IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v36y2025i3d10.1007_s10845-024-02328-z.html
   My bibliography  Save this article

A novel approach to enhance defect detection in wire arc additive manufacturing parts using radiographic testing without surface milling

Author

Listed:
  • Mahjoub El Mountassir

    (Equipe Monitoring et Intelligence Artificielle, Institut de Soudure)

  • Didier Flotte

    (Equipe CND Avancés, Institut de Soudure)

  • Slah Yaacoubi

    (Equipe Monitoring et Intelligence Artificielle, Institut de Soudure)

  • Eric Riff

    (Equipe CND Avancés, Institut de Soudure)

  • Morgan Ferrari

    (Equipe CND Avancés, Institut de Soudure)

  • Daniel Chauveau

    (Institut de Soudure Industrie)

  • Clément Bourlet

    (Equipe Soudage Arc, Institut de Soudure)

  • Sacha Bernet

Abstract

The wire arc additive manufacturing (WAAM) process is gaining popularity in industrial production due to its ability to manufacture large, customized, and complex shapes. However, because of the lack of quality assurance standards in this field, non-destructive testing (NDT) methods are required to evaluate the quality of the produced parts. Radiography testing is a good candidate for that purpose, but the surface roughness of the product being tested can lead to difficulties in the interpretation of the obtained image, which could result in unseen defects. To overcome this challenge, we propose, in this study, a novel approach for improving defect detectability using 3D laser scanning and an appropriate mathematical formulation. We first tested this approach on a weld bead and then verified it on different healthy and defective WAAM parts. In all cases, the created defects were successfully detected. Besides, the effect of surface roughness was significantly reduced. A special attention should, however, be paid to the scattering noise in the radiographic image.

Suggested Citation

  • Mahjoub El Mountassir & Didier Flotte & Slah Yaacoubi & Eric Riff & Morgan Ferrari & Daniel Chauveau & Clément Bourlet & Sacha Bernet, 2025. "A novel approach to enhance defect detection in wire arc additive manufacturing parts using radiographic testing without surface milling," Journal of Intelligent Manufacturing, Springer, vol. 36(3), pages 1743-1760, March.
  • Handle: RePEc:spr:joinma:v:36:y:2025:i:3:d:10.1007_s10845-024-02328-z
    DOI: 10.1007/s10845-024-02328-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-024-02328-z
    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/s10845-024-02328-z?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:36:y:2025:i:3:d:10.1007_s10845-024-02328-z. 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.