IDEAS home Printed from https://ideas.repec.org/a/ids/ijpmbe/v10y2020i1p22-47.html
   My bibliography  Save this article

Quality edge extraction of mechanical CAD parts for intelligent manufacturing

Author

Listed:
  • Tushar Jain
  • Meenu
  • H.K. Sardana

Abstract

Computer aided testing (CAT) is the latest technique. It is because CAT involve in a different stages of manufacturing like designing, production and quality control by 3D measuring instrument that is time consuming. If the object position is known before examined, time can be managed. Machine vision dependent inspection of mechanical CAD parts has become demanding area in the field of industrial inspection. In this work, we developed the procedure to detect the mechanical CAD parts with the edge-based algorithms. The data has been taken with 3D model that has been designed using solid edge ST8 CAD/CAM PLM software and analysed using MATLAB for automated production checking system. Our proposed method uses the edge-based recognition of CAD object by fuzzy-based approach in order to create image information of shape before it can be used for pose estimation in computer aided testing system. From the experimental results, it has been found that with the proposed vision system more accurate and reliable products can be manufactured intelligently.

Suggested Citation

  • Tushar Jain & Meenu & H.K. Sardana, 2020. "Quality edge extraction of mechanical CAD parts for intelligent manufacturing," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 10(1), pages 22-47.
  • Handle: RePEc:ids:ijpmbe:v:10:y:2020:i:1:p:22-47
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=104230
    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:ijpmbe:v:10:y:2020:i:1:p:22-47. 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=95 .

    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.