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An Intelligent Logic-Based Mold Breakout Prediction System Algorithm for the Continuous Casting Process of Steel: A
Md Obaidullah Ansari1, Joyjeet Ghose2, Somnath Chattopadhyaya1
1Indian Institute of Technology, Dhanbad 826004, India.
Micromachines
|December 23, 2022
Summary
A new logic-based breakout prediction system (BOPS) effectively detects mold breakouts in continuous casting machines. This system achieves 100% detection with minimal false alarms, improving safety and reducing production loss.
Area of Science:
- Metallurgical Engineering
- Process Control Systems
- Materials Science
Background:
- Mold breakouts are critical issues in continuous casting, causing safety hazards, high costs, and production downtime.
- Existing systems may struggle with diverse breakout causes and accurate localization.
Purpose of the Study:
- To develop and validate a logic-judgment-based mold breakout prediction system (BOPS) for continuous casting machines.
- To enhance breakout detection accuracy, reduce false alarms, and identify breakout locations.
Main Methods:
- Development of specialized algorithms to detect various sticker behaviors and other breakout causes.
- Integration of an online thermal map for process visualization and prediction assistance.
- Implementation of alerts and automatic cast speed reduction based on real-time data.
Main Results:
- Achieved 100% detection of all 13 breakouts in field applications.
- Reduced false alarm frequency to less than 0.056% per heat.
- Successfully detected breakouts from sticker behaviors, casting speed variations, and mold issues.
Conclusions:
- The developed logic-based BOPS is highly effective in predicting and preventing mold breakouts.
- The system offers advantages over neural networks due to minimal learning data requirements.
- BOPS enhances operational safety and efficiency in steel production.
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