This work proposes the utilization of electromechanical impedance measurements as a means of non-destructive evaluation (NDE) for additive manufacturing (AM). The effectiveness and sensitivity of the technique for a variety of defect types commonly encountered in AM are investigated.
To evaluate the feasibility of impedance-based NDE for AM, the authors first designed and fabricated a suite of test specimens with build errors typical of AM processes, including dimensional inaccuracies, positional inaccuracies and internal porosity. Two polymer AM processes were investigated in this work: material jetting and extrusion. An impedance-based analysis was then conducted on all parts and utilized, in a supervised learning context, for identifying defective parts.
The newly proposed impedance-based NDE technique has been proven to be an effective solution for detecting several types of print defects. Specifically, it was shown that the technique is capable of detecting print defects resulting in mass change (as small as 1 per cent) and in feature displacement (as small as 1 mm) in both extruded nylon parts and jetted VeroWhitePlus parts. Internal porosity defects were also found to be detectable; however, the impact of this defect type on the measured impedance was not as profound as that of dimensional and positional inaccuracies.
Compared to currently available NDE techniques, the newly proposed impedance-based NDE is a functional-based technique with the advantages of being cost-effective, sensitive and suitable for inspecting AM parts of complex geometry and deeply embedded flaws. This technique has the potential to bridge the existing gaps in current NDE practices, hence paving the road for a wider adoption of AM to produce mission-critical parts.