- author = "An-Chen Lee and Ruei-Yu Huang and Trong-Doan Nguyen and Chung-Wei Cheng and Mi-Ching Tsai",
- title = "Laser Powder Bed Fusion of Multilayer Thin-walled Structures Based on Data-driven Model",
- journal = "JLMN-Journal of Laser Micro/Nanoengineering",
- year = "2020",
- volume = "15",
- number = "1",
- pages = "38--44",
- month = jun,
- keywords = "genetic algorithms, genetic programming, symbolic regression, selective laser melting, SLM, symbolic regressed solution, data-driven model",
- ISSN = "1880-0688",
-
URL = "
http://www.jlps.gr.jp/jlmn/uploads/b8b7209c72a808bfa694af825e6835fed8cec913.pdf",
-
DOI = "
10.2961/jlmn.2020.01.2007",
- size = "7 pages",
- abstract = "The laser powder bed fusion (LPBF) process has the advantage of directly building metal parts with complex geometries and lattice structures. The lattice structures are usually composed of different thin-walled structures. Therefore, precise control over the shape of structures on the LPBF fabricated lattice structures is important. a symbolic regression solution that describes the relationship between scan track width and process parameters (laser power and scanning velocity) is generated by empirical data. This regression model is then implemented into the control scheme that stabilizes the structure width for single-layer and multilayer thin-walled structures. The experiment results showed that the average errors for the single-layer track with desired width from 120 micrometers to 180 um are all under 5 percent, and the average error for the ten-layered structures with desired width 180 micrometers about 2.2 percent.",
-
notes = "http://www.jlps.gr.jp/jlmn/
Department of Mechanical Engineering, National Chiao Tung University, No. 1001, Ta Hsueh Road, Hsinchu 300, Taiwan",
