Recent developments in the application of machine-learning towards accelerated predictive multiscale design and additive manufacturing
| Autor: | Sandeep Suresh Babu, Abdel-Hamid I. Mourad, Khalifa H. Harib, Sanjairaj Vijayavenkataraman |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Virtual and Physical Prototyping, Vol 18, Iss 1 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1745-2759 1745-2767 17452759 |
| DOI: | 10.1080/17452759.2022.2141653 |
| Popis: | The application of three-dimensional (3D) printing/Additive Manufacturing (AM) for developing multi-functional smart/intelligent composite materials is a highly promising area of engineering research. However, there is often no reliable means for predicting and modelling the material performance, and the wide-scale industrial adoption of AM is limited due to factors such as design barriers, limited materials library, processing defects and inconsistency in product quality. A comprehensive framework considering the generalised applicability of ML algorithms at sub-sequent stages of the AM process from the initial design to the post-processing stages in the literature is lacking. In this paper, the integration of various ML applications at various sub-processes is discussed, including pre-processing design stage, parameter optimisation, anomaly detection, in-situ monitoring, and the final post-processing stages. The challenges and potential solutions for standardising these integrated techniques have been identified. The article is promising for professionals and researchers in AM and AI/ML techniques. |
| Databáze: | Directory of Open Access Journals |
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