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Improvement of Rolling Load Prediction with Consideration of Spread in Hot Rolling
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 Title & Authors
Improvement of Rolling Load Prediction with Consideration of Spread in Hot Rolling
Jeong, Jong-Yeop; Im, Yong-Taek;
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Thickness control of hot-rolled strips has become an important issue in recent years because of the need for improving the quality of the hot-rolled strip. In this study, a modifying method of rolling force set-up with consideration of spread was developed to improve the thickness uniformity at the finishing rolling units in hot rolling. Through the analysis of real production data it was found that the accuracy of the rolling force determined from the finishing mill set-up (FSU) model dominantly governed the thickness uniformity in rolled plates at the front. Based on this analysis , several examples were selected to calculate the spread of rolled plate using three dimensional rigid thermo-viscoplastic finite element program. FE analysis results were used to train the neural network system that can predict the spread hot-rolled plate and the rolling force was modified based on the predicted value of spread. The modified rolling forces were closer to the measured rolling force so it can be expected that the accuracy of thickness uniformity of hot-rolled plate will be improved.
Hot Rolling;Finishing Mill Set-up;Spread;Finite Element Analysis;Neural Network;
 Cited by
Yamada, F., Sekiguchi, K., Tsugeno, M., Anbe, Y., Andoh, Y., Forse, C., Guernier, M. and Coleman, T., 1991, 'Hot Strip Mill Mathematical Models and Set-Up Calculation,' IEEE Tran. on Industry Application, Vol. 27, No. 1, pp. 131-139 crossref(new window)

Yamashita, M., Yarita, I., Abe, H., Mikuriya, T. and Yanagishima, F., 1987, 'Technologies of Flying Gauge Change in Fully Continuous Cold Rolling Mill for Thin Gauge Steel Strips,' IRSID Rolling Conference, 2(1), pp. E.36.1-E.36.11

Terano, T., Asai, K. and Sugeno, M., 1989, Applied Fuzzy Systems, AP Professional

Portmann, N., 1995, 'Application of Neural Networks in Rolling Mill Automation,' Iron and Steel Engineer, Vol. 72, No. 2, pp. 33-36

Pican, N., Alexander, F. and Bresson, P., 1996, 'Artificial Neural Networks for the Presetting of a Steel Temper Mill,' IEEE Expert, Vol. 11, No. 1, pp. 22-27 crossref(new window)

문영훈, 이경종, 이필종, 이준정, 1993, '보정함수를 이용한 강판의 열간 압연하중 예측정도 향상,' 대한기계학회논문집, 제17권, 제5호, pp. 1193-1201

문영훈, 한석영, 1993, '열연 강판의 선단부 두께편차 감소를 위한 마무리 압연 설정모델의 개선,' 제1회 압연심포지움 논문집-압연기술의 진보, pp. 220-238

이종영, 조형석, 심민석, 조성준, 장민, 조용중, 윤성철, 1996, '보정신경망을 이용한 냉연 압하력 적중률 향상,' Proceedings of KACC, pp. 1083-1086

정종엽, 임용택, 홍성철, 이주강, 1998, '열연 공정의 선단부 압연하중 설정용 퍼지시스템,' 대한기계학회논문집, 제22권, 제9호, pp. 1625-1638

정종엽, 김수영, 임용택, 1996, '유한요소해석을 이용한 열간압연공정의 장력값 설정,' 제2회 압연심포지움 논문집-압연기술 현재와 미래, pp. 220-238

Kim, S.Y. and Im, Y.T., 1998, 'Three-Dimensional Finite Element Analysis of Non-Isothermal Shape Rolling,' Proc. of the 4th International Conf. on Advances in Materials and Processing Technologies, K.L., Malaysia, pp. 950-957

Kim, S.Y. and Im, Y.T., 'Three-Dimensional Finite Element Simulation of Shape Rolling of Bars,' Int. Journal of Forming Processes, (will be published)

Ginzburg, V.B., 1993, High-Quality Steel Rolling-Theory and Practice, Marcel Dekker, Inc.

Simon, H., 1994, 'Neural Networks - A Comprehensive Foundation,' Macmillan Collage Publishing Company, New York