Automated Process Monitoring in 3D Printing Using Supervised Machine Learning
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering
Reference8 articles.
1. G. White, Industry analysis: The pros and cons of 3D printing (2015). Retrieved from http://www.manufacturingglobal.com/
2. Initial work on the characterization of additive manufacturing (3D printing) using software image analysis;Straub;Journal of Machines,2015
3. An approach to monitoring quality in manufacturing using supervised machine learning on product state data;Wuest;Journal of Intelligent Manufacturing,2014
4. J. Fastowicz, K. Okarma, Texture based quality assessment of 3D prints for different lighting conditions. In Proceedings of the International Conference on Computer Vision and Graphics, ICCVG (2016) 17-28.
5. Effects of layer thickness and binder saturation level parameters on 3D printing process;Vaezi;International Journal of Advanced Manufacturing Technology,2011
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