SBIR/STTR Research Award

Enhanced Process Control of Electron Beam Additive Manufacturing

Award identifier de6761bcb8a59031df61ceabd82131ecbf4e210526ad3b4381ab7fddb5c0c218Awarding agency National Aeronautics and Space Administration

Award amount

$120,665

Program and phase

SBIR · Phase I

Award year

2021

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
SCIAKY INC
Proposal award date
2021-05-03
Contract end date
2021-11-19
UEI
HLSYVMUELL93
Solicitation number
SBIR_21_P1
Topic code
Z4

Research abstract

Sciaky has been witness to a number of process deviations that have resulted in component defects. One such ldquo;defectrdquo; is related to metal vapor condensate contamination. One of the benefits of the EBAM process is its efficient use of power as well as the high purity vacuum environment. These process characteristics allow EBAM to provide fast deposition speeds that in many cases lead the industry. One side effect of this high deposition rate with the vacuum is that the raw material is often vaporized at a high rate as well and this metal vapor condenses back into solid form on surfaces local to the process. Over time the condensate build up can become substantial and occurrences have been observed where the condensate gets dislodged and can fall into the melt pool. Sciaky has learned that in the case of EBAM deposition targeting Ti-6Al-4V, the condensate is made up of predominantly aluminum.nbsp; This issue is a well-documented concern when processing alloys with elements having various vapor pressures in a high vacuum environment.nbsp; If the condensate becomes entrapped within the molten pool, the local area no longer achieves the target chemistry or metallurgical properties.nbsp; There has been at least one instance where the condensate provided a crack initiation site that resulted catastrophic failure of a preform in response to residual stress buildup.Our phase 1 approach will target the real-time identification of metal condensate events, document the location of detected events and provide the basis for corrective action avoiding the scrapping of a part. This proof of concept shall provide the basis for a series of other identified defects to be addressed via a machine learning approach that may include material contaminants, process interruptions, gross lack of fusion type defects, large porosity and potentially others as the approaches get refined.

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.

Research funding history

10 SBIR/STTR records share this UEI (2009–2025). Reported award amounts total $7,531,982. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

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

Agency intelligence

National Aeronautics and Space Administration

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