Details
Originalsprache | Englisch |
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Titel des Sammelwerks | Proceedings of the Conference on Production Systems and Logistics |
Untertitel | CPSL 2021 |
Seiten | 244-253 |
Seitenumfang | 10 |
Publikationsstatus | Veröffentlicht - 2021 |
Veranstaltung | Conference on Production Systems and Logistics - Online Dauer: 10 Aug. 2021 → 11 Aug. 2021 https://cpsl-conference.com/ |
Publikationsreihe
Name | Proceedings of the Conference on Production Systems and Logistics |
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Abstract
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Maschinenbau
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Technologie- und Innovationsmanagement
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Strategie und Management
Ziele für nachhaltige Entwicklung
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- BibTex
- RIS
Proceedings of the Conference on Production Systems and Logistics: CPSL 2021. 2021. S. 244-253 (Proceedings of the Conference on Production Systems and Logistics).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Extended Simulation Model For An Aerodynamic Feeding System
AU - Kolditz, Torge Mattis
AU - Hentschel, Jakob
AU - Katz, Fabian
AU - Raatz, Annika
N1 - Funding Information: Funded by the Deutsche Forschungsgemeinschaft (DFG - German Research Foundation) within the project “Model-based increase of the flexibility and robustness of an aerodynamic feeding system for high-performance assembly” (project number: 243351293).
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Aerodynamic Feeding
KW - Flexible Feeding Systems
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=85127489306&partnerID=8YFLogxK
U2 - 10.15488/11252
DO - 10.15488/11252
M3 - Conference contribution
T3 - Proceedings of the Conference on Production Systems and Logistics
SP - 244
EP - 253
BT - Proceedings of the Conference on Production Systems and Logistics
T2 - Conference on Production Systems and Logistics
Y2 - 10 August 2021 through 11 August 2021
ER -