawid Luczyniec3, Enyu Guo4

  • 1Department of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.

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Summary

Researchers quantified imperfections in laser powder bed fusion (LPBF) by studying porosity and humps. Understanding these defects is key to improving the reliability of metal components produced by LPBF.

Keywords:
X-ray imagingXCTadditive manufacturingimperfectionmultiphaseporesimulation

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Area of Science:

  • Materials Science
  • Manufacturing Engineering
  • Additive Manufacturing

Background:

  • Laser powder bed fusion (LPBF) is crucial for producing high-value metallic components.
  • The widespread adoption of LPBF for safety-critical applications is hindered by process-induced imperfections.
  • The relationship between LPBF processing parameters and defect formation is not fully understood.

Purpose of the Study:

  • To quantify the evolution of porosity and humps during LPBF.
  • To elucidate the mechanisms driving the formation of pores and humps.
  • To provide insights for enhancing the reliability of LPBF processes.

Main Methods:

  • Utilized X-ray and electron imaging for defect observation.
  • Employed high-fidelity multiphase process simulation.
  • Quantified pore evolution kinetics, size distribution, waviness, surface roughness, and melt volume.

Main Results:

  • Identified keyhole collapse, pore coalescence, and entrapment as mechanisms for irregular pore formation.
  • Revealed that pore formation is driven by high temperatures and metal vapor concentration within the keyhole.
  • Demonstrated that Kelvin-Helmholtz instability at the melt track surface causes hump formation due to vapor plume and molten pool interaction.

Conclusions:

  • The study clarifies the formation mechanisms of porosity and humps in LPBF.
  • Understanding these mechanisms is critical for controlling imperfections.
  • The findings offer a basis for improving process reliability in additive manufacturing.