Abstract <p>The introduction of additive technology in practice entails the monitoring of internal defects in the added layers (real time online monitoring) during the production of large, reliable, and expensive components, for which defects are impermissible. An engineering sketch of an additive production system for metal parts with X-ray tomographic quality monitoring of the added layers was developed in [1]. The tomographic images were analyzed by means of artificial intelligence (neural networks), and feedback-based control of the production conditions was organized. The development of X-ray computed tomographic (CT) systems for use in additive manufacturing and specialized algorithms for tomogram reconstruction in the case of conical radiation beams and helical scanning was considered in [2–7]. The present work considers the additive production of 08G2S alloy steel samples by wire arc additive manufacturing (WAAM), in the case of both defective and defect-free layers [8]. WAAM is the most productive additive manufacturing technology and is associated with the fewest defects and so is in great demand for the production of large, reliable, and expensive components, for which defects are impermissible. Optical microscopy is used to investigate the surface structure of the added layers. In addition, a high-resolution industrial X-ray computed tomography system is used to study defective and defect-free layers. Comparison of the microscopic and tomographic images permits assessment of the applicability of X-ray tomography for real time online quality monitoring of the added layers and the utility of neural networks for tomogram analysis and defect detection.</p>