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Michigan Tech's Open Sustainability Technology Lab.
Wanted: Students to make a distributed future with solar-powered open-source 3-D printing and recycling. |
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Pearce Publications: Energy Conservation • Energy Policy • Industrial Symbiosis • Life Cycle Analysis • Materials Science • Open Source • Photovoltaic Systems • Solar Cells • Sustainable Development • Sustainability Education
| This page is part of an international project to use RepRap 3-D printing to make OSAT for sustainable development. Learn more.
Research: Open source 3-D printing of OSAT • RecycleBot • LCA of home recycling • Green Distributed Recycling • Ethical Filament • LCA of distributed manufacturing • RepRap LCA Energy and CO2 • Solar-powered RepRaps • solar powered recyclebot • Feasibility hub • Mechanical testing • RepRap printing protocol: MOST• Lessons learned • MOST RepRap Build • MOST Prusa Build • MOST HS RepRap build • RepRap Print Server Make me: Want to build a MOST RepRap? - Start here! • Delta Build Overview:MOST • Athena Build Overview • MOST metal 3-D printer • Humanitarian Crisis Response 3-D Printer |
Source
- Nuchitprasitchai, S., Roggemann, M. & Pearce, J.M. Factors effecting real-time optical monitoring of fused filament 3D printing. Progress in Additive Manufacturing. 2(3), pp 133–149 (2017). doi:10.1007/s40964-017-0027-x open access
- Open source code for Matlab https://osf.io/hwdzm/
Abstract
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.
Keywords[edit | edit source]
Real-time monitoring, 3D printing, Optical monitoring, RepRap, Open hardware, Quality assurance
See also[edit | edit source]
| How To Run Error Detection Part 2 |
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| How To Run Error Detection Part 1 |
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