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State of the Art of Digital Twins in Improving Supply Chain Resilience

Author

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  • Eugenia-Alina Roman

    (Transport Faculty, National University for Science and Technology Politehnica Bucharest, Spl. Independentei, No 313, RO-060042 Bucharest, Romania)

  • Armand-Serban Stere

    (Transport Faculty, National University for Science and Technology Politehnica Bucharest, Spl. Independentei, No 313, RO-060042 Bucharest, Romania)

  • Eugen Roșca

    (Transport Faculty, National University for Science and Technology Politehnica Bucharest, Spl. Independentei, No 313, RO-060042 Bucharest, Romania)

  • Adriana-Valentina Radu

    (Transport Faculty, National University for Science and Technology Politehnica Bucharest, Spl. Independentei, No 313, RO-060042 Bucharest, Romania)

  • Denis Codroiu

    (Transport Faculty, National University for Science and Technology Politehnica Bucharest, Spl. Independentei, No 313, RO-060042 Bucharest, Romania)

  • Ilie Anamaria

    (Transport Faculty, National University for Science and Technology Politehnica Bucharest, Spl. Independentei, No 313, RO-060042 Bucharest, Romania)

Abstract

Background : In today’s complex and rapidly changing global markets, supply chain resilience (SCR) has become critical for businesses aiming to maintain continuity and competitive advantage. Disruptions and challenges in the supply chain will always exist; therefore, preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. Methods : Digital twins (DTs) provide a comprehensive view of product performance, enabling companies to adopt an end-to-end approach to product management. To maximize product and service value, supply chains must also be managed holistically. Results : Therefore, companies will need smarter strategies to balance inventory costs, availability and lead times. The optimal setup of suppliers, manufacturing, logistics and stock locations will ensure high service levels and meet customer expectations. Additionally, supply chains must be resilient, and capable of maintaining performance during disruptions and adapting to demand changes. Conclusions : This paper aims to provide a comprehensive review of the state of the art in digital twin applications within supply chains, focusing on their role in improving visibility, agility and decision-making. This paper explores how digital twins might integrate with emerging technologies such as IoT, AI and blockchain, fostering a more adaptive and robust supply chain ecosystem.

Suggested Citation

  • Eugenia-Alina Roman & Armand-Serban Stere & Eugen Roșca & Adriana-Valentina Radu & Denis Codroiu & Ilie Anamaria, 2025. "State of the Art of Digital Twins in Improving Supply Chain Resilience," Logistics, MDPI, vol. 9(1), pages 1-33, February.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:1:p:22-:d:1585116
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    References listed on IDEAS

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    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    3. Hau L. Lee & Corey Billington, 1993. "Material Management in Decentralized Supply Chains," Operations Research, INFORMS, vol. 41(5), pages 835-847, October.
    4. Yossi Sheffi, 2005. "The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262693496, December.
    5. Dmitry Ivanov & Alexander Tsipoulanidis & Jörn Schönberger, 2021. "Global Supply Chain and Operations Management," Springer Texts in Business and Economics, Springer, edition 3, number 978-3-030-72331-6, December.
    6. Chang, Shuchih Ernest & Chen, Yi-Chian & Lu, Ming-Fang, 2019. "Supply chain re-engineering using blockchain technology: A case of smart contract based tracking process," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 1-11.
    7. Carbonneau, Real & Laframboise, Kevin & Vahidov, Rustam, 2008. "Application of machine learning techniques for supply chain demand forecasting," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1140-1154, February.
    8. Kouhizadeh, Mahtab & Saberi, Sara & Sarkis, Joseph, 2021. "Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers," International Journal of Production Economics, Elsevier, vol. 231(C).
    9. Morris A. Cohen & Hau L. Lee, 1988. "Strategic Analysis of Integrated Production-Distribution Systems: Models and Methods," Operations Research, INFORMS, vol. 36(2), pages 216-228, April.
    10. Gunasekaran, A. & Ngai, E. W. T., 2004. "Information systems in supply chain integration and management," European Journal of Operational Research, Elsevier, vol. 159(2), pages 269-295, December.
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