IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-40060-5_56.html
   My bibliography  Save this book chapter

Research on IOT-Based Material Delivery System of the Mixed-Model Assembly Workshop

In: Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013)

Author

Listed:
  • Yun-long Wan

    (Huazhong University of Science and Technology)

  • Hai-ping Zhu

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Yan-ping Mu

    (The Trade Logistic College, Wuhan Commercial Service College)

  • Hong-chen Yu

    (Huazhong University of Science and Technology)

Abstract

Taking a mixed-model assembly workshop as the research object, this paper proposes a material distribution method based on Internet of Things (IOT). Firstly, the material information of each assembly station is monitored in real time by using the IOT technology. Then, a model for the real-time material distribution in mixed-model assembly workshop is built. Aiming at the optimization of the vehicle routing problem, an improved genetic algorithm is designed to solve this model. Finally, the IOT-based material distribution system of mixed-model assembly workshop is developed on the basis of the previous researches.

Suggested Citation

  • Yun-long Wan & Hai-ping Zhu & Yan-ping Mu & Hong-chen Yu, 2014. "Research on IOT-Based Material Delivery System of the Mixed-Model Assembly Workshop," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013), edition 127, pages 581-593, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40060-5_56
    DOI: 10.1007/978-3-642-40060-5_56
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:sprchp:978-3-642-40060-5_56. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.