Reduced Three-Dimensional Model for Cold Rolling Simulation of Aluminium Alloys

Abstract

Mathematical modelling and computational analyses allow to deepen the understanding of manufacturing processes, to ensure high product quality and to reduce experimental efforts for the optimization of product properties and production processes. In order to predict the evolution of flat rolled aluminium product properties and their interdependence with process parameters, virtual representations of the entire process chain including process models of hot rolling, coiling, and cold rolling operations are highly beneficial. Starting from the solid foundation of a comprehensively validated 3D model of the hot rolling process of various aluminium alloys, the present work presents a 3D thermo-mechanical cold rolling simulation model using the commercial finite element code LS-DYNA. The material behaviour is considered by means of a user defined material model according to a modified dislocation density based flow model. The calculated microstructural and deformation history of the hot rolled strip is considered as input for the developed cold rolling model allowing for seamless prediction of product properties. For numerical studies, a modular modelling approach is pursued, comprising tailor-made simplifications depending on actual applications and research problems. For time efficient multi-pass simulations in an industrial environment, a reduced model with plane strain conditions is derived that extends the predictability of product properties and process parameters from hot rolling over coiling to cold rolling. Simulation results and computational costs are compared with detailed 3D models. Strip tensions can be adjusted showing the expected effects on roll separating forces and minimum rolled thickness. To ensure the desired strip tensions in the numerical model, a sensor-based control of strip tensions is implemented. For validation purposes, measured rolling forces from industrial pass schedules for 6xxx series alloys are compared against simulation results.