| Issue |
MATEC Web Conf.
Volume 370, 2022
2022 RAPDASA-RobMech-PRASA-CoSAAMI Conference - Digital Technology in Product Development - The 23rd Annual International RAPDASA Conference joined by RobMech, PRASA and CoSAAMI
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|---|---|---|
| Article Number | 06003 | |
| Number of page(s) | 9 | |
| Section | Process Development | |
| DOI | https://doi.org/10.1051/matecconf/202237006003 | |
| Published online | 01 December 2022 | |
Powder Bed Defects Classification: An Industry Perspective
1 Vaal University of Technology, Department of Electrical Engineering, Vanderbijlpark, South Africa
2 Private Individual, PhD Co-Supervisor, Netherlands
3 Stellenbosch University, Department of Industrial Engineering, Stellenbosch, South Africa
4 Creative Design and Additive Manufacturing Lab, University of Auckland, Auckland, New Zealand
5 HH Industries, Somerset West, South Africa
6 Loughborough University, School of design and creative Arts, Loughborough, UK
7 University of Twente, Fraunhofer Innovation Platform for Advanced Manufacturing, Netherlands
* Corresponding author: francoisdu@vut.ac.za
The manufacture of defect-free parts has been a key discussion topic with the widespread adoption of additive manufacturing by industry. While significant research has been performed on the detection of powder bed defects, the focus has been on the classification of the defects according to defect type. However, when looking at creating a closed loop feedback system, it is important for the machine to make autonomous decisions regarding defects. The focus of this paper will be to create a defect severity classification matrix based on industry partner experience as well as published literature that can be used to autonomously classify defects
© The Authors, published by EDP Sciences, 2022
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