SBIR/STTR Award attributes
Additive manufacturing technology enables field production of spare parts, building non-traditional shapes and sizes, a reduction in the required number of individual parts, and expedited production, all offering great potential to the DOD. However, such parts can suffer from a combination of defect types and inherent problems, specific to AM that are difficult to detect in the finished part with conventional inspection methods. Such defects change the mechanical properties of the material and affect performance of a part. This SBIR Phase I proposal is to develop and demonstrate a method to evaluate printed parts and to enable certification of subsequent similar printed parts without employing current destructive, expensive, and time-consuming methods. Every object is a unique vibrational system that can be categorized by its vibrational spectrum. It is virtually impossible for two objects that are not identical to have the same vibrational spectrum; therefore, this spectrum provides a unique signature that matches and identifies specific components free of many types of defects. Vibrational properties of components, such as resonant modes, damping, and spectral frequency depend strongly upon the mechanical properties of the material, including its internal hardness, tensile strength, alloy/composite compositions, flaws, defects, and other internal material properties, and they respond differently to various forcing functions. In previous research we have demonstrated how such defects and printing errors affect the vibrational spectrum of AM parts, how the spectrum can be employed as a signature that is altered in a detectable manner, and how to measure and correlate such signatures with AM anomalies. The concept leads to a non- destructive testing method that can detect relevant defects in 3D printed metal parts and provide information for an assortment of representative part designs that can be correlated statistically with tests-to-failure. In this research we will print a large number of metal test coupons with and without known defects, measure their acoustical signatures with laser Doppler vibrometry, and determine if deviations from the predicted signature and parts known to be without defects can be correlated with the known defects and correlate these with tests to failure. The proposal includes a plan to develop and demonstrate methods of both predicting and measuring the effects of typical manufacturing defects on the acoustical signatures of AM parts This can lead to a relatively simple procedure to anticipate critical problems in AM parts without employing complex and expensive NDE or destructive testing methods. Approved for Public Release | 20-MDA-10643 (3 Dec 20)
