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Hypernetwork-based manufacturing service scheduling for distributed and collaborative manufacturing operations towards smart manufacturing

Author

Listed:
  • Ying Cheng

    (Beihang University (BUAA)
    The Hong Kong Polytechnic University)

  • Luning Bi

    (Beihang University (BUAA))

  • Fei Tao

    (Beihang University (BUAA))

  • Ping Ji

    (The Hong Kong Polytechnic University)

Abstract

In the future smart manufacturing, both of sensor-based environment in shop floors and cloud-based environment among more and more enterprises are deployed gradually. Various distributed and separated manufacturing facilities are as collaborative cloud services, integrated and aggregated with their real-time information. It provides opportunities for the distributed and collaborative manufacturing operations across lots of distributed but networked enterprises on demand with enough flexibility. To this end, the scheduling problem and its result of those collaborative services for distributed manufacturing operations play an important role in improving manufacturing utilization and efficiency. In this paper, we put forward the hypernetwork-based models introducing the thought of graph coloring and an artificial bee colony algorithm based method for this scheduling problem. Three groups of experiments are carried out respectively to discuss therein different situations of distributed and collaborative manufacturing operations, i.e., in a private cloud, in a public cloud, and in a hybrid cloud. Some future studies with further consideration of collaboration equilibrium, dynamic control and data-based intelligence, are finally pointed out in the conclusion.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:7:d:10.1007_s10845-018-1417-8
    DOI: 10.1007/s10845-018-1417-8
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    References listed on IDEAS

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    1. Nishikant Mishra & Akshit Singh & Sushma Kumari & Kannan Govindan & Syed Imran Ali, 2016. "Cloud-based multi-agent architecture for effective planning and scheduling of distributed manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7115-7128, December.
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    Cited by:

    1. Peng Zhan & Shaokun Wang & Jun Wang & Leigang Qu & Kun Wang & Yupeng Hu & Xueqing Li, 2021. "Temporal anomaly detection on IIoT-enabled manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1669-1678, August.
    2. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    3. 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.

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