Extended Simulation Model For An Aerodynamic Feeding System

authored by: Torge Mattis Kolditz, Jakob Hentschel, Fabian Katz, Annika Raatz
Abstract: 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.
Organisation(s): Institute for Assembly Technology and Robotics
Type: Conference contribution
Pages: 244-253
No. of pages: 10
Publication date: 2021
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Mechanical Engineering, Management of Technology and Innovation, Industrial and Manufacturing Engineering, Strategy and Management
Sustainable Development Goals: SDG 9 - Industry, Innovation, and Infrastructure
Electronic version(s): https://doi.org/10.15488/11252 (Access: Open)