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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
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    References listed on IDEAS

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    1. Cheng, C.-L. & Shalabh, & Garg, G., 2014. "Coefficient of determination for multiple measurement error models," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 137-152.
    2. A. Chabot & N. Laroche & E. Carcreff & M. Rauch & J.-Y. Hascoët, 2020. "Towards defect monitoring for metallic additive manufacturing components using phased array ultrasonic testing," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1191-1201, June.
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