IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v43y2011i3p176-191.html
   My bibliography  Save this article

Simulation-based estimation of cycle time using quantile regression

Author

Listed:
  • Nan Chen
  • Shiyu Zhou

Abstract

Production cycle time is an important performance measure in manufacturing systems, and thus it is of interest to characterize distributional properties, such as quantiles, for informative decision making. This article proposes a non-linear quantile regression model for the relationship between stationary cycle time quantiles and corresponding throughput rates of a manufacturing system. The statistical properties of the estimated cycle time quantiles are investigated and the impact of dependent data from simulation output on parameter estimations is analyzed. Extensive numerical studies are presented to demonstrate the effectiveness of the proposed methods.

Suggested Citation

  • Nan Chen & Shiyu Zhou, 2011. "Simulation-based estimation of cycle time using quantile regression," IISE Transactions, Taylor & Francis Journals, vol. 43(3), pages 176-191.
    • Handle: RePEc:taf:uiiexx:v:43:y:2011:i:3:p:176-191
    DOI: 10.1080/0740817X.2010.521806
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2010.521806
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0740817X.2010.521806?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.

    Citations

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


    Cited by:

    1. Batur, Demet & Bekki, Jennifer M. & Chen, Xi, 2018. "Quantile regression metamodeling: Toward improved responsiveness in the high-tech electronics manufacturing industry," European Journal of Operational Research, Elsevier, vol. 264(1), pages 212-224.

    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:uiiexx:v:43:y:2011:i:3:p:176-191. 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/uiie .

    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.