SBIR/STTR Research Award

Non-Destructive Evaluation of Additive Manufacturing Parts Using Resonance Spectroscopy

Award identifier 467e905293c1a3fd1b0db6cf8a3fb09c32abffaaae157357cd40dd3d67d48d2bAwarding agency Department of Defense · Missile Defense Agency

Award amount

$154,953

Program and phase

SBIR · Phase I

Award year

2021

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Missile Defense Agency
Recipient company
METROLASER, INCORPORATED
Proposal award date
2020-12-28
Contract end date
2021-06-30
UEI
RB8MDWWD5MF8
Solicitation number
20.2
Topic code
MDA20-011

Research abstract

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)

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

308 SBIR/STTR records share this UEI (1989–2025). Reported award amounts total $100,196,325. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Energy, National Science Foundation, Department of Commerce, Department of Health and Human Services

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.