4.6 Article

Investigation of the Effects of Roller Spreading Parameters on Powder Bed Quality in Selective Laser Sintering

Journal

MATERIALS
Volume 15, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/ma15113849

Keywords

selective laser sintering; spread the powder quality; parameter optimization; DEM; RSM; NSGA-II

Funding

  1. Natural Science Foundation of Hunan Province Youth Project [2020JJ5541]
  2. Outstanding Youth Project of the Hunan Natural Science Foundation [2021JJ20009]
  3. Hunan Education Department Project [2018111400702]
  4. Education Reform Project of the Hunan Province Education Department [2021JGYB083]
  5. National Natural Science Foundation of China [51705442]

Ask authors/readers for more resources

This study investigates the importance of powder spreading in SLS and proposes a method to optimize the quality of powder spreading through the use of DEM and RSM. By establishing a regression model and utilizing an improved multi-objective optimization algorithm, the powder laying quality in the SLS process was enhanced.
Powder spreading is one of crucial steps in selective laser sintering (SLS), which controls the quality of the powder bed and affects the quality of the printed parts. It is not advisable to use empirical methods or trial-and-error methods that consume lots of manpower and material resources to match the powder property parameters and powder laying process parameters. In this paper, powder spreading in realistic SLS settings was simulated using a discrete element method (DEM) to investigate the effects of the powder's physical properties and operating conditions on the bed quality, characterized by the density characteristics, density uniformity, and flatness of the powder layer. A regression model of the powdering quality was established based on the response surface methodology (RSM). The relationship between the proposed powdering quality index and the research variables was well expressed. An improved multi-objective optimization algorithm of the non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize the powder laying quality of nylon powder in the SLS process. We provided different optimization schemes according to the different process requirements. The reliability of the multi-objective optimization results for powdering quality was verified via experiments.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available