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Designing a changeable multi-level supply chain network with additive manufacturing capability and costs uncertainty: a Monte Carlo approach

Author

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  • Pardis Roozkhosh

    (Ferdowsi University of Mashhad)

  • Alireza Pooya

    (Ferdowsi University of Mashhad)

  • Omid Soleimani Fard

    (Ferdowsi University of Mashhad)

  • Rouhollah Bagheri

    (Ferdowsi University of Mashhad)

Abstract

Production technology known as additive manufacturing completely deviates from the conventional subtractive method. Due to its unique nature, its application could result in significant Supply Chain (SC) changes and impact the interactions between supply chain participants. This study shows the additive manufacturing applicable in an SC, considers the combination of traditional and additive manufacturing, and redesigns the SC structure. Also, this study aims to reduce operational and traditional costs and provides a new optimization model for changeable multi-level SC. Additive manufacturing is considered both a centralized and decentralized state. Additionally, this paper proposes a new Monte Carlo (MC) method combined with a Machine Learning (MCML) approach to improve the cost uncertainty accuracy compared with simple MC. For validation, the model is tested in a real case and sensitively analyzed regarding changes in the uncertainty and type of manufacturers. The results show that this hybrid model can reduce costs, MCML-based-MPL can increase the uncertainty accuracy in MC, and this model performs considerably better than only one type of traditional or additive manufacturing in SC.

Suggested Citation

  • Pardis Roozkhosh & Alireza Pooya & Omid Soleimani Fard & Rouhollah Bagheri, 2024. "Designing a changeable multi-level supply chain network with additive manufacturing capability and costs uncertainty: a Monte Carlo approach," Operational Research, Springer, vol. 24(1), pages 1-37, March.
    • Handle: RePEc:spr:operea:v:24:y:2024:i:1:d:10.1007_s12351-023-00812-7
    DOI: 10.1007/s12351-023-00812-7
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    References listed on IDEAS

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    1. Sajjad Rahmanzadeh & Mir Saman Pishvaee & Mohammad Reza Rasouli, 2020. "Integrated innovative product design and supply chain tactical planning within a blockchain platform," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2242-2262, April.
    2. Saeedeh Bazari & Alireza Pooya & Omid Soleimani Fard & Pardis Roozkhosh, 2023. "Modeling and solving the problem of scheduling university exams in terms of new constraints on the conflicts of professors' exams and the concurrence of exams with common questions," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 877-915, June.
    3. Muhammad Imran & Muhammad Salman Habib & Amjad Hussain & Naveed Ahmed & Abdulrahman M. Al-Ahmari, 2020. "Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty," Mathematics, MDPI, vol. 8(3), pages 1-29, March.
    4. Altekin, F. Tevhide & Bukchin, Yossi, 2022. "A multi-objective optimization approach for exploring the cost and makespan trade-off in additive manufacturing," European Journal of Operational Research, Elsevier, vol. 301(1), pages 235-253.
    5. Suryawanshi, Pravin & Dutta, Pankaj, 2022. "Optimization models for supply chains under risk, uncertainty, and resilience: A state-of-the-art review and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    6. Jose M. Framinan & Paz Perez-Gonzalez & Victor Fernandez-Viagas, 2023. "An overview on the use of operations research in additive manufacturing," Annals of Operations Research, Springer, vol. 322(1), pages 5-40, March.
    7. Beltagui, Ahmad & Gold, Stefan & Kunz, Nathan & Reiner, Gerald, 2023. "Special Issue: Rethinking operations and supply chain management in light of the 3D printing revolution," International Journal of Production Economics, Elsevier, vol. 255(C).
    8. Nuwan Munasinghe & Thomas Romeijn & Gavin Paul, 2023. "Voxel-based sensor placement for additive manufacturing applications," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 739-751, February.
    9. Arbabian, Mohammad E., 2022. "Supply Chain Coordination via Additive Manufacturing," International Journal of Production Economics, Elsevier, vol. 243(C).
    10. Ghanei, Shima & Contreras, Ivan & Cordeau, Jean-François, 2023. "A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
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