Due to an increased number of product variants and shorter product life cycles, flexible automation plays a
vital role in the producing industry. In assembly systems, industrial robots are used as highly versatile
handling and joining devices. Simultaneously, the corresponding feeding systems that provide the
workpieces in an orderly fashion for automated assembly can often not meet the required flexibility. In order
to achieve high flexibility and reusability, an aerodynamic feeding system was developed. The feeding
system can flexibly and rapidly adapt itself to new workpieces autonomously, using a genetic algorithm. To
find the optimal parameters for the genetic algorithm, a workpiece specific simulation model of the
aerodynamic orientation process was developed and validated in earlier work. In this work, we extended the
simulation 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 the
genetic algorithm even further by predicting the optimal range of the feeding system’s parameters for any
workpiece using the extended simulation model. To evaluate and validate the simulation model, we carried
out extensive tests with different exemplary workpieces. The results show that the setting time of the
aerodynamic feeding system can be dramatically reduced using the extended simulation model, further
increasing the flexibility and reusability of the system.
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