AURA TECHNOLOGIES Wins U.S. Army Contract ― SBIR Phase II Research Using AI to Tackle Parts-Supply Shortages (DMSMS) — a federal contract (USAspending)
The U.S. Army (Department of Defense) awarded AURA TECHNOLOGIES, LLC a federal contract of about $1.58 million. It funds SBIR Phase II research on using AI (artificial intelligence) to address the problem of equipment parts becoming hard to obtain (DMSMS).
Contract key facts
- RecipientAURA TECHNOLOGIES, LLC
- Contract value$1,579,931 (≈$1.6M)
- Awarding agencyDepartment of Defense
- Awarding sub-agencyDepartment of the Army
- Award typeDEFINITIVE CONTRACT
- Period of performance2022-06-15 〜 2024-06-14
- Contract ID (PIID)W15QKN22C0047
Contract scope (original)
SBIR PHASE II FOR ARTIFICIAL INTELLIGENCE FOR DIMINISHING MANUFACTURING SOURCES AND MATERIAL SHORTAGES (DMSMS)
Key points
- Awarded by the Department of Defense / U.S. Army to AURA TECHNOLOGIES, LLC for $1,579,931 (PIID: W15QKN22C0047).
- The subject is SBIR Phase II research on applying AI to DMSMS (Diminishing Manufacturing Sources and Material Shortages).
- DMSMS is the problem of part makers and materials leaving the market as equipment ages, making parts hard to obtain.
- SBIR Phase II is the substantial development stage that follows initial proof of concept.
- Specific deliverables, outcomes, or the level of research progress are not stated in the source.
Military equipment such as weapons, vehicles, and electronics is often kept in service for decades. The companies that make the electronic components and materials inside that equipment, however, refresh their product lines or exit the business within just a few years. This mismatch ― long-lived equipment versus short-lived part supply ― produces what is called DMSMS (Diminishing Manufacturing Sources and Material Shortages). Once a part goes out of production it can vanish from the market, making every repair or upgrade harder to source. This contract funds SBIR Phase II research that approaches the problem with AI (artificial intelligence ― technology that learns patterns from large amounts of data to support prediction and decision-making).
SBIR (Small Business Innovation Research) is a federal program that supports small-business research and development in stages, with Phase II being the substantial development stage that follows initial proof of concept. In other words, this award marks the point where the idea has moved past the concept stage and received funding for development toward practical use. Why it matters: DMSMS is not simply running out of parts. The key is to predict which parts are at risk before supply is cut off, and to find substitute parts or alternative suppliers early. Tracking every part by hand is an enormous task, so the intent of applying AI ― which excels at analyzing large data sets ― can be read from the subject.
Viewed more broadly, this contract sits where military logistics and sustainment (the work of keeping equipment usable over time) meet AI. The idea of getting ahead of supply-chain risk using data is relevant well beyond defense, reaching any industry that operates long-lived facilities or infrastructure. Note that the research's level of progress or any deployment results are not stated in the source, so they are not covered here.
Why it matters
This is an effort to identify supply-chain risk for long-lived equipment and facilities early, based on data. It is a useful reference case for organizations involved in defense logistics and sustainment, and for industries that face long-term parts procurement. Specific outcomes or scope of application are not stated in the source.
FAQ
What is DMSMS?
What stage is SBIR Phase II?
What was produced in this research?
Sources (primary)
This article is an independent organization based on the U.S. official spending data below. Verify the exact, latest details with the official source.
- USAspending (award details)
- Contract ID (PIID)：W15QKN22C0047