COMPARISON BETWEEN MODELS FOR CALCULATION OF INDUSTRIAL HOT ROLLING LOADS

• Published in: Tecnologia em metalurgia, materiais e mineração Vol. 9; no. 3; pp. 197 - 203
• Main Authors: Antonio Augusto Gorni, Marcos Roberto Soares da Silva
• Format: Journal Article
• Language: English
• Published: Associação Brasileira de Metalurgia, Materiais e Mineração 01-09-2012
• Subjects: Hot strip mill; Loads; Neural network
• ISSN: 2176-1515; 2176-1523
• DOI: 10.4322/tmm.2012.028

An evaluation is made about the precision of hot strip rolling mill loads at the F1 stand calculated according to the theoretical models of Orowan, Sims, Alexander-Ford, Orowan-Pascoe, Ekelund and Tselikov in comparison to real values got for carbon-manganese steels. In the deterministic approach, without any fit of the calculated values to real data, Orowan, Sims and Alexander-Models show best levels of precision, as expected from the information got in the literature. However, in the semi-empirical approach, after a linear fit between calculated values and real data, Tselikov and Ekelund models show better adequacy to the industrial data, a fact that can be attributed to more significant errors occurring in the sub-models of temperature, tribology and hot strength than in the rolling load models. For its turn, neural network models show the best levels of precision which make very attractive the adoption of this approach.