IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v159y2015icp16-28.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527314002825
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2014.09.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Purvis, Laura & Gosling, Jonathan & Naim, Mohamed M., 2014. "The development of a lean, agile and leagile supply network taxonomy based on differing types of flexibility," International Journal of Production Economics, Elsevier, vol. 151(C), pages 100-111.
    2. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    3. Wong, W.K. & Guo, Z.X. & Leung, S.Y.S, 2014. "Intelligent multi-objective decision-making model with RFID technology for production planning," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 647-658.
    4. Fan, Ti-Jun & Chang, Xiang-Yun & Gu, Chun-Hua & Yi, Jian-Jun & Deng, Sheng, 2014. "Benefits of RFID technology for reducing inventory shrinkage," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 659-665.
    5. Chongwatpol, Jongsawas & Sharda, Ramesh, 2013. "RFID-enabled track and traceability in job-shop scheduling environment," European Journal of Operational Research, Elsevier, vol. 227(3), pages 453-463.
    6. Sari, Kazim, 2010. "Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance," European Journal of Operational Research, Elsevier, vol. 207(1), pages 174-183, November.
    7. Koulamas, Christos, 2010. "The single-machine total tardiness scheduling problem: Review and extensions," European Journal of Operational Research, Elsevier, vol. 202(1), pages 1-7, April.
    8. Zhi-Long Chen & Guruprasad Pundoor, 2006. "Order Assignment and Scheduling in a Supply Chain," Operations Research, INFORMS, vol. 54(3), pages 555-572, June.
    9. Vallada, Eva & Ruiz, Rubén, 2011. "A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 211(3), pages 612-622, June.
    10. T.C. Poon & K.L. Choy & H.C.W. Lau, 2007. "A real-time shop floor control system: an integrated RFID approach," International Journal of Enterprise Network Management, Inderscience Enterprises Ltd, vol. 1(4), pages 331-349.
    11. Zhou, Wei & Piramuthu, Selwyn, 2013. "Remanufacturing with RFID item-level information: Optimization, waste reduction and quality improvement," International Journal of Production Economics, Elsevier, vol. 145(2), pages 647-657.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu Tan & Lining Xing & Zhaoquan Cai & Gaige Wang, 2020. "Analysis of production cycle-time distribution with a big-data approach," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1889-1897, December.
    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. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.

    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. Ahmed Musa & Al-Amin Abba Dabo, 2016. "A Review of RFID in Supply Chain Management: 2000–2015," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 17(2), pages 189-228, June.
    2. Gong, Qiguo & Yang, Yuru & Wang, Shouyang, 2014. "Information and decision-making delays in MRP, KANBAN, and CONWIP," International Journal of Production Economics, Elsevier, vol. 156(C), pages 208-213.
    3. 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.
    4. Zhong, Ray Y. & Huang, George Q. & Lan, Shulin & Dai, Q.Y. & Chen, Xu & Zhang, T., 2015. "A big data approach for logistics trajectory discovery from RFID-enabled production data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 260-272.
    5. Lei, Quansheng & Chen, Jian & Wei, Xingyu & Lu, Shan, 2015. "Supply chain coordination under asymmetric production cost information and inventory inaccuracy," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 204-218.
    6. Zhang, Zhe & Song, Xiaoling & Huang, Huijung & Zhou, Xiaoyang & Yin, Yong, 2022. "Logic-based Benders decomposition method for the seru scheduling problem with sequence-dependent setup time and DeJong’s learning effect," European Journal of Operational Research, Elsevier, vol. 297(3), pages 866-877.
    7. 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).
    8. Koulamas, Christos & Kyparisis, George J., 2023. "A classification of dynamic programming formulations for offline deterministic single-machine scheduling problems," European Journal of Operational Research, Elsevier, vol. 305(3), pages 999-1017.
    9. Xingong Zhang & Guangle Yan & Wanzhen Huang & Guochun Tang, 2011. "Single-machine scheduling problems with time and position dependent processing times," Annals of Operations Research, Springer, vol. 186(1), pages 345-356, June.
    10. Muawia Ramadan & Bashir Salah & Mohammed Othman & Arsath Abbasali Ayubali, 2020. "Industry 4.0-Based Real-Time Scheduling and Dispatching in Lean Manufacturing Systems," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    11. Dung-Ying Lin & Tzu-Yun Huang, 2021. "A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem," Mathematics, MDPI, vol. 9(7), pages 1-20, April.
    12. Bai, Danyu & Tang, Mengqian & Zhang, Zhi-Hai & Santibanez-Gonzalez, Ernesto DR, 2018. "Flow shop learning effect scheduling problem with release dates," Omega, Elsevier, vol. 78(C), pages 21-38.
    13. Wen-Hung Wu & Yunqiang Yin & T C E Cheng & Win-Chin Lin & Juei-Chao Chen & Shin-Yi Luo & Chin-Chia Wu, 2017. "A combined approach for two-agent scheduling with sum-of-processing-times-based learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 111-120, February.
    14. Yung-Chia Chang & Kuei-Hu Chang & Ching-Ping Zheng, 2022. "Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards," Mathematics, MDPI, vol. 10(13), pages 1-21, July.
    15. Reyes, Pedro M. & Li, Suhong & Visich, John K., 2016. "Determinants of RFID adoption stage and perceived benefits," European Journal of Operational Research, Elsevier, vol. 254(3), pages 801-812.
    16. Min Ji & Chou-Jung Hsu & Dar-Li Yang, 2013. "Single-machine scheduling with deteriorating jobs and aging effects under an optional maintenance activity consideration," Journal of Combinatorial Optimization, Springer, vol. 26(3), pages 437-447, October.
    17. Ullrich, Christian A., 2013. "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, Elsevier, vol. 227(1), pages 152-165.
    18. Monideepa Tarafdar & Sufian Qrunfleh, 2017. "Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 925-938, February.
    19. Radosław Rudek, 2012. "Scheduling problems with position dependent job processing times: computational complexity results," Annals of Operations Research, Springer, vol. 196(1), pages 491-516, July.
    20. Lee, Jongkuk & Palekar, Udatta S. & Qualls, William, 2011. "Supply chain efficiency and security: Coordination for collaborative investment in technology," European Journal of Operational Research, Elsevier, vol. 210(3), pages 568-578, May.

    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:eee:proeco:v:159:y:2015:i:c:p:16-28. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.