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Data scienceBlast furnaceOff-line simulation modelOperational improvement

Data Science

Simulation Model for Estimation of the Blast Furnace Cohesive Zone

This off-line simulation model for estimating the 2-dimensional distributions of temperature, pressure, and the reduction ratio in the blast furnace provides quantitative support for understanding the condition of operation and studying operational improvement measures.

Solution Point

  • Visualizes the blast furnace condition based on blast furnace operational parameters, the burden distribution, the furnace body profile, etc.
  • Performing simulations using this model before applying proposed improvements in actual operation accelerates the PDCA cycle of improvement actions, and also prevents operational trouble due to poor operation planning.
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Features 01

Expected Problems
?We want to visualize and understand the condition in the blast furnace with the current operational parameters.
?We want to implement operational improvements, but we're not making any progress because we don't understand how the improvement actions will affect blast furnace operation.

Features 02

Technology highlight
Using blast furnace operational parameters (raw material blend and quality, blast conditions, etc.), the condition of burden distribution, and the furnace body profile as input items, the 2-dimensional (furnace radius x height) distribution of the temperature, pressure, and reduction ratio in the blast furnace is estimated by a steady-state 2D model using the finite element method (FEM), and the main operational parameters and 2D heat maps are output.
高炉融着帯推定モデル

Features 03

Proposed Solutions (Examples)
This model has been applied to all blast furnaces in 汤头条 Steel, and is now being used in anomaly avoidance and operational improvement by visualization of the condition in the blast furnace.
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