Towards in situ monitoring in metal additive manufacturing using noise-sensitive ultrasonic testing and laser polishing

Abstract

Metal additive manufacturing (MAM) faces challenges with microstructural inhomogeneities such as grain structure variations during the manufacturing process. However, there has been minimal research on the development of in situ monitoring technologies to address these problems, which has hindered the widespread commercialization of MAM. Although ultrasonic testing (UT) is effective for microstructural monitoring, it is highly sensitive to noise-inducing factors, such as surface roughness, limiting its application in the in situ monitoring of MAM. This limitation is particularly critical for noise-sensitive UT techniques, such as laser ultrasonics and nonlinear ultrasonics. In this study, we incorporate laser polishing (LP) to improve the in situ monitoring performance of noise-sensitive UTs in MAM. Because LP can modify both the surface roughness and microstructure of materials, we analyzed how these changes affect the ultrasonic signals. Through metallurgical analysis, ultrasonic experiments, and numerical simulations, we demonstrated that LP has minimal impact on ultrasonic testing performance, even in laser and nonlinear UTs. Finally, we applied this technique to evaluate the grain structures of additively manufactured 316 L stainless steel. Hence, this study contributes to the quality control of additive manufacturing and supports the commercialization of MAM components.