IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v57y2019i8p2247-2262.html
   My bibliography  Save this article

Serial production lines with geometric machines and finite production runs: performance analysis and system-theoretic properties

Author

Listed:
  • Zhiyang Jia
  • Liang Zhang

Abstract

A production run is typically referred to as a group of identical goods that is produced by a particular manufacturing process. In many discrete manufacturing practices, the manufacturing activity is carried out by deploying a series of production runs of different products according to customer orders. If the volume of a production run is relatively small and process changeovers are necessary, the production system operates partially (or entirely) in the transient regime, especially at the beginning and near the end of a production run. In this case, the traditional steady-state analysis approach may become inapplicable. In this paper, we consider finite production run-based manufacturing in serial lines with machines obeying the geometric reliability model and buffers having finite capacity. Exact Markovian analysis is first used to derive the closed-form formulae to calculate the transient performance of the production line during a production run as well as the distribution, mean, and standard deviation of its completion time in one- and two-machine lines. For multi-machine lines, an aggregation-based approach is proposed to approximate the system performance measures with high accuracy and computational efficiency. In addition, system-theoretic properties of production run completion time with respect to machine and buffer parameters are discussed.

Suggested Citation

  • Zhiyang Jia & Liang Zhang, 2019. "Serial production lines with geometric machines and finite production runs: performance analysis and system-theoretic properties," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2247-2262, April.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2247-2262
    DOI: 10.1080/00207543.2018.1513658
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1513658
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2018.1513658?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:57:y:2019:i:8:p:2247-2262. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.