SBIR/STTR Research Award

Autonomic Reasoning-based Troubleshooting Management System

Award identifier 3f156ce6608281431750c8d2f32115a1381ba6e9d1b4357ffa03e429dfdb25d0Awarding agency Department of Defense · Air Force

Award amount

$99,934

Program and phase

SBIR · Phase I

Award year

2010

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 Defense
Branch
Air Force
Recipient company
RIDGETOP GROUP INC
Proposal award date
2010-07-01
Contract end date
2011-02-28
UEI
CRLUWHJZHLU8
Solicitation number
2009.3
Topic code
AF093-208

Research abstract

Ridgetop will develop an advanced reasoning-based troubleshooting algorithm to identify the failed components in complex mechanical/electrical systems. The reasoning-based algorithm will be used in an Autonomic Reasoning-based Troubleshooting (ART) management system which will provide support for maintenance personnel in the following areas: (1) the integration with Condition Based Maintenance (CBM) activities; (2) the interpretation of the components interactions; (3) reduction of uncertainty by updating CBM information with in-situ measurement; and (4) an easy-to-use tool with a user-interface and automation support. The significance of the innovation is that expert troubleshooting systems are needed to achieve significant savings by learning what diagnostic actions lead to correct outcomes and minimize wasted time and effort while achieving reduced maintenance costs. Studies show that it is possible to achieve 20% savings on deployed electronic systems. In Phase I, Ridgetop will develop and deliver the design of an ART systems including: - Mapping the fault tree into a reasoning-based troubleshooting algorithm - Interpretation of the component interactions through hierarchical, spatial and temporal information - Reduction of uncertainty with in-situ measurement - Design of an easy-to-use tool including a user-interface and autonomic capability - Validation of the algorithm to quantify the potential benefits through appropriate metrics BENEFIT: For today’s complex military aircraft, rigorous routine inspection and maintenance procedures are performed to ensure the health of the plane’s numerous mechanical and electronic systems. While vital, this constant process has seen significant cost increases over the past 10 years as various cost components such as labor, parts, and aircraft downtime rise in conjunction with the increasing complexity of these systems. The proposed autonomic reasoning-based troubleshooting (ART) analysis model can drastically reduce these costs via the rapid identification of faults and failures which typically take significant amounts of time to repair. In addition, Ridgetop’s innovation will provide an intelligent, user-friendly interface supplying not only the visual diagnosis, but an optimal action plan and rationale to correct the issue as well. Specifically designed for aircraft such as the C-130 and F-15, the innovation can also be applied to the ECSS, F-35, NASA NextGen Shuttles, UAV’s, commercial aircraft, and commercial automotive applications.

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

80 SBIR/STTR records share this UEI (2001–2025). Reported award amounts total $27,524,868. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

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

Agency intelligence

Department of Defense

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.