A review of physics-informed and data-driven approaches for manufacturing process optimization in polymer matrix composites
Machine learning approaches that integrate physical laws with data-driven models are transforming process optimization and quality assurance in polymer matrix composite manufacturing. This review synthesizes recent developments in neural metamodels for injection molding, spatio-temporal digital twin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Advanced Manufacturing: Polymer & Composites Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/20550340.2025.2547335 |
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