IDEAS home Printed from https://ideas.repec.org/a/igg/jmmme0/v2y2012i1p30-46.html
   My bibliography  Save this article

Modeling of Cement-Bonded Sand Mould System: An Artificial Intelligence Approach

Author

Listed:
  • B. Surekha

    (DVR & Dr. HS MIC College of Technology, India)

  • Pandu R. Vundavilli

    (DVR & Dr. HS MIC College of Technology, India)

  • M. B. Parappagoudar

    (Chhatrapati Shivaji Institute of Technology, India)

Abstract

The present paper deals with the forward mapping problem of cement bonded sand mould system using fuzzy logic (FL)-based approaches. It is important to note that the performance of an FL-based approach depends on its knowledge base (KB) that is, rule base and data base. Here, three approaches have been proposed to solve the said problem. The first Approach deals with the development of manually constructed Mamdani-based FL system, and the second Approach deals with the optimization of the rule base and data base of the FL system constructed in Approach 1, whereas the third Approach deals with automatic evolution of the FL system, in which the consequent part has also been optimized. A binary coded genetic algorithm (GA) has been used for the said purpose. The performances of the developed approaches are tested in forward mapping of a cement bonded sand mould system. It is to be noted that all the approaches can be effectively used to model the cement-bonded moulding sand system.

Suggested Citation

  • B. Surekha & Pandu R. Vundavilli & M. B. Parappagoudar, 2012. "Modeling of Cement-Bonded Sand Mould System: An Artificial Intelligence Approach," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), IGI Global, vol. 2(1), pages 30-46, January.
    • Handle: RePEc:igg:jmmme0:v:2:y:2012:i:1:p:30-46
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2012010103
    Download Restriction: no
    ---><---

    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:igg:jmmme0:v:2:y:2012:i:1:p:30-46. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.