Modeling and Simulation of Shape Control Based on Digital Twin Technology in Hot Strip Rolling.

Area of Science:

• Materials Science and Engineering
• Manufacturing Processes
• Computational Modeling

Background:

• Strip shape quality control is critical in hot rolling finishing.
• Existing models often lack accuracy in predicting complex shape variations.
• Integrating physical and virtual processes is key to advanced manufacturing.

Purpose of the Study:

• To develop a novel shape model for hot rolling strip quality control.
• To create a digital twin framework for real-time shape simulation and prediction.
• To enhance the precision of strip shape prediction using historical data and iterative optimization.

Main Methods:

• A shape model based on metal flow and stress release with varying contact rolling parameters.
• Integration with digital twin technology for a unified physical-virtual framework.
• Iterative parameter optimization using historical production data.

Main Results:

• The digital twin framework successfully integrates physical and virtual time-space.
• Strip shape simulation accurately predicts various export conditions.
• Prediction errors for crown and flatness were below 5 μm and 5 I-unit, respectively.

Conclusions:

• The proposed shape simulation model demonstrates strong predictive performance for hot rolling.
• The model serves as a valuable reference for operators in parameter setting.
• This work promotes intelligent shape control strategies in industrial applications.