IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v44y2023i3p336-350.html
   My bibliography  Save this article

ANFIS and regression-based ANOVA for attribute and variable prediction: a case of quality characteristics in the cement bags industry

Author

Listed:
  • Mahmoud A. El-Sharief
  • Omar Salah
  • Mahmoud Heshmat

Abstract

Efficient models are significant to manufacturing systems for the purpose of prediction and performance evaluation. Traditionally, regression models have been widely held for this purpose; recently, soft computing models are widely used. Efficiency of soft computing models depends on the size of the problem dataset. In this paper, we conduct a regression-based ANOVA study and ANFIS for cement bags production. Quality characteristics of bag dimensions are considered. The results show that ANFIS can predict attributes and variables of production lines more than regression-based ANOVA.

Suggested Citation

  • Mahmoud A. El-Sharief & Omar Salah & Mahmoud Heshmat, 2023. "ANFIS and regression-based ANOVA for attribute and variable prediction: a case of quality characteristics in the cement bags industry," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 44(3), pages 336-350.
  • Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:336-350
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=132283
    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.

    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:ijisen:v:44:y:2023:i:3:p:336-350. 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=188 .

    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.