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Integrated data-driven and artificial intelligence framework to develop digital twins in distribution system of supply chains: A real industrial case

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  • Ziari, Matineh
  • Taleizadeh, Ata Allah

Abstract

The development of digital twins and the application of industry 4.0, Artificial Intelligence (AI), and recent Machine Learning (ML) approaches have significantly advanced supply chain management and garnered considerable attention. The importance of digital twins in the supply chain became specifically clear following the outbreak of the COVID-19 pandemic, demonstrating substantial benefits in risk and disruption management. We propose an integrated framework for developing digital twins in distribution systems for managing demand risks, and it designs a decision support system for data-driven modeling to respond to two scenarios: (1) proactive design for managing future demand risks and (2) reactive design for managing real-time demand risks. This research aims to provide a more comprehensive study compared to previous investigations by designing this conceptual framework for development of digital twin in distribution systems and creating a support system using technical analysis and demand data via Regression algorithm in machine learning based on a real industrial case problem. The results of the current paper contribute to practical actions and research in demand risk management and the discovery of patterns, trends, and potential changes, enhancing both proactive and reactive decision-making. By integrating the visualization of the distribution system, analyzing historical and online demand data, implementing exogenous variables and connecting it to Enterprise Resource Planning (ERP) systems, this approach ensures the resilience and agility of systems, as well as the continuity of business operations in global companies.

Suggested Citation

  • Ziari, Matineh & Taleizadeh, Ata Allah, 2025. "Integrated data-driven and artificial intelligence framework to develop digital twins in distribution system of supply chains: A real industrial case," International Journal of Production Economics, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:proeco:v:289:y:2025:i:c:s0925527325002282
    DOI: 10.1016/j.ijpe.2025.109743
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    References listed on IDEAS

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    1. Kamble, Sachin S & Gunasekaran, Angappa & Parekh, Harsh & Mani, Venkatesh & Belhadi, Amine & Sharma, Rohit, 2022. "Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    2. Yang, Miying & Fu, Mingtao & Zhang, Zihan, 2021. "The adoption of digital technologies in supply chains: Drivers, process and impact," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Dmitry Ivanov & Alexandre Dolgui & Ajay Das & Boris Sokolov, 2019. "Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility," International Series in Operations Research & Management Science, in: Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov (ed.), Handbook of Ripple Effects in the Supply Chain, pages 309-332, Springer.
    4. Vaibhav Sharma & Rajeev Agrawal & Vijaya Kumar Manupati, 2024. "Blockchain technology as an enabler for digital trust in supply chain: evolution, issues and opportunities," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(9), pages 4183-4209, September.
    5. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    6. Zhang, Linda L. & Jiao, Roger J. & Huang, George & MacCarthy, Bart L., 2025. "Extended guest editorial: Smart product platforming in the industry 4.0 era and beyond," International Journal of Production Economics, Elsevier, vol. 280(C).
    7. Blandine Ageron & Omar Bentahar & Angappa Gunasekaran, 2020. "Digital Supply chain: challenges and future directions," Post-Print hal-03021364, HAL.
    8. Linda Zhang & Roger Jiao & George Huang & Bart Maccarthy, 2025. "Extended guest editorial: Smart product platforming in the industry 4.0 era and beyond," Post-Print hal-05126310, HAL.
    9. Chen, Ziyue & Huang, Lizhen, 2021. "Digital twins for information-sharing in remanufacturing supply chain: A review," Energy, Elsevier, vol. 220(C).
    10. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    11. Dmitry Ivanov, 2025. "No risk, no fun? A bioinspired adaptation-based framework for supply chain resilience in Industry 5.0," International Journal of Production Research, Taylor & Francis Journals, vol. 63(19), pages 7153-7173, October.
    12. Matt Bassett & Leslie Gardner, 2013. "Designing optimal global supply chains at Dow AgroSciences," Annals of Operations Research, Springer, vol. 203(1), pages 187-216, March.
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    1. Du, Weijian & Cheng, Cheng & Li, Mengjie, 2025. "Can listed company digitization reduce the risk of export failure? Evidence from multisource heterogeneous data in China," International Review of Economics & Finance, Elsevier, vol. 103(C).

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