Classification of metal PBF-LB parts manufactured with different process parameters using resonant ultrasound spectroscopy

Abstract

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.