AVNIK DEFENSE SOLUTIONS INC — Department of Defense STTR Phase II: A21C-T013
AVNIK DEFENSE SOLUTIONS INC — STTR Phase II award from Department of Defense.
Phase II STTR prototype / development signal
- Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
- Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
- Obligated amount $1,144,286 is consistent with substantial Phase II-scale effort; compare to related awards from the same agency.
- Topic code A21C-T013 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $1,144,286
- Agency
- Department of Defense · Army
- Program / Phase
- STTR · Phase II
- Topic
- A21C-T013
- Solicitation
- 21.C
- NAICS
- —
- Place of performance
- AL
- Period
- 2023-08-08 → 2025-08-07
Description
Technical Abstract: Operational availability, reliability, and performance of Army weapons systems platforms are key factors in achieving mission success. Army maintainers and depot artisans have a requirement for an intelligent toolset to quickly detect, locate, characterize/classify, and predict wire and connector faults in interconnect cables. AVNIK Defense Solutions, Inc. (AVNIK) has conducted Phase I of an Army Small Business Technology Transfer (STTR) project to develop an intelligent Frequency Modulated Continuous Wave (iFMCW) hand-held toolset to detect, diagnose, and predict cable faults in aircraft and missile systems. We have worked with expert subcontract team members at Auburn University, the University of Alabama at Huntsville (UAH), and Instrumental Sciences, Inc. (ISI) to research cable properties, evaluate iFMCW waveform options, evaluate candidate data analytics methods for cable fault characterization, and demonstrate key elements of the toolset in the laboratory. Primary objectives of Phase II of the project research are to design, build, test, and demonstrate an engineering prototype with (1) enhanced capabilities of the prior AVNIK iFMCW hand-held cable fault identification tool prototypes, (2) applied data analytics and artificial intelligence techniques to identify and quantify cable and connector fault characteristics, and (3) use of statistical methods to maximize fault detection/prediction accuracy of the iFMCW tool technology for cable field data sets.