Generating Authentic Grounded Synthetic Maintenance Work Orders
Large language models (LLMs) are promising for generating synthetic technical data, particularly for industrial maintenance where real datasets are often limited and unbalanced. This study generates synthetic maintenance work orders (MWOs) that are grounded to accurately represent engineering knowle...
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| Main Authors: | Allison Lau, Jadeyn Feng, Melinda Hodkiewicz, Caitlin Woods, Michael Stewart, Adriano Polpo |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11124200/ |
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