Automated robotic system for dual ultrasonic and eddy current array integration and data fusion in wire arc additive manufacturing material inspection

Wire Arc Additive Manufacturing (WAAM) is a direct energy deposition method that enables the fabrication of large, complex metal components with minimal material waste, making it a key technology within Industry 4.0. However, WAAM is prone to weld-like defects, such as lack of fusion, keyholes, and porosities, which compromise structural integrity and require a reliable Non-Destructive Evaluation (NDE). Conventional post-process inspection methods, including Ultrasonic Testing (UT) and X-ray imaging, can detect such defects but often lead to costly rework once fabrication is complete. This work presents a dual-sensor robotic inspection system enabling simultaneous phased array UT and Eddy Current Testing (ECT) during WAAM deposition for early defect detection and efficient process monitoring. The system integrates an industrial manipulator with closed-loop force-torque control for repeatable layer-wise scanning without tool changes or process interruption. The system was evaluated using two Ti-6Al-4V reference blocks that replicated WAAM geometries and contained artificial defects. A depth-weighted C-scan data fusion approach, supported by targeted ECT denoising, improved contrast-to-noise ratio by 4.44 dB and 9.02 dB for the two samples, respectively. The approach was further validated on a titanium WAAM sample containing embedded tungsten inclusions, demonstrating the robustness of the methodology. A receiver operating characteristic analysis further confirmed the improved defect discrimination of the fused data, consistently resulting in higher area-under-curve values than either UT or ECT alone across all evaluated samples.

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Publication Details

Journal
NDT & E International
Published
2026-02-10
DOI
https://doi.org/10.1016/j.ndteint.2026.103665
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
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article

Automated robotic system for dual ultrasonic and eddy current array integration and data fusion in wire arc additive manufacturing material inspection

Shaun McKnight, R. B. GOMES, Rastislav Zimermann, Euan Foster et al.
NDT & E International
Additive Manufacturing Materials and Processes
article

Automated robotic system for dual ultrasonic and eddy current array integration and data fusion in wire arc additive manufacturing material inspection

Shaun McKnight, R. B. GOMES, Rastislav Zimermann, Euan Foster, Vedran Tunukovic, Charalampos Loukas, S.Gareth Pierce, Randika K.W. Vithanage, Stewart Williams, Ehsan Mohseni, Charles N. MacLeod
article en

Abstract

Wire Arc Additive Manufacturing (WAAM) is a direct energy deposition method that enables the fabrication of large, complex metal components with minimal material waste, making it a key technology within Industry 4.0. However, WAAM is prone to weld-like defects, such as lack of fusion, keyholes, and porosities, which compromise structural integrity and require a reliable Non-Destructive Evaluation (NDE). Conventional post-process inspection methods, including Ultrasonic Testing (UT) and X-ray imaging, can detect such defects but often lead to costly rework once fabrication is complete. This work presents a dual-sensor robotic inspection system enabling simultaneous phased array UT and Eddy Current Testing (ECT) during WAAM deposition for early defect detection and efficient process monitoring. The system integrates an industrial manipulator with closed-loop force-torque control for repeatable layer-wise scanning without tool changes or process interruption. The system was evaluated using two Ti-6Al-4V reference blocks that replicated WAAM geometries and contained artificial defects. A depth-weighted C-scan data fusion approach, supported by targeted ECT denoising, improved contrast-to-noise ratio by 4.44 dB and 9.02 dB for the two samples, respectively. The approach was further validated on a titanium WAAM sample containing embedded tungsten inclusions, demonstrating the robustness of the methodology. A receiver operating characteristic analysis further confirmed the improved defect discrimination of the fused data, consistently resulting in higher area-under-curve values than either UT or ECT alone across all evaluated samples.

NDT & E InternationalVol. 160
University of Strathclyde (GB), Cranfield University (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 61%
Additive Manufacturing Materials and Processes
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