Reduction in slabbing-mill roll wear

Metallurgist ◽  
1981 ◽  
Vol 25 (8) ◽  
pp. 321-322
Author(s):  
V. I. Beznos ◽  
A. E. Rudnev ◽  
D. I. Isirov ◽  
B. E. Dubinskii ◽  
I. A. Titarenko
Keyword(s):  
Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 859
Author(s):  
Natalia Vasilyeva ◽  
Elmira Fedorova ◽  
Alexandr Kolesnikov

Big data analysis is becoming a daily task for companies all over the world as well as for Russian companies. With advances in technology and reduced storage costs, companies today can collect and store large amounts of heterogeneous data. The important step of extracting knowledge and value from such data is a challenge that will ultimately be faced by all companies seeking to maintain their competitiveness and place in the market. An approach to the study of metallurgical processes using the analysis of a large array of operational control data is considered. Using the example of steel rolling production, the development of a predictive model based on processing a large array of operational control data is considered. The aim of the work is to develop a predictive model of rolling mill roll wear based on a large array of operational control data containing information about the time of filling and unloading of rolls, rolled assortment, roll material, and time during which the roll is in operation. Preliminary preparation of data for modeling was carried out, which includes the removal of outliers, uncharacteristic and random measurement results (misses), as well as data gaps. Correlation analysis of the data showed that the dimensions and grades of rolled steel sheets, as well as the material from which the rolls are made, have the greatest influence on the wear of rolling mill rolls. Based on the processing of a large array of operational control data, various predictive models of the technological process were designed. The adequacy of the models was assessed by the value of the mean square error (MSE), the coefficient of determination (R2), and the value of the Pearson correlation coefficient (R) between the calculated and experimental values of the mill roll wear. In addition, the adequacy of the models was assessed by the symmetry of the values predicted by the model relative to the straight line Ypredicted = Yactual. Linear models constructed using the least squares method and cross-validation turned out to be inadequate (the coefficient of determination R2 does not exceed 0.3) to the research object. The following regressions were built on the basis of the same operational control database: Linear Regression multivariate, Lasso multivariate, Ridge multivariate, and ElasticNet multivariate. However, these models also turned out to be inadequate to the object of the research. Testing these models for symmetry showed that, in all cases, there is an underestimation of the predicted values. Models using algorithm composition have also been built. The methods of random forest and gradient boosting are considered. Both methods were found to be adequate for the object of the research (for the random forest model, the coefficient of determination is R2 = 0.798; for the gradient boosting model, the coefficient of determination is R2 = 0.847). However, the gradient boosting algorithm is recognized as preferable thanks to its high accuracy compared with the random forest algorithm. Control data for symmetry in reference to the straight line Ypredicted = Yactual showed that, in the case of developing the random forest model, there is a tendency to underestimate the predicted values (the calculated values are located below the straight line). In the case of developing a gradient boosting model, the predicted values are located symmetrically regarding the straight line Ypredicted = Yactual. Therefore, the gradient boosting model is preferred. The predictive model of mill roll wear will allow rational use of rolls in terms of minimizing overall roll wear. Thus, the proposed model will make it possible to redistribute the existing work rolls between the stands in order to reduce the total wear of the rolls.


1975 ◽  
Vol 61 (3) ◽  
pp. 371-387 ◽  
Author(s):  
Katsumi SUZUKI ◽  
Kenji TAKAHASHI ◽  
Tadashi NISHI ◽  
Hiroshi KOHIRA ◽  
Masao HORI

Author(s):  
Katsumi SUZUKI ◽  
Kenji TAKAHASHI ◽  
Tadashi NISHI ◽  
Hiroshi KOHIRA ◽  
Masao HORI

Metallurgist ◽  
1979 ◽  
Vol 23 (4) ◽  
pp. 273-275
Author(s):  
V. A. Chegolya ◽  
V. T. Litvinenko ◽  
V. G. Chernyatevich ◽  
A. F. Trofimov
Keyword(s):  

2018 ◽  
Author(s):  
S.K. Thakur ◽  
S. K. Mohapatra ◽  
P. Pathak ◽  
D. Roy ◽  
C. Mishra

2012 ◽  
Vol 535-537 ◽  
pp. 697-700
Author(s):  
Zhong Feng Guo ◽  
Jun Hong Hu ◽  
Xue Yan Sun

Roll wear model for Hot Strip Mill (HSM) was researched and the factors affect roll wear are analyzed. The simulation program was compiled by program visual C++ language and work roll wear was calculated according to the rolling schedule. Calculation results shows that roll wear like box shape. Strip width affects roll wear clearly. The strip length is one of the important issues which affect roll wear. Work roll wear of F7 top roll middle get to 280μm after a rolling schedule. Roll wear curve calculated by program were good agreement with the wear curve got by high-precision grinder. The results show that the roll wear model has high accuracy.


2015 ◽  
Vol 220-221 ◽  
pp. 898-904 ◽  
Author(s):  
Piotr Szota ◽  
Sebastian Mróz ◽  
Andrzej Stefanik ◽  
Henryk Dyja

Numerical modelling of the round bar rolling process, while considering the wear of passes depending on their shape, was carried out within the present work. The analysis of the rolling process was conducted thus analysing the influence of interstand tension on roll wear. For the theoretical study of the rolling process, Forge2011® was employed, which is finite element method-relying software that enables the thermo-mechanical simulation of rolling processes in a triaxial state of strain. The wear model implemented in Forge2011® permits no quantitative evaluation, but only a comparative analysis of the wear of rolls. In order to use the results of simulation employing the simplified Archard model for the quantitative evaluation of roll wear, it is necessary to define the factor of wear and the hardness of the tool as a function of temperature.


2019 ◽  
Vol 60 (5) ◽  
pp. 770-776 ◽  
Author(s):  
Atsuo Yamamoto ◽  
Yoshio Ishii ◽  
Hyo-Gyoun Kang ◽  
Futoshi Sakata ◽  
Akio Sonoda ◽  
...  

Author(s):  
Carlos Arturo Vega Lebrún ◽  
Rumualdo Servin Castañeda ◽  
Genoveva Rosano Ortega ◽  
Juan Manuel Lopez ◽  
José Luis Cendejas Valdéz ◽  
...  

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