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Integration of Metallurgical Model into Mill Level 2

Integration with metallurgical model can greatly improve the quality of the Level 2 model. Traditional Level 2 model was designed without metallurgical concept in mind. Such a design, however, is facing increasing challenge due to the application of the new rolling technologies such as the low temperature rolling, hold between rolling passes including the two-piece rolling and the use of microalloy for the steel. In the low temperature rolling the recrystallization often cannot be completed and this causes a retained strain from pass to pass.

A slight modification of the Level 2 model with metallurgical principle would create great benefit. In many times, the modification is only necessary for the input data files or inside a single function in a single file. The resume pass after the hold may have over 40% force error, as in the case of a client. Modification for such a system is necessary. Quite often, in the finish pass with the draft 10% or lower, some formula is actually not valid. This cause force error, and thus a wrong draft schedule would be created and bad shape of the steel is produced.

What to Integrate

Metal Data, with its rich experiences in integrating metallurgical models into mill Level 2 systems, has identified various issues in the present Level 2 models and a long list of metallurgical parameters to be integrated into current Level 2 systems. Contact us via bli68@qq.com for a list of metallurgical parameters and related models specific to your Level 2 model and mill practice.

How to Integrate

Metallurgical models to be integrated into the existing Level 2 system don't have to be a very complicated one. Integration in various levels of complicity could be performed. Special attention should be paid to protect the existing Level 2 system from any possible damage.

  • Modification of existing Level 2 model, preferably, the modification of only a function or only a file.
  • Attaching a metallurgical model package, e.g., the one to predict the retained strain, into an existing Level 2 system. If the metallurgical model to be added into an existing system is pretty complicated, it is preferred to create an extra software package to be attached into the existing Level 2 system.
  • Modification of an input file or an input database, without the change of actual source code.

Existing Level 2 model can be improved with the metallurgical effects being integrated into Level 2 parameters. For example, the effect of the retained strain may be integrated into the strain coefficient C3. In a consulting project for a steel plate reversing mill, 6000 sets of new coefficients for the flow stress were designed by integrating retained stain into those coefficients, and the flow stress for the resume pass was modified. In this way, the metallurgical effects were added into the existing Level 2 system with minimal change of source code, because most changes were for the data in the database. Due to the inclusion of the metallurgical effects, much higher prediction accuracy was achieved with the force error below 5% in most passes for the previously troubled grades and sizes.

Model Development

Metallurgical models are usually very complicated and are very cost-intensive to develop. Currently available metallurgical models, mainly off-line ones, don't have sufficient prediction accuracy and thus are not widely accepted. Microstructure model development from Metal Data integrates our metallurgical model into the steel mill online systems (Level 2 systems) to utilize accurate rolling process parameters. In addition, we have advanced learning technologies, so in all the trials, the neural network learning will be used, and the expert system and fuzzy logic rules will be applied to specify the value boundaries. More detailed, such a system consists of followings:

  • An expert system, which consists of logics, data and influence factors on the mechanical, thermal and metallurgical parameters depending on rolling and thermal processes. Past mill-experiences can be programmed as a portion of the expert system.
  • A hybrid intelligent learning system, based on rolling process models, in which the neural network provides the correcting factors for the model coefficients, and fuzzy logic rules and expert system provide guidelines (upper and lower boundaries, etc.) for the learning.


Related Resources

Metal Data Work List on Level 2 and Mill Modeling

 Metal Data Recent Publications

Technical papers published in the February and March of 2008. Those publications are primarily on Level 2, Level 2 model and process automation.

Metal Data has dozens of research reports and some software applications available at no charge for the consulting clients (only for the projects in the name of Metal Data and approved by Dr. Benjamin Li).


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