IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v35y2024i8d10.1007_s10845-023-02262-6.html
   My bibliography  Save this article

Cloud material handling systems: a cyber-physical system to enable dynamic resource allocation and digital interoperability

Author

Listed:
  • Cosmin Aron

    (Norwegian University of Science and Technology)

  • Fabio Sgarbossa

    (Norwegian University of Science and Technology)

  • Eric Ballot

    (Mines Paris - PSL)

  • Dmitry Ivanov

    (Berlin School of Economics and Law (HWR Berlin))

Abstract

The existing logistics practices frequently lack the ability to effectively handle disruptions. Recent research called for dynamic, digital-driven approaches that can help prioritise allocation of logistics resources to design more adaptive and sustainable logistics networks. The purpose of this study is to explore inter-dependencies between physical and digital assets to examine how cyber-physical systems could enable interoperability in logistics networks. The paper provides an overview of the existing literature on cyber-physical applications in logistics and proposes a conceptual model of a Cloud Material Handling System. The model allows leveraging the use of digital technologies to capture and process real-time information about a logistics network with the aim to dynamically allocate material handling resources and promote asset and infrastructure sharing. The model describes how cloud computing, machine learning and real-time information can be utilised to dynamically allocate material handling resources to product flows. The adoption of the proposed model can increase efficiency, resilience and sustainability of logistics practices. Finally, the paper offers several promising research avenues for extending this work.

Suggested Citation

  • Cosmin Aron & Fabio Sgarbossa & Eric Ballot & Dmitry Ivanov, 2024. "Cloud material handling systems: a cyber-physical system to enable dynamic resource allocation and digital interoperability," Journal of Intelligent Manufacturing, Springer, vol. 35(8), pages 3815-3836, December.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:8:d:10.1007_s10845-023-02262-6
    DOI: 10.1007/s10845-023-02262-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-023-02262-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-023-02262-6?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. Kai Zhang & Ting Qu & Yongheng Zhang & Ray Y. Zhong & George Huang, 2022. "Big data-enabled intelligent synchronisation for the complex production logistics system under the opti-state control strategy," International Journal of Production Research, Taylor & Francis Journals, vol. 60(13), pages 4159-4175, July.
    2. Li, Mingxing & Huang, George Q., 2021. "Production-intralogistics synchronization of industry 4.0 flexible assembly lines under graduation intelligent manufacturing system," International Journal of Production Economics, Elsevier, vol. 241(C).
    3. Dan Luo & Zailin Guan & Cong He & Yeming Gong & Lei Yue, 2022. "Data-driven cloud simulation architecture for automated flexible production lines: application in real smart factories," International Journal of Production Research, Taylor & Francis Journals, vol. 60(12), pages 3751-3773, June.
    4. Mehran Fazili & Uday Venkatadri & Pemberton Cyrus & Mahdi Tajbakhsh, 2017. "Physical Internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2703-2730, May.
    5. Zhang, Yingfeng & Zhang, Geng & Du, Wei & Wang, Junqiang & Ali, Ebad & Sun, Shudong, 2015. "An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 282-292.
    6. Xifan Yao & Jiajun Zhou & Yingzi Lin & Yun Li & Hongnian Yu & Ying Liu, 2019. "Smart manufacturing based on cyber-physical systems and beyond," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2805-2817, December.
    7. Tarik Chargui & Abdelghani Bekrar & Mohamed Reghioui & Damien Trentesaux, 2020. "Proposal of a multi-agent model for the sustainable truck scheduling and containers grouping problem in a Road-Rail physical internet hub," International Journal of Production Research, Taylor & Francis Journals, vol. 58(18), pages 5477-5501, September.
    8. Yeming Gong & René de Koster, 2011. "A review on stochastic models and analysis of warehouse operations," Post-Print hal-02312651, HAL.
    9. 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.
    10. René de Koster & Yeming Gong, 2008. "A polling-based dynamic order picking system for online retailers," Post-Print hal-02312476, HAL.
    11. Dan Luo & Zailin Guan & Cong He & Yeming Gong & Lei Yue, 2022. "Data-driven cloud simulation architecture for automated flexible production lines : application in real smart factories," Post-Print hal-04325622, HAL.
    12. C.K.M. Lee & Yaqiong Lv & K.K.H. Ng & William Ho & K.L. Choy, 2018. "Design and application of Internet of things-based warehouse management system for smart logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2753-2768, April.
    13. Rochdi Sarraj & Eric Ballot & Shenle Pan & Driss Hakimi & Benoit Montreuil, 2014. "Interconnected logistic networks and protocols: simulation-based efficiency assessment," Post-Print hal-01112138, HAL.
    14. Shenle Pan & Damien Trentesaux & Duncan Mcfarlane & Benoit Montreuil & Eric Ballot & George Huang, 2021. "Digital interoperability in logistics and supply chain management: state-of-the-art and research avenues towards Physical Internet," Post-Print hal-03161524, HAL.
    15. Eric Ballot & Benoit Montreuil & Zach Zacharia, 2021. "Physical Internet: First results and next challenges," Post-Print hal-03524475, HAL.
    16. Wenzhu Liao & Tong Wang, 2019. "A Novel Collaborative Optimization Model for Job Shop Production–Delivery Considering Time Window and Carbon Emission," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    17. A. J. H. Redelinghuys & A. H. Basson & K. Kruger, 2020. "A six-layer architecture for the digital twin: a manufacturing case study implementation," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1383-1402, August.
    18. Horst Treiblmaier, 2019. "Combining Blockchain Technology and the Physical Internet to Achieve Triple Bottom Line Sustainability: A Comprehensive Research Agenda for Modern Logistics and Supply Chain Management," Logistics, MDPI, vol. 3(1), pages 1-13, February.
    19. Ray Y. Zhong & Chen Xu & Chao Chen & George Q. Huang, 2017. "Big Data Analytics for Physical Internet-based intelligent manufacturing shop floors," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2610-2621, May.
    20. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
    21. Yanyan Yang & Shenle Pan & Eric Ballot, 2017. "Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet," International Journal of Production Research, Taylor & Francis Journals, vol. 55(14), pages 3970-3983, July.
    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. 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).
    2. Shoufeng Ji & Pengyun Zhao & Tingting Ji, 2023. "A Hybrid Optimization Method for Sustainable and Flexible Design of Supply–Production–Distribution Network in the Physical Internet," Sustainability, MDPI, vol. 15(7), pages 1-34, April.
    3. 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.
    4. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    5. 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).
    6. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Zied Babai, M., 2023. "Network inventory deployment for responsive fulfillment," International Journal of Production Economics, Elsevier, vol. 255(C).
    7. 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).
    8. 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.
    9. 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).
    10. 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).
    11. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    12. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
    13. Hisatoshi Naganawa & Enna Hirata & Nailah Firdausiyah & Russell G. Thompson, 2024. "Logistics Hub and Route Optimization in the Physical Internet Paradigm," Logistics, MDPI, vol. 8(2), pages 1-18, April.
    14. Shenle Pan, 2019. "Opportunities of Product-Service System in Physical Internet," Post-Print hal-02155622, HAL.
    15. Claeys, Dieter & Adan, Ivo & Boxma, Onno, 2016. "Stochastic bounds for order flow times in parts-to-picker warehouses with remotely located order-picking workstations," European Journal of Operational Research, Elsevier, vol. 254(3), pages 895-906.
    16. Tarik Chargui & Anne-Laure Ladier & Abdelghani Bekrar & Shenle Pan & Damien Trentesaux, 2022. "Towards designing and operating Physical Internet cross-docks: problem specifications and research perspectives," Post-Print hal-03624314, HAL.
    17. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    18. Tan, Bing Qing & Xu, Su Xiu & Kang, Kai & Xu, Gangyan & Qin, Wei, 2021. "A reverse Vickrey auction for physical internet (PI) enabled parking management systems," International Journal of Production Economics, Elsevier, vol. 235(C).
    19. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    20. Mohammadi, Mehrdad & Dehghan, Milad & Pirayesh, Amir & Dolgui, Alexandre, 2022. "Bi‐objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID‐19 pandemic," Omega, Elsevier, vol. 113(C).

    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:spr:joinma:v:35:y:2024:i:8:d:10.1007_s10845-023-02262-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.