Blast Furnace Stability Control in Ironmaking Plant Optimization
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Solution Overview
Problem
Current process optimization methods for ironmaking plants fail to consider the impact of pre-ironmaking units and operational stability, particularly the cohesive zone characteristics of the blast furnace, which are crucial for efficient operation, due to the lack of real-time estimation capabilities.
Innovation Solution
A processor-implemented method and system that collects and preprocesses data from various sources, integrates simulated data using soft sensors, determines key performance indicators and stability scores for the blast furnace, and configures optimization recommendations based on deviations from predefined thresholds to ensure operational stability and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If process optimization is carried out considering only blast furnace operation in isolation, then blast furnace performance can be improved, but the overall ironmaking plant performance cannot be optimized and operational stability is compromised
Solution Approach 1:
The patent merges the optimization of pre-ironmaking units with the blast furnace operation into a unified plant-wide optimization framework. The system integrates data from sinter plants, pellet plants, coke plants, and the blast furnace, optimizing them as a combined system rather than in isolation, thereby achieving both productivity improvement and operational stability.
Solution Approach 2:
The patent implements a feedback mechanism that continuously monitors key performance indicators and stability scores from all units, uses this information to adjust optimization parameters in real-time, and feeds the results back to maintain both productivity and operational stability across the entire ironmaking plant.
2Measurement precision
If high fidelity 2D/3D physics-based models are used to obtain cohesive zone characteristics, then operational stability can be estimated, but real-time estimation is not possible due to computational complexity
Solution Approach 1:
The patent replaces expensive, computationally intensive high-fidelity 2D/3D physics-based models with cheaper, simplified models that provide sufficient accuracy for real-time estimation of cohesive zone characteristics. These simplified models deliver the necessary measurement precision without the computational burden, enabling real-time operation.
Solution Approach 2:
The patent changes the parameters of the modeling approach by transitioning from complex spatial models to simplified empirical or reduced-order models that use key operational parameters to estimate cohesive zone characteristics in real-time, maintaining adequate precision while enabling rapid computation.
3Measurement precision
If more process parameters are monitored in pre-ironmaking units and blast furnace, then optimization accuracy can be improved, but the complexity of operation increases making it impractical for operators
Solution Approach 1:
The patent implements a self-service optimization system that automatically collects data from multiple sources, processes the information, determines optimal parameters, and generates recommendations without requiring operator intervention. The system serves itself by handling the complexity of monitoring and optimizing numerous parameters, freeing operators from manual analysis while maintaining high optimization accuracy.
Solution Approach 2:
The patent introduces an intermediary automated optimization system that acts as a mediator between the complex process parameters and the operators. This intermediary handles the complexity of monitoring and analyzing numerous parameters, translating them into actionable recommendations, thereby maintaining measurement precision while reducing operator workload.
Data Source
AI summary
State-of-the-art systems used for plant monitoring and optimization fail to efficiently monitor and improve the performance of blast furnace ironmaking plants due to complexity of such plants. In addition, they attempt optimization without considering the operational stability of the blast furnace. The disclosure herein generally relates to industrial plant monitoring, and, more particularly, to a method and system for ironmaking plant optimization. The system determines an operational stability of the plant in terms of value of a determined Blast Furnace Stability Index (BFSI). Further, if the BFSI or one or more Key Performance Indicators (KPIs) of the plant deviates from corresponding threshold, then the optimization is done.