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Data scienceBlast furnaceShaft furnaceAnomaly detectionFurnace heat

Data Science

Real-Time Blast Furnace Heat Level Evaluation Technology (New Furnace Heat Index)

Accurately detects drops in the furnace heat level, not only in steady operation, but also in unsteady operation, contributing to prevention of cooled hearth and other serious trouble.

Solution Point

  • Accurately detects drops in the furnace heat level 2-3 hours before hot metal temperature measurements by iterative detailed calculations of heat supplied per unit of hot metal in the furnace bottom (tuyere level). Reduces the risk of operational anomalies.
  • Maintains accuracy not only in steady operation, but also in unsteady operation such as before/after blowing down.
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Features 01

Expected Problems
?Want to detect the furnace heat level without waiting for hot metal temperature measurements to prevent trouble and achieve stable operation.
?Want a furnace heat index that is reliable even during unsteady operation.

Features 02

Technology highlight
?When calculating the amount of heat supplied per unit of hot metal (1 ton) in the furnace bottom (tuyere level), this technology improves the estimation accuracy of the hot metal temperature in unsteady operation by considering variables that were not considered in conventional furnace heat indexes.
高炉内の熱レベル評価技術(新炉熱指数の開発)

Features 03

Proposed Solutions (Examples)
Improves estimation accuracy of temperature of the hot metal discharged from the taphole, contributing to stabilization of blast furnace operation.
In addition, because it is possible to detect temperature drops 3 hours before tapping, anomalies can be detected without waiting for hot metal temperature measurements, also contributing to prevention of serious trouble such as cooled hearth, etc.
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