Due to an increased number of product variants and shorter product life cycles, flexible automation plays avital role in the producing industry. In assembly systems, industrial robots are used as highly versatilehandling and joining devices. Simultaneously, the corresponding feeding systems that provide theworkpieces in an orderly fashion for automated assembly can often not meet the required flexibility. In orderto achieve high flexibility and reusability, an aerodynamic feeding system was developed. The feedingsystem can flexibly and rapidly adapt itself to new workpieces autonomously, using a genetic algorithm. Tofind the optimal parameters for the genetic algorithm, a workpiece specific simulation model of theaerodynamic orientation process was developed and validated in earlier work. In this work, we extended thesimulation model with regard to the spectrum of workpieces that can be simulated and developed a userfriendly framework to simplify the application of the model. Our goal is to reduce the setting time of thegenetic algorithm even further by predicting the optimal range of the feeding system’s parameters for anyworkpiece using the extended simulation model. To evaluate and validate the simulation model, we carriedout extensive tests with different exemplary workpieces. The results show that the setting time of theaerodynamic feeding system can be dramatically reduced using the extended simulation model, furtherincreasing the flexibility and reusability of the system.