Edge-Deployed Explainable Digital-Twin Condition Based Maintenance Carrier-Based Aviation Platforms
- Client
- Washington, DC
- RFP Number
- SW-118456
- Posted
- —
- Category
- Software, System and Application
- Budget
- Looking for Proposals
- NAICS
- —
- Set-aside
- —
- Contact
- —
Description
AI GeneratedThe buyer seeks an onshore, United States organization to provide edge-deployed, explainable digital-twin condition-based maintenance platforms for carrier-based aviation platforms. The contractor must deliver offsite performance to handle massive, high-frequency streams of voltage, current, pressure, vibration, and temperature data across multiple subsystems, including Advanced Arresting Gear, steam catapults, hydraulic deck handlers, and fuel management valves. The vendor must embed hybrid physics and semantic-AI reasoning while leveraging model-order-reduction and adaptive sampling to transform raw sensor traces. Additionally, the contractor must fuse first-principles Digital Twin models with maintenance-domain knowledge graphs alongside shipboard asset and contextual mission-specific knowledge graphs. Through these integrations, the system must automatically infer and explain emerging fault modes, deliver human-readable diagnostics instead of opaque alerts, and isolate faults down to the Lowest Replaceable Unit. The buyer is currently looking for proposals and has not provided additional evaluation or key-date details.
Source and verification
Original sourceCraxy AI summarizes this opportunity from the original listing and available solicitation documents. Confirm submission instructions and amendments with the issuing source before responding.
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