A novel model-based approach for the prediction of wear in cold rolling

Abstract

The tribological interface between work roll and strip significantly influences the process parameters and mill performance in cold rolling as well as the final quality of flat products. Due to the severe contact conditions associated with the underlying plastic deformation of the strip and the elastic deformation of the work roll, the tribological mechanisms occurring at that interface are difficult to investigate by experimental methods or conventional cold rolling theories.The model-based approach presented in this work utilizes a modular tribological cold rolling model to predict the local mixed lubrication interface conditions based on rolling mill, pass and lubricant parameters. The calculated values for pressure, temperature, etc. are used to estimate the wear extracted from the strip surface by utilizing a locally distributed implementation of Archard's equation.The new model was validated against results obtained from a pilot reversing mill including the accumulated wear volume generated during rolling of various steel grades using different emulsions. The proposed modelling approach contributes to a better understanding of tribology and wear in cold rolling processes of flat products. In particular, the influence of significant rolling as well as lubrication parameters on rolling performance and wear generation can be estimated.