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An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment

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  • Guo, Z.X.
  • Ngai, E.W.T.
  • Yang, Can
  • Liang, Xuedong

Abstract

Global manufacturing companies have some pressing needs to improve production visibility and decision-making performance by implementing effective production monitoring and scheduling. This paper proposes a radio frequency identification (RFID)-based intelligent decision support system architecture to handle production monitoring and scheduling in a distributed manufacturing environment. A pilot implementation of the architecture is reported in a distributed clothing manufacturing environment. RFID and cloud technologies were integrated for real-time and remote production capture and monitoring. Intelligent optimization techniques were also implemented to generate effective production scheduling solutions. A prototype system with remote monitoring and production scheduling functions was developed and implemented in a distributed manufacturing environment, which demonstrated the effectiveness of the architecture. The proposed architecture has good extensibility and scalability, which can easily be integrated with production decision-making as well as production and logistics operations in the supply chain. Lastly, this paper discusses the difficulties encountered and lessons learned during system implementation and the managerial implications of the proposed architecture.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:159:y:2015:i:c:p:16-28
    DOI: 10.1016/j.ijpe.2014.09.004
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    Cited by:

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    2. Montecchi, Matteo & Plangger, Kirk & West, Douglas C., 2021. "Supply chain transparency: A bibliometric review and research agenda," International Journal of Production Economics, Elsevier, vol. 238(C).
    3. Jaroslav Vrchota & Martin Pech & Ladislav Rolínek & Jiří Bednář, 2020. "Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review," Sustainability, MDPI, vol. 12(15), pages 1-47, July.
    4. Sumera Ahmad & Suraya Miskon & Rana Alabdan & Iskander Tlili, 2020. "Towards Sustainable Textile and Apparel Industry: Exploring the Role of Business Intelligence Systems in the Era of Industry 4.0," Sustainability, MDPI, vol. 12(7), pages 1-23, March.
    5. 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.
    6. Chuang Wang & Xu’nan Chen & Abdel-Hamid Ali Soliman & Zhixiang Zhu, 2018. "RFID Based Manufacturing Process of Cloud MES," Future Internet, MDPI, vol. 10(11), pages 1-11, October.
    7. Xiaoming Qian & Jiachen Tu & Peihuang Lou, 2019. "A general architecture of a 3D visualization system for shop floor management," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1531-1545, April.
    8. Dai, Hongyan & Ge, Ling & Zhou, Weihua, 2015. "A design method for supply chain traceability systems with aligned interests," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 14-24.
    9. Wei Wang & Jingjie Chen & Qi Liu & Zhaoxia Guo, 2018. "Green Project Planning with Realistic Multi-Objective Consideration in Developing Sustainable Port," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    10. Kalaiarasan, Ravi & Olhager, Jan & Agrawal, Tarun Kumar & Wiktorsson, Magnus, 2022. "The ABCDE of supply chain visibility: A systematic literature review and framework," International Journal of Production Economics, Elsevier, vol. 248(C).
    11. Aydin Azizi, 2017. "Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing," Complexity, Hindawi, vol. 2017, pages 1-18, June.
    12. Lui, Ariel K.H. & Lo, Chris K.Y. & Ngai, Eric W.T., 2019. "Does mandated RFID affect firm risk? The moderating role of top management team heterogeneity," International Journal of Production Economics, Elsevier, vol. 210(C), pages 84-96.
    13. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
    14. Neto, Anis Assad & Ribeiro da Silva, Elias & Deschamps, Fernando & do Nascimento Junior, Laercio Alves & Pinheiro de Lima, Edson, 2023. "Modeling production disorder: Procedures for digital twins of flexibility-driven manufacturing systems," International Journal of Production Economics, Elsevier, vol. 260(C).
    15. Juan Huang & Yuhong Shuai & Qi Liu & Hang Zhou & Zhenggang He, 2018. "Synergy Degree Evaluation Based on Synergetics for Sustainable Logistics Enterprises," Sustainability, MDPI, vol. 10(7), pages 1-18, June.

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