A Predictive Maintenance Solution for Aircraft Health Monitoring that can Learn and Improve Over Time
Award amount
$71,661Program and phase
SBIR · Phase IAward year
2024Award details
- Awarding agency
- Department of Defense
- Branch
- Air Force
- Recipient company
- PREDICTRONICS CORP
- Proposal award date
- 2023-12-13
- Contract end date
- 2024-03-13
- UEI
- MEB7MTZDX629
- Solicitation number
- X23.7
- Topic code
- AFX237-PCSO1
Research abstract
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.
- Digital Twin-Based Process Monitoring, In-Situ Defect Detection, and Real-Time Process Adjustment Solution for Automated Fiber Placement (AFP) Process
- Normalization the Effect of Multiple Operating Conditions for Robust Machining Center Predictive Maintenance
- N193-A01 NAVY TECHNOLOGY ACCELERATION - Machine Learning (ML) and Artificial Intelligence (AI) to Develop Capabilities and Impact Mission Success
- NAVY TECHNOLOGY ACCELERATION - Machine Learning (ML) and Artificial Intelligence (AI) to Develop Capabilities and Impact Mission Success
- SBIR Phase I: A Fleet-based Fault Detection System Based on Clustering Approach
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Penetration X-ray Inspection of Spacecraft
- AI Enhanced Battle Damage Assessment and Ballistic Prediction for Medium Range UAS
- ThinkOrbital TACFI
- Accurate Drone Localization Using Lighthouse's Innovative Computer Vision-Based Airspace Management System and Integrated RF Sniffing
- QuickSAT/SHERLOCK, An AI Architecture For In Situ Vehicle Monitoring, Vehicle Health Management and Fault Detection
Research funding history
6 SBIR/STTR records share this UEI (2014–2026). Reported award amounts total $2,051,960. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: Department of Defense, National Science Foundation