In-situ characterization and quantification of melt pool variation under constant input energy density in laser powder bed fusion additive manufacturing process

Qilin Guo, Cang Zhao, Minglei Qu, Lianghua Xiong, Luis I. Escano, S. Mohammad H. Hojjatzadeh, Niranjan D. Parab, Kamel Fezzaa, Wes Everhart, Tao Sun, Lianyi Chen

Research output: Contribution to journalArticlepeer-review

186 Scopus citations

Abstract

Size and shape of a melt pool play a critical role in determining the microstructure in additively manufactured metals. However, it is very challenging to directly characterize the size and shape of the melt pool beneath the surface of the melt pool during the additive manufacturing process. Here, we report the direct observation and quantification of melt pool variation during the laser powder bed fusion (LPBF) additive manufacturing process under constant input energy density by in-situ high-speed high-energy x-ray imaging. We show that the melt pool can undergo different melting regimes and both the melt pool dimension and melt pool volume can have orders-of-magnitude change under a constant input energy density. Our analysis shows that the significant melt pool variation cannot be solely explained by the energy dissipation rate. We found that energy absorption changes significantly under a constant input energy density, which is another important cause of melt pool variation. Our further analysis reveals that the significant change in energy absorption originates from the separate roles of laser power and scan speed in depression zone development. The results reported here are important for understanding the laser powder bed fusion additive manufacturing process and guiding the development of better metrics for processing parameter design.

Original languageEnglish
Pages (from-to)600-609
Number of pages10
JournalAdditive Manufacturing
Volume28
DOIs
StatePublished - Aug 2019
Externally publishedYes

Funding

The authors would like to acknowledge Alex Deriy at the Advanced Photon Source for his help on the beamline experiments. This work is supported by Honeywell Federal Manufacturing & Technologies (FM&T, also known as the Kansas City National Security Campus), National Science Foundation , University of Missouri Research Board (UMRB) , Intelligent Systems Center at Missouri S&T , and Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory , provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. All data prepared, analyzed and presented has been developed in a specific context of work and was prepared for internal evaluation and use pursuant to that work authorized under the referenced contract. Reference herein to any specific commercial product, process or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government, any agency thereof or Honeywell Federal Manufacturing & Technologies, LLC. This publication has been authored by Honeywell Federal Manufacturing & Technologies under Contract No. DE-NA0002839 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes.

FundersFunder number
DOE Office of Science
Intelligent Systems Center at Missouri S&T
University of Missouri Research Board
National Science Foundation
U.S. Department of Energy
Office of Science
Argonne National Laboratory
Laboratory Directed Research and Development
Honeywell Federal Manufacturing and Technologies

    Keywords

    • Additive manufacturing
    • Energy absorption
    • Laser powder bed fusion
    • Melt pool
    • X-ray imaging

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