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Optimization of Hub-Based Milkrun Supply

Author

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  • Tamás Bányai

    (Institute of Logistics, University of Miskolc, 3515 Miskolc, Hungary)

Abstract

Background: Milkrun-based material supply plays an important role in the automotive industry, as it is a material supply concept where high efficiency can be achieved. When implementing milkrun-based material supply, the milkrun supply of the production plant often has to be integrated with an existing warehouse material handling system, which frequently leads to a less efficient solution. Methods: In this paper, the author investigates the impact of a hub-based milkrun supply, where the collection processes in the component’s warehouse and the distribution processes in the assembly plant are connected to a hub, which is responsible for the sequencing of component demands. After a systematic literature review, the paper introduces a novel mathematical model, which makes it possible to describe the conventional milkrun-based solutions, the hub-based milkrun solutions, and to compare them in terms of the length of transportation routes, transportation time, total service time, and virtual emission points of view. Results: The scenario analysis demonstrates that the hub-based solution can lead to an efficiency improvement of about 13% in total service time, 23% savings in transportation time, and 45% savings in transportation time in the component’s warehouse. Conclusions: The article’s findings suggest that implementing a hub-based milkrun system in automotive material supply can significantly enhance efficiency. The described approach could lead to more streamlined operations in production plants by optimizing the integration of milkrun systems.

Suggested Citation

  • Tamás Bányai, 2024. "Optimization of Hub-Based Milkrun Supply," Logistics, MDPI, vol. 8(3), pages 1-21, September.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:3:p:86-:d:1470421
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    References listed on IDEAS

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    1. Simon Emde & Shohre Zehtabian & Yann Disser, 2023. "Point-to-point and milk run delivery scheduling: models, complexity results, and algorithms based on Benders decomposition," Annals of Operations Research, Springer, vol. 322(1), pages 467-496, March.
    2. Julian Baals, 2024. "Environmental aspects in supplier networks-a bi-objective just-in-time truck routing problem," International Journal of Production Research, Taylor & Francis Journals, vol. 62(12), pages 4290-4313, June.
    3. Meyer, Anne & Amberg, Boris, 2018. "Transport concept selection considering supplier milk runs – An integrated model and a case study from the automotive industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 147-169.
    4. Yasemin Kocaoglu & Emre Cakmak & Batuhan Kocaoglu & Alev Taskin Gumus, 2020. "A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-24, February.
    5. Du, Timon & Wang, F.K. & Lu, Pu-Yun, 2007. "A real-time vehicle-dispatching system for consolidating milk runs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 565-577, September.
    6. Francesco Facchini & Giorgio Mossa & Claudio Sassanelli & Salvatore Digiesi, 2024. "IoT-based milk-run routing for manufacturing system: an application case in an automotive company," International Journal of Production Research, Taylor & Francis Journals, vol. 62(1-2), pages 536-555, January.
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