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

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Tunukovic, Vedran and Gomes, Rylan and McKnight, Shaun and Zimermann, Rastislav and Foster, Euan and Loukas, Charalampos and Vithanage, Randika K.W. and Mohseni, Ehsan and Pierce, S. Gareth and MacLeod, Charles N. and Williams, Stewart (2026) Automated robotic system for dual ultrasonic and eddy current array integration and data fusion in wire arc additive manufacturing material inspection. NDT and E International, 160. 103665. ISSN 0963-8695 (https://doi.org/10.1016/j.ndteint.2026.103665)

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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.

ORCID iDs

Tunukovic, Vedran ORCID logoORCID: https://orcid.org/0000-0002-3102-9098, Gomes, Rylan ORCID logoORCID: https://orcid.org/0009-0004-9937-7322, McKnight, Shaun ORCID logoORCID: https://orcid.org/0000-0002-3904-5092, Zimermann, Rastislav, Foster, Euan, Loukas, Charalampos ORCID logoORCID: https://orcid.org/0000-0002-3465-8076, Vithanage, Randika K.W. ORCID logoORCID: https://orcid.org/0000-0002-1023-2564, Mohseni, Ehsan ORCID logoORCID: https://orcid.org/0000-0002-0819-6592, Pierce, S. Gareth ORCID logoORCID: https://orcid.org/0000-0003-0312-8766, MacLeod, Charles N. ORCID logoORCID: https://orcid.org/0000-0003-4364-9769 and Williams, Stewart;
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