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Shop Floor Digital Twin in Smart Manufacturing: A Systematic Literature Review

Author

Listed:
  • Angelo Corallo

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

  • Vito Del Vecchio

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

  • Marianna Lezzi

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

  • Paola Morciano

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

Abstract

The digital twin is currently recognized as a key technology allowing the digital representation of a real-world system. In smart manufacturing, the digital twin enables the management and analysis of physical and digital processes, products, and people in order to foster the sustainability of their lifecycles. Although past research addressed this topic, fragmented studies, a lack of a holistic view, and a lack of in-depth knowledge about digital twin concepts and structures are still evident in the domain of the shop floor digital twin. Manufacturing companies need an integrated reference framework that fits the main components of both physical and digital space. On the basis of a systematic literature review, this research aims to investigate the characteristics of the digital twin for shop floor purposes in the context of smart manufacturing. The “hexadimensional shop floor digital twin” (HexaSFDT) is proposed as a comprehensive framework that integrates all the main components and describes their relationships. In this way, manufacturing organizations can rely on an inclusive framework for supporting their journey in understanding the shop floor digital twin from a methodological and technological viewpoint. Furthermore, the research strengthens the reference literature by collecting and integrating relevant contributions in a unique framework.

Suggested Citation

  • Angelo Corallo & Vito Del Vecchio & Marianna Lezzi & Paola Morciano, 2021. "Shop Floor Digital Twin in Smart Manufacturing: A Systematic Literature Review," Sustainability, MDPI, vol. 13(23), pages 1-24, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:12987-:d:686420
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    References listed on IDEAS

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    1. Kendrik Yan Hong Lim & Pai Zheng & Chun-Hsien Chen, 2020. "A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1313-1337, August.
    2. Piera Centobelli & Roberto Cerchione & Emilio Esposito, 2017. "Knowledge Management in Startups: Systematic Literature Review and Future Research Agenda," Sustainability, MDPI, vol. 9(3), pages 1-19, March.
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    1. Giulia Pellegrino & Massimiliano Gervasi & Mario Angelelli & Angelo Corallo, 2025. "A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review," Information Systems Frontiers, Springer, vol. 27(1), pages 7-32, February.
    2. Alexandru-Nicolae Rusu & Dorin-Ion Dumitrascu & Adela-Eliza Dumitrascu, 2025. "Shopfloor Visualization-Oriented Digitalization of Heterogeneous Equipment for Sustainable Industrial Performance," Sustainability, MDPI, vol. 17(17), pages 1-17, September.
    3. Weng Siew Lam & Weng Hoe Lam & Pei Fun Lee, 2023. "A Bibliometric Analysis of Digital Twin in the Supply Chain," Mathematics, MDPI, vol. 11(15), pages 1-24, July.
    4. Varun Tripathi & Deepshi Garg & Gianpaolo Di Bona & Alessandro Silvestri, 2025. "Leveraging the Power of Human Resource Management Practices for Workforce Empowerment in SMEs on the Shop Floor: A Study on Exploring and Resolving Issues in Operations Management," Sustainability, MDPI, vol. 17(15), pages 1-35, July.

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