Issue |
MATEC Web Conf.
Volume 406, 2024
2024 RAPDASA-RobMech-PRASA-AMI Conference: Unlocking Advanced Manufacturing - The 25th Annual International RAPDASA Conference, joined by RobMech, PRASA and AMI, hosted by Stellenbosch University and Nelson Mandela University
|
|
---|---|---|
Article Number | 11002 | |
Number of page(s) | 12 | |
Section | Rapid Casting | |
DOI | https://doi.org/10.1051/matecconf/202440611002 | |
Published online | 09 December 2024 |
The introduction of modern techniques in 3D printing of sand cores and moulds – a review
1 Department of Engineering Metallurgy, University of Johannesburg, South Africa
2 Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, South Africa
3 Department of Metallurgical and Materials Engineering, Air Force Institute of Technology, Nigerian Air Force, Kaduna
* Corresponding author: samsoniumdare@gmail.com
Growing technological innovation has led to faster, easier, and more efficient methods of getting things done. Owing to increasing requests for parts and the need to enhance 3D printing of sand cores and moulds and their conventional counterparts, Artificial intelligence (AI) and Smart systems are expected to address the existing challenges in using these techniques. Conventional metal-casting techniques often necessitate the application of tools in the design of patterns, cores, dies and moulds. Also, specialised skills are needed for pattern-making in wood, plastic or other materials. Metallurgical models dealing with shrinkage rates, machining, draft allowances and solidification in diverse metals, are essential considerations in pattern designing. Furthermore, the possibility of using 3D sand core and mould printing in high-tech applications necessitates minimal error or error-free production of parts. Therefore, this review explores how AI and Smart systems could be introduced into conventional and 3D printing to make the techniques suitable for high-tech applications, such as in the biomedical, aerospace and automotive industries.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.