A methodology for simulation production systems considering the degree of autonomy

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Voit, Patrick; Beller, Marie; Reinhart, Gunther: A methodology for simulation production systems considering the degree of autonomy. In: Nyhuis, P.; Herberger, D.; Hübner, M. (Eds.): Proceedings of the 1st Conference on Production Systems and Logistics (CPSL 2020), 2020, S. 332-341. DOI: https://doi.org/10.15488/9675

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Sum total of downloads: 180




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Abstract: 
The increasing number of product varieties and declining product life cycles combined with individualised customer behaviour demand flexible and efficient production systems. A proper solution approach can be the use of intelligent technologies, capable of autonomous processing in order to react rapidly to changing requirements. However, production planners need a profound planning approach for the implementation of such technologies in production systems due to their cost intense investments. Therefore, simulation studies are suitable means for the analysis of a proper degree of autonomy in production systems. An appropriate methodology for the simulation of such systems is presented in this paper. The methodology is aligned with common guidelines on simulation studies and focuses on system analysis, formalisation and simulation. It is based on consistent methods – fact sheets and Value Stream Design for system analysis, Unified Modelling Language (UML) diagrams for formalisation and agent-based simulation. A central contribution to current research is the modular modelling of intelligence skills in production resources and parts in a simulation environment. Consequently, the developed methodology provides a basis for the implementation of simulation experiments in order to facilitate the evaluation of the economically efficient use of intelligent objects in production systems.
License of this version: CC BY 3.0 DE
Document Type: bookPart
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Proceedings CPSL 2020
Proceedings CPSL 2020

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pos. country downloads
total perc.
1 image of flag of Germany Germany 105 58.33%
2 image of flag of Poland Poland 10 5.56%
3 image of flag of Czech Republic Czech Republic 7 3.89%
4 image of flag of United States United States 6 3.33%
5 image of flag of China China 6 3.33%
6 image of flag of France France 5 2.78%
7 image of flag of Sweden Sweden 4 2.22%
8 image of flag of Austria Austria 4 2.22%
9 image of flag of Serbia Serbia 3 1.67%
10 image of flag of Portugal Portugal 3 1.67%
    other countries 27 15.00%

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