Sheet metal blanking is a manufacturing process widely used in many industries. It consists in shearing thin sheets metal using two sharp tools called punch and die. During a blanking operation, these cutting tools are subjected to extreme stress, which leads to their progressive wear. Wear of blanking tools is an inevitable phenomenon during the blanking process. It leads to significant press shutdowns and can have a significant impact on the quality of the blanked parts, particularly the quality of the cut edge. Additionally, punch wear noticeably affects punch force, making the punch force/penetration curve a good wear indicator that can be combined with cut edge quality to quantify wear. In this context, this work focuses on the study of the effect of punch wear on the cutting force curve and on the quality of the cut edge with the aim of establishing a correlation between these two indicators and the degree of punch wear. To achieve that, realistic wear profiles of the punch based on wear profile measurements were implemented in a finite element model to predict the force on the punch during the entire punching process (i.e. cutting phase, phase of punch penetration into the die and stripping phase). As high-fidelity predictions are required, particular attention is paid to the sheet metal constitutive model. In this work the sheet metal behavior is described using a J2 plasticity model combined with Modified Mohr-Coulomb (MMC) fracture criterion. The procedure thus developed was used to link the state of the punch wear to the cutting force curve and the shape of the cut edge. These results are intended to enrich a database of physical test measurements for machine learning training purposes.