This study analyzes a low-cost reliable real-time optical monitoring platform for fused filament fabrication-based open source 3D printing. An algorithm for reconstructing 3D images from overlapping 2D intensity measurements with relaxed camera positioning requirements is compared with a single-camera solution for single-side 3D printing monitoring. The algorithms are tested for different 3D object geometries and filament colors. The results showed that both of the algorithms with a single- and double-camera system were effective at detecting a clogged nozzle, incomplete project, or loss of filament for a wide range of 3D object geometries and filament colors. The combined approach was the most effective and achieves 100% detection rate for failures. The combined method analyzed here has a better detection rate and a lower cost compared to previous methods. In addition, this method is generalizable to a wide range of 3D printer geometries, which enables further deployment of desktop 3D printing as wasted print time and filament are reduced, thereby improving the economic advantages of distributed manufacturing.
- Open source code for Matlab https://osf.io/hwdzm/
Keywords[edit | edit source]
Real-time monitoring, 3D printing, Optical monitoring, RepRap, Open hardware, Quality assurance
See also[edit | edit source]
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- OS Computer Vision for Distributed Recycling and Additive Manufacturing
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- Additional OS Computer Vision Applications
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