Digital-Twin and LLM Decision Support for Thickening–Dewatering

Sun, 01 Mar 2026 00:00:00 +0000

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.

Intelligent Transformation and State Recognition for Blast-Furnace Iron Tapping

Thu, 01 Dec 2022 00:00:00 +0000

The system combines field instrumentation and communication with molten-iron level tracking, Bi-GRU state recognition, post-processing, and an operator interface. The industrial partner and furnace identifiers are omitted from the public version.

Technical focus

continuous extraction of level-related process signals;
temporal state recognition using a Bi-GRU composite model;
post-processing rules for stable tapping-state decisions;
integration of algorithm services with industrial data and visualization.

Public outputs