Additive manufacturing (AM) enables the production of parts with extremely complex shapes, such as lattice structures and internal structures (cavities, channels). As a result of this geometric complexity, the applicability of most conventional nondestructive testing (NDT) techniques to AM parts is limited, and innovative volumetric NDT methods are needed for quality control. Few established volumetric NDT methods are suitable for inspecting the integrity of parts with complex geometries. X-ray computed tomography (XCT) is widely recognized as the most powerful method for detecting and evaluating the dimensions of structural flaws and also for checking the compliance of parts with their numerical model. However, it is an expensive method. The image analysis takes more time than is appropriate for routine inspection, and the files are large and, thus, difficult to handle. Furthermore, XCT is not suitable for large and high-density parts. Alternative methods are therefore needed. Investigation of resonant acoustic methods such as resonant ultrasound spectroscopy (RUS) or electromagnetic-acoustic resonance methods, linear or nonlinear, has shown great potential. RUS methods are global, enabling identification of defective parts based on analysis of their natural resonant frequencies. There are several variants of RUS methods, but their basic principles are similar. They can inspect any part shape, and they are insensitive to inherent surface roughness. In addition, although they are global volumetric methods (“pass/fail”), they can inspect parts of any size, unlike XCT, which can determine the locations of defects but is restricted by the size or density of the parts. Moreover, compared to XCT, they are simple to implement, easy to use, quite affordable, and the inspection of the parts is particularly fast, which is very suitable for routine inspection. This article describes the capabilities of various linear RUS methods, as well as a nonlinear electromagnetic-acoustic resonance method for quality assurance of AM parts.

To face the challenges raised by the qualification of metallic additively manufactured (AM) complex shaped and rough finish parts, non-destructive testing (NDT) volumetric methods are required. X-ray computed tomography (XCT) is presently the favored technique; however, alternative methods are needed to overcome the requirement of technical skills and the high cost of the technique. XCT also has limitations regarding the size and density of parts. Here, we propose an easy to use, fast, and efficient global NDT volumetric method based on resonant ultrasound spectroscopy (RUS) which basic principle relies on the comparative analysis of natural resonant frequency spectra of similar parts from the same family, both of which vibrating as free as possible. The methods have already proven to have the ability to sort parts with defects from flawless parts. In the present study, we demonstrate that RUS can also segregate metallic parts manufactured with different AM system process parameters. Eleven sets of three parts were manufactured, using a metal laser-powder bed fusion process, with different wall thicknesses, laser powers, scanning speeds, and scanning strategies. These parts were tested by RUS and then analyzed using the Z-score statistical method. The AM process parameter changes clearly influenced the resonance responses of the parts, and thus, the method is able to classify the different groups of parts according to their process parameters. Hence, the RUS methods can provide industries convenient tools to not only identify defective parts but to also configure AM machine parameters according to the expected and desired material properties.