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Optimizing multiple process parameters in fused deposition modeling with particle swarm optimization

  • Arup Dey
  • David Hoffman
  • Nita YodoEmail author
Original Paper
  • 28 Downloads

Abstract

Fused deposition modeling (FDM) is one of the most widely used additive manufacturing processes to produce prototypes as well as functional parts from thermoplastics. However, the applications of the FDM process are still limited due to several drawbacks, such as poor surface quality, poor mechanical properties, or high built time. It has been deemed that the part characteristics and build time can be improved by determining an optimum combination of process parameters. To optimize multiple process parameters in FDM, this paper employs a multi-objective particle swarm optimization based on the data collected from the experimental study. Four (04) process parameters, namely layer thickness, build orientation, infill density, and extrusion temperature are optimized to achieve higher compressive strength and lower build time. The optimization results provide information on the combined impacts of the four process parameters on compressive strength and build time. This information can aid decision makers with better judgment when dealing with multiple conflicting objectives.

Keywords

Fused deposition modeling Process parameters Compressive strength Build time Multi-parameters Particle swarm optimization 

Notes

Acknowledgements

This research work was partially supported by NDSU EPSCoR Grant FAR0030453.

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Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Industrial and Manufacturing EngineeringNorth Dakota State UniversityFargoUSA

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