SBIR/STTR Research Award

Real Time Non-Destructive Evaluation during 3D Manufacturing of Metal Parts

Award identifier 84f55f1bb8a0c8ac955689a1eb93102e1fc5cababdfbdca6686a7e1abe327922Awarding agency Department of Energy

Award amount

$149,995

Program and phase

SBIR · Phase I

Award year

2018

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 Energy
Branch
Not reported
Recipient company
LER TECHNOLOGIES INC
Proposal award date
2018-07-02
Contract end date
2019-04-01
UEI
NUB4MK6NUJQ8
Solicitation number
DE-FOA-0001771
Topic code
30g

Research abstract

Additive manufacturing, such as laser sintering or melting of additive layers can produce parts rapidly at small volume and in a factory setting. To make the parts nuclear quality, a real-time non-destructive evaluation (NDE) technique is required to detect defects while they are being manufactured. The proposed NDE technique is a feasibility study of an optical sensor unit that is incorporated in a direct laser sintering machine to capture defects in real-time. The sensor data can be used to identify defects as they occur such that immediate corrective action can be taken. It also provides parameters that enable the prediction if the part is of nuclear quality.The proposed work will be a multi-parameter sensing approach, incorporating multiple optical sensing and imaging techniques. The apparatus will be incorporated in a 3D metal printing machine. The final outputs of the sensors will be combined to produce a defect map in real-time as the part is being printed. Defects such as voids improper melting, bulging of the metal, and out-of-spec prints will be revealed.During Phase I, the feasibility of the proposed multi- parameter NDE approach will be demonstrated using a combination of theory and experiments. Samples with representative defects that occur during additive manufacturing of metal parts will be prepared and tested to demonstrate the ability and effectiveness of the proposed approach. Commercial Applications and Other Benefits: When this NDE technology is commercialized by carrying over to Phase II and Phase III, the sensor unit will be incorporated in the 3D printing machines without requiring design changes to the machine. The unit will detect printing defects in real-time. The sensor data will be utilized to pre-qualify parts for nuclear quality, and therefore minimize or eliminate the need for post fabrication testing. The economic benefits include reduction of cost of post-process testing, and significant reduction of loss of labor and material due to faulty parts. DOE and other branches of the government will benefit by streamlining the nuclear parts manufacturing. The reduced cost of manufacturing will help transition to modern nuclear energy, which will benefit the public by providing safe and cost effective energy solution. Other applications include NDE for manufacturing parts for the aerospace industry.

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

10 SBIR/STTR records share this UEI (2003–2022). Reported award amounts total $4,435,862. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation, Department of Energy, National Aeronautics and Space Administration

Agency intelligence

Department of Energy

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.