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Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept

Author

Listed:
  • Kamil Židek

    (Department of Industrial Engineering and Informatics, Faculty of Manufacturing Technologies with a Seat in Presov, Technical University of Kosice, Bayerova 1, 08001 Prešov, Slovakia)

  • Ján Piteľ

    (Department of Industrial Engineering and Informatics, Faculty of Manufacturing Technologies with a Seat in Presov, Technical University of Kosice, Bayerova 1, 08001 Prešov, Slovakia)

  • Milan Adámek

    (Department of Security Engineering, Faculty of Applied Informatics, Tomas Bata University in Zlín, Nad Stráněmi 4511, 76005 Zlín, Czech Republic)

  • Peter Lazorík

    (Department of Industrial Engineering and Informatics, Faculty of Manufacturing Technologies with a Seat in Presov, Technical University of Kosice, Bayerova 1, 08001 Prešov, Slovakia)

  • Alexander Hošovský

    (Department of Industrial Engineering and Informatics, Faculty of Manufacturing Technologies with a Seat in Presov, Technical University of Kosice, Bayerova 1, 08001 Prešov, Slovakia)

Abstract

This article deals with the creation of a digital twin for an experimental assembly system based on a belt conveyor system and an automatized line for quality production check. The point of interest is a Bowden holder assembly from a 3D printer, which consists of a stepper motor, plastic components, and some fastener parts. The assembly was positioned in a fixture with ultra high frequency (UHF) tags and internet of things (IoT) devices for identification of status and position. The main task was parts identification and inspection, with the synchronization of all data to a digital twin model. The inspection system consisted of an industrial vision system for dimension, part presence, and errors check before and after assembly operation. A digital twin is realized as a 3D model, created in CAD design software (CDS) and imported to a Tecnomatix platform to simulate all processes. Data from the assembly system were collected by a programmable logic controller (PLC) system and were synchronized by an open platform communications (OPC) server to a digital twin model and a cloud platform (CP). Digital twins can visualize the real status of a manufacturing system as 3D simulation with real time actualization. Cloud platforms are used for data mining and knowledge representation in timeline graphs, with some alarms and automatized protocol generation. Virtual digital twins can be used for online optimization of an assembly process without the necessity to stop that is involved in a production line.

Suggested Citation

  • Kamil Židek & Ján Piteľ & Milan Adámek & Peter Lazorík & Alexander Hošovský, 2020. "Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:9:p:3658-:d:353137
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    Citations

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    Cited by:

    1. Nabil El Bazi & Mustapha Mabrouki & Oussama Laayati & Nada Ouhabi & Hicham El Hadraoui & Fatima-Ezzahra Hammouch & Ahmed Chebak, 2023. "Generic Multi-Layered Digital-Twin-Framework-Enabled Asset Lifecycle Management for the Sustainable Mining Industry," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    2. Özden Tozanlı & Elif Kongar & Surendra M. Gupta, 2020. "Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain," Sustainability, MDPI, vol. 12(13), pages 1-33, July.
    3. Rong Xie & Muyan Chen & Weihuang Liu & Hongfei Jian & Yanjun Shi, 2021. "Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review," Sustainability, MDPI, vol. 13(5), pages 1-22, February.
    4. Issam A. R. Moghrabi & Sameer Ahmad Bhat & Piotr Szczuko & Rawan A. AlKhaled & Muneer Ahmad Dar, 2023. "Digital Transformation and Its Influence on Sustainable Manufacturing and Business Practices," Sustainability, MDPI, vol. 15(4), pages 1-35, February.
    5. Yen Sheng Tsai & Wei-Hsi Hung, 2023. "A low-cost intelligent tracking system for clothing manufacturers," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 473-491, February.
    6. Cheng Qian & Xing Liu & Colin Ripley & Mian Qian & Fan Liang & Wei Yu, 2022. "Digital Twin—Cyber Replica of Physical Things: Architecture, Applications and Future Research Directions," Future Internet, MDPI, vol. 14(2), pages 1-25, February.
    7. Adriana Grenčíková & Marcel Kordoš & Jozef Bartek & Vladislav Berkovič, 2021. "The Impact of the Industry 4.0 Concept on Slovak Business Sustainability within the Issue of the Pandemic Outbreak," Sustainability, MDPI, vol. 13(9), pages 1-14, April.

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