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Anomaly detectionOperation stabilizationTrouble avoidanceImprovement of production efficiencySkill transfer

Data Science

Intelligent Blast Furnace Operation Support System

Gain visibility into the internal condition of the blast furnace, a highly complex process with long operational time constants, through a Digital Twin based virtual blast furnace model.
Provides operational guidance and early anomaly detection alerts, helping operators maintain stable, efficient, and reliable blast furnace performance.

Solution Point

  • A lineup of advanced models enables stable blast furnace operation through heat guidance which predict furnace heat for optimum action, and early detection of abnormalities in permeability, furnace heat, and slag level.
  • Also includes indexes/mechanisms for automatic evaluation of the reliability of operational and sensor data, which is extremely important in realizing the digital twin.
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Features 01

Expected Problems
・Facing challenges due to variations in operator skill levels?
・Struggling to stabilize hot metal temperature due to reactive operations?
・Struggling to recognize anomalies in furnace conditions early enough?
・Struggling to transfer operational know-how to the next generation?

Features 02

Technology highlight
A comprehensive lineup of online models visualizes and predicts blast furnace conditions.
The optimal model combination is tailored to your operational challenges and furnace conditions.
[For details of each model, please see the following links.]

Real-time visualization of internal conditions enables highly efficient and stable operations.

Features 03

Proposed Solutions (Examples)
・Detection of operational anomalies in the blast furnace and provision of operational guidance.
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