Machine learning and sensor-based approach for defect detection in MEX additive manufacturing process- A Review-Reference-Cited by-同舟云学术

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Machine learning and sensor-based approach for defect detection in MEX additive manufacturing process- A Review

Published:2023-09-23 Issue:10 Volume:45 Page:
ISSN:1678-5878
Container-title:Journal of the Brazilian Society of Mechanical Sciences and Engineering
language:en
Short-container-title:J Braz. Soc. Mech. Sci. Eng.

Author:

Selot Avinash,Dwivedi R. K.

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,General Engineering,Aerospace Engineering,Automotive Engineering,Industrial and Manufacturing Engineering,Applied Mathematics

Link

https://link.springer.com/content/pdf/10.1007/s40430-023-04425-1.pdf

Reference164 articles.

1. MacDonald E, Wicker R (2016) Multiprocess 3D printing for increasing component functionality. Science. https://doi.org/10.1126/science.aaf2093

2. Gibson I, Rosen D, Stucker B, Khorasani M (2021) Additive manufacturing technologies. Addit Manuf Technol. https://doi.org/10.1007/978-3-030-56127-7

3. Standard A (2012) Standard terminology for additive manufacturing technologies. ASTM Int F2792–12a

4. Elkaseer A, Schneider S, Scholz SG (2020) Experiment-based process modeling and optimization for high-quality and resource-efficient FFF 3D printing. Appl Sci 10:2899. https://doi.org/10.3390/app10082899

5. Wohlers Report (2022) Finds Strong Industry-Wide Growth-Wohlers Associates. https://wohlersassociates.com/press-releases/wohlers-report-2022-finds-strong-industry-wide-growth/. Accessed 22 Sep 2022

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