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Level 2 Model Improvement Case Study: Oregon Steel


<Continue>
 
 

3. First Improvement

Improvement of the existing Level 2 force model was primarily based on the following principles:

  • The logical learning error must be corrected, so the average values C3m and C4m should be used instead of zeros in the FIT2, FIT3A and FIT3B;

  • Limitation of the adaptive learning in FIT4 should be removed, especially the use of the widely scattered values caused by the dependence of C3-C4;

  • Metallurgical principles should be considered; so the effect of the retained strain should be reflected;

  • There should not be significant change to the existing source code.

  • Data analysis showed earlier indicated that the metallurgical process had great effects on the flow stress coefficients and was one of the primary reasons to cause C3 to scatter in a wide range and to be larger than the theoretical value. Even for the FIT4, due to the use of the widely scattered data caused by the dependence of C3 and C4, the learning quality is still limited. In the log files there were many occasions where the FIT4 had poorer quality than other fits (FIT2, FIT3A or FIT3B), even though those fits were defective with the use of 0 instead of a medium value of C3 or/and C4.

    There are various solutions possible. In developing a new Level 2 system, adding logic to improve C3-C4 dependence issue for FIT4, improving logic for FIT3A and FIT3B, and predicting retained strain, etc. would be the right solution. However, for existing system, too many modifications would introduce potential bugs and would be time consuming. For this reason, a simple but effective solution was accepted.

    In this solution, carefully designed average values for C3 and C4, covering all the above-mentioned issues including the medium values and the dependence of C3 and C4 as well as the retained strain effects, etc., were generated. Because the retained strain is affected by material composition, rolling temperature and inter-pass time, the coefficients C3 and C4 were specifically designed for each model grades in every temperature regions. As a result of implementing these coefficients in the learning process, the designed C3 and C4 remained constant and only C1 and C2 were adapted. Manipulating the retained strain into the flow stress coefficients meant that there was no need to change the flow stress formula and therefore, the change to the source code would be minimal. This learning procedure can be referred to as the Guided Two-Parameter Learning (FIT2G).

    The concept to manipulate the retained strain into the flow stress coefficient C3 was also observed in many publications such as [7] mentioned above. Those authors usually argued that the contributions from the strain and the strain rate were much less than those from the material and the temperature. Even though, using a single pair of C3 and C4 for all grades still seems too rough. In the EOS Level 2 models project, over 6000 sets of C3 and C4 were actually used! In the current production practice, EOS has over 2000 model grades. As mentioned earlier in the Introduction section, a model grade is created based on the steel grade, product and production practice, etc. For each model grade, there are three sets of coefficients, for the three temperature regions.

    Designing over 6000 sets of C3 and C4 needs a good understanding of the flow stress model. In this specific case, the contribution of the metallurgical parameters to the C3 and C4 added much more difficulty to the work. In the first step, a basic range of the C3 and C4 was created as a guideline for the coefficient design. The basic range of the C3 and C4 was determined based on various considerations such as

  • the initial values of the coefficients C3 and C4 in typical hot rolling [5],

  • the pattern of the initial values (C3 and C4) in different temperature regions, and

  • the retained strains in different temperature regions.

  • The pattern of the initial values was established through studies of published flow stress models in various sources [5].

    In EOS case, if the inter-pass time is 30-40 seconds, the percentage of the strain retained from a pass to the next is estimated in Table 3. For further details, different steel grade, etc. may have different ratio of the retained strain. At this plate mill, the inter-pass time may be longer than some strip mills, so the ratio of the retained strain here should be slightly lower than that in many strip mills with the similar rolling temperatures.

    Table 3: Ratio of Retained Strain in various Temperatures

    T (Deg C)

    1000

    900

    850

    800

    750

    T (Deg F)

    1830

    1650

    1560

    1470

    1380

    Ratio of Retained Strain

    0%

    15%

    21%

    33%

    42%

    Application of the newly designed C3 and C4 sets in the production system also involved another issue. If C1 and C2 corresponding to the new C3 and C4 were not carefully handled, there would be problem for the first piece (at least the first pass) after the new coefficients are introduced into the Level 2 system. Therefore, C1 and C2 were also carefully designed and the entire set of coefficients C1, C2, C3 and C4 were tested against the 1.5 million records of the history data. This would guarantee the smooth transition from the old coefficients to the new ones.

     

    <To Be Continued>

     

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