IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3283-d1064768.html
   My bibliography  Save this article

Leveraging Blockchain to Support Collaborative Distributed Manufacturing Scheduling

Author

Listed:
  • Veera Babu Ramakurthi

    (Department of Mechanical Engineering, National Institute of Technology, Warangal 506004, India)

  • Vijaya Kumar Manupati

    (Operations and Supply Chain Division, NITIE, Mumbai 400087, India)

  • Leonilde Varela

    (ALGORITMI Research Centre/LASI, Department of Production and Systems, School of Engineering, University of Minho, 4804-533 Guimarães, Portugal)

  • Goran Putnik

    (ALGORITMI Research Centre/LASI, Department of Production and Systems, School of Engineering, University of Minho, 4804-533 Guimarães, Portugal)

Abstract

The recent trend in collaborative distributed manufacturing scheduling (CDMS) has gained significant importance in extended, networked, and virtual manufacturing environments due to its adaptability and integration potential. In a distributed manufacturing environment, CDMS can occur within a single factory or across multiple companies in a dynamic and variable extended or virtual organization. For effective collaboration, the CDMS system must be secure, transparent, and trustworthy. This paper proposes a blockchain-based model for CDMS and discusses its implementation in the processing of manufacturing functions, specifically joint process planning and scheduling. An illustrative example is used to demonstrate the application of the proposed approach and its potential to enhance the management processes of CDMS enterprises. The results of the analysis indicate that the proposed blockchain approach can effectively facilitate communication and integration among CDMS enterprises. Additionally, the approach can be expanded to more complex manufacturing environments under different conditions.

Suggested Citation

  • Veera Babu Ramakurthi & Vijaya Kumar Manupati & Leonilde Varela & Goran Putnik, 2023. "Leveraging Blockchain to Support Collaborative Distributed Manufacturing Scheduling," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3283-:d:1064768
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3283/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3283/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aytug, Haldun & Lawley, Mark A. & McKay, Kenneth & Mohan, Shantha & Uzsoy, Reha, 2005. "Executing production schedules in the face of uncertainties: A review and some future directions," European Journal of Operational Research, Elsevier, vol. 161(1), pages 86-110, February.
    2. James R. Jackson, 1956. "An extension of Johnson's results on job IDT scheduling," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(3), pages 201-203, September.
    3. Xiaohui Zhang & Xinhua Liu & Shufeng Tang & Grzegorz Królczyk & Zhixiong Li, 2019. "Solving Scheduling Problem in a Distributed Manufacturing System Using a Discrete Fruit Fly Optimization Algorithm," Energies, MDPI, vol. 12(17), pages 1-24, August.
    4. Sikorski, Janusz J. & Haughton, Joy & Kraft, Markus, 2017. "Blockchain technology in the chemical industry: Machine-to-machine electricity market," Applied Energy, Elsevier, vol. 195(C), pages 234-246.
    5. Fabio Sgarbossa & Mirco Peron & Giuseppe Fragapane, 2020. "Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities," International Series in Operations Research & Management Science, in: Boris Sokolov & Dmitry Ivanov & Alexandre Dolgui (ed.), Scheduling in Industry 4.0 and Cloud Manufacturing, chapter 0, pages 87-101, Springer.
    6. Baker, Kenneth R. & Trietsch, Dan, 2009. "Safe scheduling: Setting due dates in single-machine problems," European Journal of Operational Research, Elsevier, vol. 196(1), pages 69-77, July.
    7. Guo, Z.X. & Ngai, E.W.T. & Yang, Can & Liang, Xuedong, 2015. "An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment," International Journal of Production Economics, Elsevier, vol. 159(C), pages 16-28.
    8. Ying Cheng & Luning Bi & Fei Tao & Ping Ji, 2020. "Hypernetwork-based manufacturing service scheduling for distributed and collaborative manufacturing operations towards smart manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 31(7), pages 1707-1720, October.
    9. Farnaz Torabi Yeganeh & Seyed Hessameddin Zegordi, 2020. "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, Springer, vol. 285(1), pages 161-196, February.
    10. Mirco Peron & Giuseppe Fragapane & Fabio Sgarbossa & Michael Kay, 2020. "Digital Facility Layout Planning," Sustainability, MDPI, vol. 12(8), pages 1-17, 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. Trietsch, Dan & Mazmanyan, Lilit & Gevorgyan, Lilit & Baker, Kenneth R., 2012. "Modeling activity times by the Parkinson distribution with a lognormal core: Theory and validation," European Journal of Operational Research, Elsevier, vol. 216(2), pages 386-396.
    2. Yan Wang & Ping Han, 2023. "Digital Transformation, Service-Oriented Manufacturing, and Total Factor Productivity: Evidence from A-Share Listed Companies in China," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
    3. 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.
    4. Alexey Matveev & Varvara Feoktistova & Ksenia Bolshakova, 2016. "On Global Near Optimality of Special Periodic Protocols for Fluid Polling Systems with Setups," Journal of Optimization Theory and Applications, Springer, vol. 171(3), pages 1055-1070, December.
    5. Shichang Xiao & Zigao Wu & Hongyan Dui, 2022. "Resilience-Based Surrogate Robustness Measure and Optimization Method for Robust Job-Shop Scheduling," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
    6. Faicel Hnaien & Taha Arbaoui, 2023. "Minimizing the makespan for the two-machine flow shop scheduling problem with random breakdown," Annals of Operations Research, Springer, vol. 328(2), pages 1437-1460, September.
    7. Jeoung Yul Lee & Ilkhom Okmirzaevich Irisboev & Yeon-Sik Ryu, 2021. "Literature Review on Digitalization in Facilities Management and Facilities Management Performance Measurement: Contribution of Industry 4.0 in the Global Era," Sustainability, MDPI, vol. 13(23), pages 1-29, December.
    8. Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo & Newman, Alexandra, 2024. "A target-time-windows technique for project scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 314(2), pages 792-806.
    9. Seyyed-Alireza Radmanesh & Alireza Haji & Omid Fatahi Valilai, 2023. "Blockchain-Based Architecture for a Sustainable Supply Chain in Cloud Architecture," Sustainability, MDPI, vol. 15(11), pages 1-19, June.
    10. Tandon, Anushree & Kaur, Puneet & Mäntymäki, Matti & Dhir, Amandeep, 2021. "Blockchain applications in management: A bibliometric analysis and literature review," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    11. Byeongtae Ahn, 2022. "Implementation and Early Adoption of an Ethereum-Based Electronic Voting System for the Prevention of Fraudulent Voting," Sustainability, MDPI, vol. 14(5), pages 1-16, March.
    12. Selcuk Goren & Ihsan Sabuncuoglu & Utku Koc, 2012. "Optimization of schedule stability and efficiency under processing time variability and random machine breakdowns in a job shop environment," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(1), pages 26-38, February.
    13. Shengmin Tan & Xu Wang & Chuanwen Jiang, 2019. "Privacy-Preserving Energy Scheduling for ESCOs Based on Energy Blockchain Network," Energies, MDPI, vol. 12(8), pages 1-16, April.
    14. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    15. Yan Wang & Congxianzi Pei & Qiushuo Li & Jingbang Li & Deng Pan & Ciwei Gao, 2020. "Flow Shop Providing Frequency Regulation Service in Electricity Market," Energies, MDPI, vol. 13(7), pages 1-15, April.
    16. Yuki Matsuda & Yuto Yamazaki & Hiromu Oki & Yasuhiro Takeda & Daishi Sagawa & Kenji Tanaka, 2021. "Demonstration of Blockchain Based Peer to Peer Energy Trading System with Real-Life Used PHEV and HEMS Charge Control," Energies, MDPI, vol. 14(22), pages 1-12, November.
    17. Young-Gyun Ahn & Taeil Kim & Bo-Ram Kim & Min-Kyu Lee, 2022. "A Study on the Development Priority of Smart Shipping Items—Focusing on the Expert Survey," Sustainability, MDPI, vol. 14(11), pages 1-21, June.
    18. Lemos, R.F. & Ronconi, D.P., 2015. "Heuristics for the stochastic single-machine problem with E/T costs," International Journal of Production Economics, Elsevier, vol. 168(C), pages 131-142.
    19. Hongbo Li & Linwen Zheng & Hanyu Zhu, 2023. "Resource leveling in projects with flexible structures," Annals of Operations Research, Springer, vol. 321(1), pages 311-342, February.
    20. Rhonda Righter, 1997. "A generalized Johnson's rule for stochastic assembly systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(2), pages 211-220, March.

    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:gam:jsusta:v:15:y:2023:i:4:p:3283-:d:1064768. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.