Next Article in Journal
Analytical and Numerical Temperature Prediction in Direct Metal Deposition of Ti6Al4V
Previous Article in Journal
Journal of Manufacturing and Materials Processing—A New Open Access Engineering Journal
Open AccessArticle

Three Hundred and Sixty Degree Real-Time Monitoring of 3-D Printing Using Computer Analysis of Two Camera Views

1
Department of Electrical & Computer Engineering, Michigan Technological University, Houghton, MI 49931, USA
2
Department of Materials Science & Engineering, Michigan Technological University, Houghton, MI 49931, USA
*
Author to whom correspondence should be addressed.
J. Manuf. Mater. Process. 2017, 1(1), 2; https://doi.org/10.3390/jmmp1010002
Received: 15 May 2017 / Revised: 19 June 2017 / Accepted: 22 June 2017 / Published: 4 July 2017
Prosumer (producing consumer)-based desktop additive manufacturing has been enabled by the recent radical reduction in 3-D printer capital costs created by the open-source release of the self-replicating rapid prototype (RepRap). To continue this success, there have been some efforts to improve reliability, which are either too expensive or lacked automation. A promising method to improve reliability is to use computer vision, although the success rates are still too low for widespread use. To overcome these challenges an open source low-cost reliable real-time optimal monitoring platform for 3-D printing from double cameras is presented here. This error detection system is implemented with low-cost web cameras and covers 360 degrees around the printed object from three different perspectives. The algorithm is developed in Python and run on a Raspberry Pi3 mini-computer to reduce costs. For 3-D printing monitoring in three different perspectives, the systems are tested with four different 3-D object geometries for normal operation and failure modes. This system is tested with two different techniques in the image pre-processing step: SIFT and RANSAC rescale and rectification, and non-rescale and rectification. The error calculations were determined from the horizontal and vertical magnitude methods of 3-D reconstruction images. The non-rescale and rectification technique successfully detects the normal printing and failure state for all models with 100% accuracy, which is better than the single camera set up only. The computation time of the non-rescale and rectification technique is two times faster than the SIFT and RANSAC rescale and rectification technique. View Full-Text
Keywords: real time monitoring; 2-D reconstruction; error detection; reliability; 3-D printing; computer analysis real time monitoring; 2-D reconstruction; error detection; reliability; 3-D printing; computer analysis
Show Figures

Figure 1

MDPI and ACS Style

Nuchitprasitchai, S.; Roggemann, M.C.; Pearce, J.M. Three Hundred and Sixty Degree Real-Time Monitoring of 3-D Printing Using Computer Analysis of Two Camera Views. J. Manuf. Mater. Process. 2017, 1, 2. https://doi.org/10.3390/jmmp1010002

AMA Style

Nuchitprasitchai S, Roggemann MC, Pearce JM. Three Hundred and Sixty Degree Real-Time Monitoring of 3-D Printing Using Computer Analysis of Two Camera Views. Journal of Manufacturing and Materials Processing. 2017; 1(1):2. https://doi.org/10.3390/jmmp1010002

Chicago/Turabian Style

Nuchitprasitchai, Siranee; Roggemann, Michael C.; Pearce, Joshua M. 2017. "Three Hundred and Sixty Degree Real-Time Monitoring of 3-D Printing Using Computer Analysis of Two Camera Views" J. Manuf. Mater. Process. 1, no. 1: 2. https://doi.org/10.3390/jmmp1010002

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop