Digital-Twin and LLM Decision Support for Thickening–Dewatering
March 1, 2026
This project developed an operational decision-support workflow for a thickening–dewatering line. It joins field measurements, condition recognition, a process digital twin, and an LLM layer with retrieval, Text2SQL, and controlled tool use. The public description omits the industrial partner, site, and operating values.
System scope
- process-data access and online condition recognition;
- a digital representation of the thickening–dewatering equipment;
- retrieval over technical documents and structured production data;
- tool-mediated analysis with the operator retained in the decision loop.
Research connection
The project supplied an application setting for work on specialist-model adaptation under operating shifts. The associated preprint presents the method and evaluation protocol without exposing production identifiers.
Authors
PhD Candidate
Youcheng Zong is a PhD candidate in Control Science and Engineering at Northeastern University, China. He develops LLM-based methods for industrial forecasting, measurement correction, model adaptation, and decision support. He also studies structure-aware visual analysis for medical imaging.
