Steel has wide range of applications in sheet form which is produced in a chain of processes where two steps have a huge influence on the usability of the product, annealing and temper rolling.

In annealing the material microstructure is reset where the undesired effects of cold-rolling are removed and a fine grained, strong and formable sheet is produced. If the roll force during this step is not tuned properly the final properties of the sheet might be affected adversely and the fine-tuning work for optimizing the microstructure in earlier steps might lose effectiveness. The amount of reduction in sheet thickness has a direct relation with the roll force which is currently the control parameter that also determines the stability of the process among other factors such as roughness transfer from the rolls to the surface of the sheet. A good initial estimation for the roll force reduces the need for control adjustments later in the process and therefore reduces the scrap rate.

Due to a lack of understanding of the yield point phenomenon and the associated yield point elongation, the prediction of roll force for temper rolling is not as accurate as it can be. In this project a new material model will be developed based on an improved understanding of the phenomenon through novel test setups for direct observation both in macroscale as well as in microscopic scale.

Building the model on the mobility and density of dislocations that contribute to plastic deformation, this physics based approach will have high predictive capability and therefore will be a good candidate to be used in temper rolling simulations where in addition to the roll force, the surface and microstructural properties are to be obtained. Furthermore, it will be used in the semi-analytical, fast, online prediction of roll force which will have a direct effect on the reduction of scrap.