A Digital Twin Framework With Meta- and Transfer Learning for Scalable Multi-Machine Modeling and Optimization in Semiconductor Manufacturing
Despite recent advances in Digital Twin (DT) technologies for semiconductor manufacturing, no existing research convincingly demonstrates a unified, rapidly scalable, and data-efficient DT framework that can effectively handle stringent multi-objective optimization under severe data scarcity. This a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10993442/ |
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