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|Title:||Experiments with machine vision for polymer flowability analysis in powder bed fusion||Authors:||Ituarte, Iñigo Flores
Powder Bed Fusion
|Issue Date:||2018||Source:||Ituarte, I. F., Huotilainen, E., Wiikinkoski, O., & Tuomi, J. (2018). Experiments with machine vision for polymer flowability analysis in powder bed fusion. Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018), 401-406. doi:10.25341/D4859D||Abstract:||This research explores the real-time process control of polymer flowability in Powder Bed Fusion (PBF). To do so, a novel system based on machine vision and an image-processing algorithm was developed and tested in an open hardware and software PBF system. The system has the ability to analyze the quality of the powder bed by computing a defect ratio of the powder bed after each recoating operation. Then, this ratio is used as a performance variable in three full factorial Design of Experiments (DOE). The results show that the installation of machine vision and image processing system can potentially provide a signal to repeat the recoating process and correct the defect on the powder bed. At the same time, recoating process parameters can be adjusted dynamically to guarantee an optimum quality of the powder bed and minimize possible build failures.||URI:||https://hdl.handle.net/10356/88587
|DOI:||https://doi.org/10.25341/D4859D||Rights:||© 2018 Nanyang Technological University. Published by Nanyang Technological University, Singapore.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||Pro-AM Conference Papers|
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