IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v273y2024ics0925527324001154.html
   My bibliography  Save this article

Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks

Author

Listed:
  • Lim, Kendrik Yan Hong
  • Dang, Le Van
  • Chen, Chun-Hsien

Abstract

In today's globalized environment, supply chain (SC) and manufacturing operations are intrinsically linked to satisfy consumer demand. Faced with rising preferences for personalized goods, convenience, and price competitiveness, many companies pivot towards e-commerce strategies and product family approaches to offer wider product varieties and shorten delivery times. This is evident in the fast-moving consumer goods (FMCG) industry, where multi-echelon networks are often utilized to optimize inventory and lower costs. While these methods can fulfill consumer expectations, decreased network resilience is a key obstacle, leaving supply networks vulnerable to supply and demand disruptions. Hence, a holistic approach is required to mitigate disruptions impacts in multi-echelon networks. As a digital enabler, digital twin (DT) technology can manage disruptions in SC networks and manufacturing shop floors. However, these solutions typically operate in silos without context considerations, resulting in illogical solutions. To overcome these challenges, this study proposes a novel supply and production (S&P) DT system to enhance resilience and disruption management in multi-echelon networks. A four-tier technology stack is introduced first, then resilience evaluation, SC replanning, and shop floor rescheduling methods are explored. Based on this, a DT-enabled disruption mitigation mechanism is proposed and featured in an F&B-oriented demand spike disruption case study. Results show the role of the hybrid S&P DT system in improving demand fulfillment rate and reducing production make span to enhance operational continuity.

Suggested Citation

  • Lim, Kendrik Yan Hong & Dang, Le Van & Chen, Chun-Hsien, 2024. "Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks," International Journal of Production Economics, Elsevier, vol. 273(C).
  • Handle: RePEc:eee:proeco:v:273:y:2024:i:c:s0925527324001154
    DOI: 10.1016/j.ijpe.2024.109258
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527324001154
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2024.109258?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    3. Liu, Zhongyi & Li, Mengyu & Zhai, Xin, 2022. "Managing supply chain disruption threat via a strategy combining pricing and self-protection," International Journal of Production Economics, Elsevier, vol. 247(C).
    4. Kyu Tae Park & Yoo Ho Son & Sang Do Noh, 2021. "The architectural framework of a cyber physical logistics system for digital-twin-based supply chain control," International Journal of Production Research, Taylor & Francis Journals, vol. 59(19), pages 5721-5742, October.
    5. Sucky, Eric, 2009. "The bullwhip effect in supply chains--An overestimated problem?," International Journal of Production Economics, Elsevier, vol. 118(1), pages 311-322, March.
    6. 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).
    7. Leung, Eric K.H. & Lee, Carmen Kar Hang & Ouyang, Zhiyuan, 2022. "From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management," International Journal of Production Economics, Elsevier, vol. 244(C).
    8. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2020. "Reconfigurable supply chain: the X-network," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4138-4163, July.
    9. Elisa Negri & Vibhor Pandhare & Laura Cattaneo & Jaskaran Singh & Marco Macchi & Jay Lee, 2021. "Field-synchronized Digital Twin framework for production scheduling with uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1207-1228, April.
    10. Min, Qingfei & Lu, Yangguang & Liu, Zhiyong & Su, Chao & Wang, Bo, 2019. "Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry," International Journal of Information Management, Elsevier, vol. 49(C), pages 502-519.
    11. Beemsterboer, Bart & Land, Martin & Teunter, Ruud & Bokhorst, Jos, 2017. "Integrating make-to-order and make-to-stock in job shop control," International Journal of Production Economics, Elsevier, vol. 185(C), pages 1-10.
    12. Anselm Busse & Benno Gerlach & Joel Cedric Lengeling & Peter Poschmann & Johannes Werner & Simon Zarnitz, 2021. "Towards Digital Twins of Multimodal Supply Chains," Logistics, MDPI, vol. 5(2), pages 1-12, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Saporiti, Nicolò & Cannas, Violetta Giada & Pozzi, Rossella & Rossi, Tommaso, 2023. "Challenges and countermeasures for digital twin implementation in manufacturing plants: A Delphi study," International Journal of Production Economics, Elsevier, vol. 261(C).
    2. Ivanov, Dmitry, 2023. "Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability," International Journal of Production Economics, Elsevier, vol. 263(C).
    3. Barata, João & Kayser, Ina, 2024. "How will the digital twin shape the future of industry 5.0?," Technovation, Elsevier, vol. 134(C).
    4. Emilia Vann Yaroson & Soumyadeb Chowdhury & Sachin Kumar Mangla & Prasanta Kumar Dey, 2024. "Unearthing the interplay between organisational resources, knowledge and industry 4.0 analytical decision support tools to achieve sustainability and supply chain wellbeing," Annals of Operations Research, Springer, vol. 342(2), pages 1321-1368, November.
    5. Tsega Y. Melesse & Chiara Franciosi & Valentina Di Pasquale & Stefano Riemma, 2023. "Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain," Logistics, MDPI, vol. 7(2), pages 1-17, June.
    6. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio, 2019. "An empirical investigation on the antecedents of the bullwhip effect: Evidence from the spare parts industry," International Journal of Production Economics, Elsevier, vol. 209(C), pages 121-133.
    7. Straubert, Christian, 2024. "A continuous approximation location-inventory model with exact inventory costs and nonlinear delivery lead time penalties," International Journal of Production Economics, Elsevier, vol. 268(C).
    8. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    9. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    10. Shraddha Mishra & Surya Prakash Singh, 2022. "Designing dynamic reverse logistics network for post-sale service," Annals of Operations Research, Springer, vol. 310(1), pages 89-118, March.
    11. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    12. Danfeng Zhang & Xin Wang & Liang Zhao & Huaqing Xie & Chen Guo & Feizhou Qian & Hui Dong & Yun Hu, 2023. "Numerical Investigation on Heat Transfer and Flow Resistance Characteristics of Superheater in Hydrocracking Heat Recovery Steam Generator," Energies, MDPI, vol. 16(17), pages 1-15, August.
    13. Chervenkova, Tanya & Ivanov, Dmitry, 2023. "Adaptation strategies for building supply chain viability: A case study analysis of the global automotive industry re-purposing during the COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    14. Mustafa Musa Jaber & Mohammed Hassan Ali & Sura Khalil Abd & Mustafa Mohammed Jassim & Ahmed Alkhayyat & Ezzulddin Hasan Kadhim & Ahmed Rashid Alkhuwaylidee & Shahad Alyousif, 2023. "RETRACTED ARTICLE: AHI: a hybrid machine learning model for complex industrial information systems," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-22, March.
    15. Xi, Mengjie & Liu, Yang & Fang, Wei & Feng, Taiwen, 2024. "Intelligent manufacturing for strengthening operational resilience during the COVID-19 pandemic: A dynamic capability theory perspective," International Journal of Production Economics, Elsevier, vol. 267(C).
    16. Metzker Soares, Paula & Thevenin, Simon & Adulyasak, Yossiri & Dolgui, Alexandre, 2024. "Adaptive robust optimization for lot-sizing under yield uncertainty," European Journal of Operational Research, Elsevier, vol. 313(2), pages 513-526.
    17. Song, Yanwu & Dong, Ying, 2024. "Influence of resource compensation and complete information on green sustainability of semiconductor supply chains," International Journal of Production Economics, Elsevier, vol. 271(C).
    18. Yun, Lifen & Fan, Hongqiang & Li, Xiaopeng, 2019. "Reliable facility location design with round-trip transportation under imperfect information part II: A continuous model," Transportation Research Part B: Methodological, Elsevier, vol. 124(C), pages 44-59.
    19. Alessia Napoleone & Alessandro Bruzzone & Ann-Louise Andersen & Thomas Ditlev Brunoe, 2022. "Fostering the Reuse of Manufacturing Resources for Resilient and Sustainable Supply Chains," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
    20. Weili Yin & Wenxue Ran, 2023. "Explaining Firm Performance During the COVID-19 With fsQCA: The Role of Supply Network Complexity, Inventory Turns, and Geographic Dispersion," SAGE Open, , vol. 13(2), pages 21582440231, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:273:y:2024:i:c:s0925527324001154. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.