Abstract
Metal additive manufacturing has become an increasingly popular technology and receives interest from multiple business sectors that require optimally lightweight components and mass customization (aerospace, automotive, and medical device). Directed energy deposition (DED) is one of the main laser-based additive manufacturing processes, but a fundamental understanding of the process is lacking partly because it has not been the focus of highspeed, in-situ x-ray imaging studies like laser powder bed fusion has. A novel in-situ DED system is presented here, and an experimental study is performed to show that the small-scale system recovers processing parameter trends of a full-scale build. Observed meltpool lengths range from about 200 µm to 900 µm, while meltpool depths range from about 50 µm to 500 µm and can support high-fidelity modelling. Additionally, an investigation on the relationship between meltpool dimensions and global energy density GGEEDD' is performed. It was found that GGEEDD' is not a good predictor of meltpool dimensions due to the discrepancy in linear and exponential trends in laser powder and powder mass flowrate. Further studies and analysis using the presented novel DED system are needed to develop an appropriate energy density term to predict of meltpool dimension and clad height.
Original language | English (US) |
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Pages (from-to) | 691-696 |
Number of pages | 6 |
Journal | 48th SME North American Manufacturing Research Conference, NAMRC 48 |
Volume | 48 |
DOIs | |
State | Published - 2020 |
Event | 48th SME North American Manufacturing Research Conference, NAMRC 48 - Cincinnati, United States Duration: Jun 22 2020 → Jun 26 2020 |
Funding
The authors would like to acknowledge Tao Sun, Niranjan Parab, and Sarah oW lff for all their support at APS , as well as Yi Shi, Nicolas Martinez , Marisa Bisram, and Shuheng Liao for experiment execution. 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 Contr act No. DE-AC02-06CH 1357. This material is based upon work supported by the National Science Foundation Graduate esearR ch Fellowship under Grant No. DGE -1842165. This research was also funded by NIMSI and CHiMaD . The authors would like to acknowledge Tao Sun, Niranjan Parab, and Sarah Wolff for all their support at APS, as well as Yi Shi, Nicolas Martinez, Marisa Bisram, and Shuheng Liao for experiment execution. 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. DEAC02-06CH11357. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1842165. This research was also funded by NIMSI and CHiMaD.
Keywords
- Directed energy deposition
- Energy density
- In-situ x-ray imaging
ASJC Scopus subject areas
- Artificial Intelligence
- Industrial and Manufacturing Engineering