The curing reaction, which settles the shape and final properties of the rubber, makes rubber injection molding a very time-consuming process. In this work, the process set-up of rubber injection molding was shifted from the practical to the virtual level in systematically applying DoE plans in injection molding simulation to develop and demonstrate a resource-effective method finding a suitable processing point. First, material characterization methods were refined to reliably measure the behavior of rubber compounds as basis of injection molding simulation, including the development of a rheometric mold which allowed the shear viscosity measurement including the effects of the real processing prehistory of injection molding. To evaluate the simulation, various characterization methods to establish curing degree-property master curves were tested, where compression set was found to the most suitable method. In addition, storage-induced changes of material properties could successfully be evaluated. These data were then used in systematic simulations, where models describing the target parameters (1) local degree of cure, representing the performance properties, (2) scorch at the end of filling, indicating the processing stability and (3) cycle time as measure for productivity could be deduced of central composite experimental designs. Both second order polynomial models and enhanced models containing a logistic growth term to meet the physical nature of the curing reaction were implemented. The practical verification experiments demonstrated the accuracy of these models. They showed that the approach is applicable (1) to find suitable process settings with minimized need for real experiments and (2) to solve the target conflict of the request for locally homogenous part quality and the demand for a maximum productivity while maintaining a stable process. Compared to a conventionally established process setting, an increase in productivity of almost 30 % could be achieved. Finally, relations of transient process data and quality parameters could be established. This allowed the automatic detection of changes in the behavior of the raw rubber compound with machine signals and the prediction of part dimensions as function of cavity pressure as well as the local state of cure, depending on the transiently measured cavity temperature.