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Modeling Particle Emissions from Three-Dimensional Printing with Acrylonitrile-Butadiene-Styrene Polymer Filament.

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A new model estimates particulate matter from industrial 3D printing. It accurately predicts near-field concentrations, aiding in workplace safety assessments and respiratory protection needs.

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Area of Science:

  • Environmental Science
  • Industrial Hygiene
  • Additive Manufacturing

Background:

  • 3D printing, or additive manufacturing, releases particulate matter.
  • Understanding these emissions is crucial for occupational safety.

Purpose of the Study:

  • To develop and validate a model for estimating particulate concentrations from industrial 3D printers.
  • To assess potential employee exposure and inform hazard assessments.

Main Methods:

  • An eddy diffusion model was developed using laboratory data from a desktop 3D printer.
  • The model was coupled with Monte Carlo analysis and validated against industrial-scale 3D printing data.
  • Key inputs included mass emission rates, particle loss, extrusion rate, temperature, and environmental diffusivity.

Main Results:

  • The model accurately predicted near-field particulate concentrations, showing no statistical difference from measured values.
  • Model predictions showed greater statistical variation in the far-field compared to air-monitoring results.
  • Environmental diffusivity and extrusion rate were identified as the most significant variables influencing emission concentrations.

Conclusions:

  • The developed model provides a reliable tool for estimating airborne particulate concentrations in 3D printing environments.
  • This model can support "what if" scenarios for employee exposure evaluation and compliance with OSHA standards.
  • It aids in determining the necessity of respiratory protection in additive manufacturing workplaces.