Daekeon Ahn
- Automotive Engineering top 1%
- Mechanical Engineering top 5%
- Industrial and Manufacturing Engineering top 1%
- Biomedical Engineering
- Building and Construction top 10%
- Co-authors
- Seok‐Hee LeeJin‐Hwe KweonHo-Chan KimSoon Man KwonJung‐il SongJinho ChoiA. N. SreeramWoo‐Sung Jang
- Topics
- Manufacturing Process and Optimization (4 papers)Additive Manufacturing and 3D Printing Technologies (4 papers)Surface Roughness and Optical Measurements (2 papers)
- Journals
- Journal of Materials Processing TechnologyInternational Journal of Machine Tools and ManufactureInternational Journal of Precision Engineering and Manufacturing
- Partner nations
- South Korea
In The Last Decade
Daekeon Ahn
7 papers receiving 682 citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Automotive Engineering 619
- Mechanical Engineering 468
- Industrial and Manufacturing Engineering 401
- Biomedical Engineering 136
- Building and Construction 63
Countries citing papers authored by Daekeon Ahn
This map shows the geographic impact of Daekeon Ahn's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daekeon Ahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daekeon Ahn more than expected).
Fields of papers citing papers by Daekeon Ahn
This network shows the impact of papers produced by Daekeon Ahn. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daekeon Ahn. The network helps show where Daekeon Ahn may publish in the future.
Co-authorship network of co-authors of Daekeon Ahn
This figure shows the co-authorship network connecting the top 25 collaborators of Daekeon Ahn. A scholar is included among the top collaborators of Daekeon Ahn based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daekeon Ahn. Daekeon Ahn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 101 | |
| 2 | Representation of surface roughness in fused deposition modelingbreakdown → | 330 |
| 3 | 22 | |
| 4 | 137 | |
| 5 | Improving the Surface Roughness of SL Parts Using a Coating and Grinding Process | 16 |
| 6 | 97 | |
| 7 | 5 |
About Daekeon Ahn
Daekeon Ahn is a scholar working on Industrial and Manufacturing Engineering, Automotive Engineering and General Materials Science, having authored 7 papers that have together received 708 indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (4 papers), Additive Manufacturing and 3D Printing Technologies (4 papers) and Surface Roughness and Optical Measurements (2 papers). The work is most often cited by research in Automotive Engineering (619 citations), Industrial and Manufacturing Engineering (401 citations) and Mechanical Engineering (468 citations). Daekeon Ahn has collaborated with scholars based in South Korea. Frequent co-authors include Seok‐Hee Lee, Jin‐Hwe Kweon, Ho-Chan Kim, Soon Man Kwon, Jung‐il Song, Jinho Choi, A. N. Sreeram and Woo‐Sung Jang. Their work appears in journals such as Journal of Materials Processing Technology, International Journal of Machine Tools and Manufacture and International Journal of Precision Engineering and Manufacturing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.