SBIR/STTR Research Award

USAF AUGMENTED MAINTENANCE PREDICTION (AMP) for Technology Area: 1. Aerospace Systems Technology

Award identifier 84167054f2770db32368afaaf14245549bb3d723287389cea865b1cb33e9aadcAwarding agency Department of Defense · Air Force

Award amount

$49,656

Program and phase

STTR · Phase I

Award year

2021

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
RIIS TECHNOLOGY LLC
Proposal award date
2021-02-08
Contract end date
2021-05-08
UEI
X99PLDJ3HZ48
Solicitation number
X20.C
Topic code
AF20C-TCSO1

Research abstract

Augmented Maintenance Prediction (AMP) enhances Condition Based Maintenance (CBM+) activities by monitoring the unique molecular markers produced by the decomposition of gaskets, fluids, and lubricants in complex mechanical systems. The current information driving CBM+ predictive maintenance is generally limited to a fleet’s logs of historic use, reported issues, SOAPS analysis, and historic maintenance, each of which is used to predict the probability of mechanical failure. AMP increases the ability of CMB+ to predict mechanical failure by identifying the molecular markers of aging/failing parts before they are observable to maintenance staff. With this molecular analysis, AMP improves the ability of CMB+ to proactively identify opportunities for low-cost interventions to avoid high-cost catastrophic failure.  ?AMP leverages a novel and inexpensive batch-collection technology to capture the full spectrum of volatile chemistry present at different physical locations in the mechanical system. AMP can be used before, during, or after equipment use. The AMP Collectors are then batch-processed through a GC-Mass Spectrometer. AMP’s unique AI is then applied to match chemical signatures identified to specific lubricants, fluids, degradation of gaskets, and by-products of combustion. Combining AMP’s intelligence with the data from historic use, environmental conditions, and maintenance logs, AMP will recommend parts to be inspected by technicians during future field- and depot-level maintenance. With the subsequent and ongoing feedback of the findings from activities prescribed by AMP, the system becomes more intelligent and accurate at predicting mechanical failure and optimizing maintenance in the context of part availability and other supply chain constraints. In addition to identifying the need for service, AMP assists in optimizing the schedule for “Time-Change Tasks”, moving them to “Demand-Change Tasks”: reducing unnecessary basic maintenance and expediting the detection of advanced issues prior to scheduled maintenance. AMP enhances the ability of CMB+ to reduce cost, improve performance, enhance readiness, and improves the predictability of the overall maintenance and requisition supply chain.

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

7 SBIR/STTR records share this UEI (2021–2023). Reported award amounts total $1,097,696. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

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.