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  4. Vol 6, Issue 7, 2022

Digital Twin Based Flexible Manufacturing System Modelling with Fuzzy Approach

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DOI: 10.23977/acss.2022.060702 | Downloads: 27 | Views: 675

Author(s)

Safiye Turgay 1, Ömer Bilgin 2, Necip Akar 1

Affiliation(s)

1 Sakarya University, Dept. of Ind.Eng, Sakarya, Turkey
2 Datacore Bilgi Sistemleri, Esentepe Mah. Milangaz Cad. No:75 Monument, D: Kat 6, Kartal, İstanbul, 34870, Turkey

Corresponding Author

Safiye Turgay

ABSTRACT

The digital twin-based fuzzy decision mechanism provides great opportunities for the realization of the optimization process, especially in the flexible production environment, with big data and new business modes beyond expectations. Developing technology has brought with it the increasing amount of data and the development of big data analysis techniques. We can give Internet of Things (IoT), 5G, digital twin and cloud computing technologies as examples. Digital twin covers the process of monitoring and directing the production processes in the virtual environment in line with the increasing amount of data and the ability to respond quickly and accurately to customer services. The digital twin provides the internal and external changes in the production environment allow instant analysis of data. In this approach, it is aimed to optimize the production process, reduce costs and increase operational efficiency. It provides continuous learning in the production system environment and self-optimization of the system. It includes a digital twin-based integrated smart production model and the evaluation of the fuzzy approach in decision-making in a flexible production environment.

KEYWORDS

Big data analytics (BDA), Intelligent production, Digital twin, Fuzzy decision making, Flexible production environment, IoT system

CITE THIS PAPER

Safiye Turgay, Ömer Bilgin, Necip Akar, Digital Twin Based Flexible Manufacturing System Modelling with Fuzzy Approach. Advances in Computer, Signals and Systems (2022) Vol. 6: 10-17. DOI: http://dx.doi.org/10.23977/acss.2022.060702.

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