IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v30y2019i3d10.1007_s10845-017-1327-1.html
   My bibliography  Save this article

Design of adaptable pin configuration machine bed optimized with genetic approach for sheet metal cutting process

Author

Listed:
  • K. Vijay Anand

    (Kumaraguru College of Technology)

  • S. Udhayakumar

    (PSG College of Technology)

Abstract

This paper proposes a novel design of machine bed used in laser, plasma and abrasive water jet (AWJ) cutting machines. During sheet metal cutting process, the laser/plasma beam pierces the sheet and further causes damage to the support bed. In contrast to the existing industrial practice of using fixed type support bed, the proposed adjustable pin type design bed adaptively provides support to the sheet by considering the parts layout that is being cut. In this design, the bed is formed with adjustable slats, in which the pins are inserted into the holes of the slats. By combining the dimensional data of machine bed and parts layout, an effective pin configuration is generated. The slats and position of the pins are represented in terms of genetic strings. The near optimal pin configuration is generated through a customized genetic algorithm. The objective is to minimize the damage caused by the tool to the bed and also to provide effective support to the different geometrical parts based on its centroid location. The effectiveness of the proposed approach is tested by combining the data of the bed and its different parts of the layout with irregular geometries. The results are promising and the uniqueness of the proposed approach is illustrated with different test cases.

Suggested Citation

  • K. Vijay Anand & S. Udhayakumar, 2019. "Design of adaptable pin configuration machine bed optimized with genetic approach for sheet metal cutting process," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1319-1333, March.
  • Handle: RePEc:spr:joinma:v:30:y:2019:i:3:d:10.1007_s10845-017-1327-1
    DOI: 10.1007/s10845-017-1327-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-017-1327-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10845-017-1327-1?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.

    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:spr:joinma:v:30:y:2019:i:3:d:10.1007_s10845-017-1327-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.