Industrial Tokenization for LLM-Based Health Intelligence: A Federated Architecture for Industrial Evidence Integration
Industrial health management increasingly relies on heterogeneous information sources, including condition monitoring systems, supervisory control and data acquisition systems, maintenance records, inspection results, and prognostic models. Although large language models provide new opportunities for cross-source reasoning, industrial data and analytical outputs differ substantially in structure, temporal resolution, physical meaning, and reliability. Directly integrating such heterogeneous information into a monolithic model may reduce interpretability, traceability, and adaptability to equipment and data changes. This paper introduces Industrial Tokenization, a conceptual interface for ...
| Authors | Deshui Li, Xiao-Ming Yuan, Zishun Wang |
|---|---|
| Primary category | cs.AI |
| Published | 24 July 2026 |
| Last updated at source | 24 July 2026 |
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