In view of the influence of the fluctuation of incoming material composition, finishing temperature and coiling temperature on the deformation resistance in the cold rolling process during the hot rolling process, the optimization objective function is established by combining the analytic method and big data regression. Further, the relevant characteristic coefficients are calculated through a large number of on-site actual data, and the deformation resistance model of hot-rolled finished strip and the rolling pressure prediction model of cold rolling process are obtained. Through the field test, the deviation between the predicted rolling force and the actual rolling force is less than 2%, and the accuracy of the model can meet the engineering requirements. More importantly, after using the research results described in this paper, the quality of cold rolled strip shape has been significantly improved, which can greatly improve the economic efficiency and market competitiveness of enterprises.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.