IDEAS home Printed from https://ideas.repec.org/a/ids/ijenma/v1y2007i4p331-349.html
   My bibliography  Save this article

A real-time shop floor control system: an integrated RFID approach

Author

Listed:
  • T.C. Poon
  • K.L. Choy
  • H.C.W. Lau

Abstract

In the past, it was difficult to have a clear picture of the present status of production in shop floor. Many enterprises have adopted bar-code-based Shop Floor Control Systems (SFCSs) for monitoring the production status. However, the deficiency of such systems is that immediate situation cannot be reflected easily. As a result, planned production schedules cannot be fulfilled due to frequent job interruptions caused by machine breakdowns or a shortage of materials. In this paper, a Radio Frequency Identification- (RFID-)based Decision Support System (RDSS) is proposed for the shop floor management to keep track of resources, monitor the throughput rate and make instant decisions for problem solving. The proposed system integrates the technologies of RFID and Rule-Based Reasoning (RBR) with production mathematical algorithm to help monitor shop floor operations. Through pilot running of RDSS in the ABC Limited, a significant improvement in terms of shop floor responsiveness was achieved.

Suggested Citation

  • 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.
  • Handle: RePEc:ids:ijenma:v:1:y:2007:i:4:p:331-349
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=13903
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. Cagno, Enrico & Accordini, Davide & Trianni, Andrea & Katic, Mile & Ferrari, Nicolò & Gambaro, Federico, 2022. "Understanding the impacts of energy efficiency measures on a Company’s operational performance: A new framework," Applied Energy, Elsevier, vol. 328(C).
    2. 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.

    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:ids:ijenma:v:1:y:2007:i:4:p:331-349. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=187 .

    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.