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Shape, Property, Productivity
 
NISCO Plate/Coil Mill Level 2 Force Model Improvements


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2.8 Grade File Generation

For the current Level 2, data for each model grade is stored in a separate grade file. Such a grade file contains about 300 lines of model data (including those reserved for future use). Data in a grade File consists of mechanical, physical, thermal and mill operational parameters. Flow stress coefficients for low, medium and high temperature regions are among those data. In the original Level 2, if the grade file for a model grade were missing in the computer, there wouldn be any draft schedule for this model grade.

By end 2010, NISCO has about 6406 model grades based on its number of grades, product mix and production procedure. Correspondingly, there are about 6406 grade files. While increasing number of grade files from about 800 to over 6000, the files were redesigned, which means all the data in each grade file are adjusted or recalculated. Newly calculated data for the grade file are stored in the database tables, just like the flow stress coefficients. Thermal and mechanical parameters are used for the high-temperature calculation for the rolling process. Data for the grade files were mainly calculated based on Metal Pass metal properties databases [6][7] and based on past studies. During the data collection as described above, data in over 800 grade files were read into database. Throughout the grade and model grade redesign, those data for each model grade were also recalculated.

In creating a grade file, contents (text string) were copied from the corresponding old grade file, line by line, and inserted into the new grade file in the exact the same order and same format; in the mean time, new data (flow stress, physical and other mechanical, mill operational, etc.) were read from the database tables and were used to replace the old data. Name of each grade file followed the name of the model grade. In this way, the data is new, but the format remains the original one.

2.9 Resume Pass Model Improvement

Hold is a common practice in the plate rolling. After certain number of passes, steel is put in the air (sometimes, it could be ACC) to cool, until it reaches certain temperature instructed in the Level 3 PDI. During the hold, there are metallurgical processes incurred inside steel, so in the pass right after the hold, the so-called resume pass, there is significant force error.

Error analysis indicates that, the force error is highly affected by the resume temperature (the temperature in the entry of the resume pass) and other metallurgical parameters. Therefore, model modification was made for the resume pass. In the modified model, the force predicted with regular procedure is further divided by a modification factor calculated from a set of related parameters.

2.10 Miscellaneous Improvements

Flow stress formula used in the Level 2, as described in equation (1), only has a narrow valid range, so modifications were made in passes, in order to reduce the force prediction error.

Ranges of temperature regions were redesigned. The Guided Two-Parameter Fitting (FIT2G) only needs a narrowed temperature range. Temperature range for the finish passes was narrowed to improve prediction accuracy. Force prediction accuracy in the finish passes is more critical for good shape than in other passes.

2.11 Source Code Modification

Throughout the project, it is a strategy to modify as little source code as possible, in order to avoid introducing new error into the system. The function change was mainly through offline design.

Primary modifications to the source code exist in two areas: to apply the FIT2G and to add the resume pass modification factors by reading a new flat file containing the constants a and b. However, in such a large software system, any minor modification for the logics, especially the very fundamental logics in the force prediction, would affect many files. This part of source code modification, together with the related function improvement, actually involves about 30 files. Besides the application of the FIT2G, model grade naming convention was also changed. In the shared memory, variables a and b were added for each steel grade. The primary change was to restrain C3 and C4 from being updated during the learning.

<To Be Continued>

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