ELECTROMECHANICAL IMPEDANCE-BASED DEFECT DETECTION IN ADDITEVELY MANUFACTURED METAL PARTS IN THE GREEN STATE

Additive Manufacturing (AM) plays a critical role in enabling the production of complex metal components with minimal waste. Bound Metal Deposition (BMD) is an AM technology that involves using metal powder suspended in a polymer binder to fabricate metal parts at relatively low temperature. At this stage, known as the green state, the binder plays a significant role in shaping the part. This process is followed by debinding and sintering stages, where the binder is removed, chemically and/or thermally, and metal particles are fused together. The latter stages are energy-intensive, timeconsuming, and significantly contribute to the overall cost associated with the process. Given the nature of this technology, the as-printed manufactured parts in the green state are prone to defects during fabrication, which, if undetected, compromise part quality after the debinding and sintering stages. Thus, early detection of manufacturing defects and anomalies is critical for this technology, and can lead to significant time, cost, and energy savings. This study investigates the feasibility of using electromechanical impedance measurements as a means for nondestructive testing (NDT) of additively manufactured metal parts, fabricated via BMD, at the green state. For this purpose, piezoelectric wafers are directly bonded to the parts under test. Owing to the coupled electromechanical characteristics of piezoelectric materials, the electrical impedance of the wafer reflects information about the part's structural properties. Thus, the presence of a defect within the part can be detected by tracking variations in the impedance signature as compared to a defect-free part. A set of test specimens, representing defect-free and defective components are designed and fabricated as part of this work. Defect-seeded parts are created through deliberate CAD model modifications, adhering to ASTM standards. These CAD-seeded defects encompass vertical cylinders to mimic voids, feature shifts to mimic dimensional inaccuracies, and partial removal of layers from the part to mimic delamination or lack of fusion. Subsequently, the as-printed parts are instrumented, and impedance signatures are measured over the frequency range of 1 - 25 kHz. Variations in impedance signatures are quantified with standard damage metrics, including root-mean-square deviation and correlation coefficients, as well as through damage sensitive features in the signature. Based on this, optimal frequency ranges for defect detection are identified, taking into consideration uncertainties induced by the instrumentation process. The results demonstrate the capability of impedance-based NDT in detecting various types of defects at the green state.