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A Low-Cost but Effective Way of Mill Level 2 Upgrade
To Improve Both Shape and Property

(Extended Summary)

ˇˇ

Bingji Li,Ph,D
 Metal Pass LLC, Pittsburgh, PA, USA.
www.metalpass.com
Email: bli@metalpass.com,
Phone (China): 13400064848
ˇˇ

Level 2 system, usually counting for below 0.5% of the strip/plate equipment investment, is nevertheless the brain and nerve of the entire production line, and determines the utilization performance of the product line. Usually, after 5-10 years of Level 2 installation, an upgrade or new installation is needed for optimized equipment utilization. In view of product quality, the primary purpose of mill Level 2 model is to create quality draft schedule for both shape and property. Current Level 2 systems in the market usually have many weaknesses such as issues in learning logics and lack of microstructure evolution consideration in model calculation. For example, plate rolling after hold is technically a cold rolling since recrystallization is not completed; traditional modeling based on hot rolling leads to high parameter prediction error and insufficient product quality. The author’s investigation through technical exchange with six steel enterprises from TISCO to Sha-Steel and Baosteel indicates that most rolling mills have issues of production process instability, poor strip/plate shape of high grade products, and instable product properties, etc. Those, from technical aspect, result from insufficient quality of the Level 2 system.

In the current steel industry with a small profit margin, it is pursued by every steel producer to produce high grade products at low cost in optimal process. For 8 years, Metal Pass has developed a simple, low-cost but very effective way of Level 2 system upgrade, to transform existing Level 2 system into the world’s top-quality new-generation Level 2 with microstructure models and intelligent learning. This way of upgrade does not need major modification of the Level 2 source code, but rather integrate over 6,000-20,000 sets of proven, high-quality data models into the current Level 2 system, by using Metal Pass?Guided Dual-Variable Learning. Since most models are ready to use and no interfaces to other systems need to be developed, the upgrade only costs 1/10 of the new Level 2 installation. This paper summarizes work results in several mill-Level 2 upgrades, especially Level 2 parameter prediction improvement and metallurgical integration into Level 2 model. Features for the new-generation Level 2 model as metallurgical system are also introduced. In this way of upgrade, offline design was performed first on the basis of the rolling process and product models the author created in the past 20 years during the work in Germany and USA. The models take into account metallurgical phenomena such as incompleted recrystallization and thus induced residual strain due to micro-alloy application. This procedure has also removed learning logic defects incurred in almost every Level 2 package in the market. Then the results were integrated into the online learning of the Level 2 System. The upgraded Level 2 system achieves extremely high parameter prediction accuracy. This makes it possible to increase operational upper limit of rolling force.

Keywords: Level 2 Upgrade, Level 2 Accuracy, Microstructure Model, Product Quality

More details, click here.


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