Edge-Deployed Explainable Digital Twin Condition-Based Maintenance Platforms for Carrier-Based Aviation
Overview
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SUMMARY
KEY REQUIREMENTS
TIMELINE
August 5th, 2026: Topics Pre-Release
August 26th, 2026: Topics Open; DoW begins accepting proposals in DSIP
September 9th, 2026: DSIP Topic Q&A closes to new questions at 12:00 p.m. ET
September 23rd, 2026: Topics Close; Deadline for receipt of proposals is 12:00 p.m. ET
QUESTION DEADLINE
CONTACTS
Primary procurement contact — name, title, email, and phone
Additional decision-makers and their departments
Issuing Agency
Department Of War
DESCRIPTION
The vendor will provide edge-deployed, explainable digital-twin condition-based maintenance platforms for carrier-based aviation systems. The platforms must support the processing of massive, high-frequency streams of voltage, current, pressure, vibration, and temperature data generated across multiple subsystems.
Applicable systems include Advanced Arresting Gear, steam catapults, hydraulic deck handlers, and fuel management valves. The solution will embed hybrid physics and semantic artificial intelligence reasoning, using model-order reduction and adaptive sampling to transform raw sensor data into actionable maintenance information.
The platforms will fuse first-principles digital-twin models with maintenance-domain knowledge graphs, shipboard asset information, and contextual mission-specific knowledge graphs. The resulting system must automatically infer and explain emerging fault modes, provide human-readable diagnostics rather than opaque alerts, and isolate faults to the Lowest Replaceable Unit.
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Frequently asked questions
- When is the submission deadline?
- Submissions are due September 23, 2026. Questions must be submitted by September 9, 2026.
- Who issued this RFP?
- It was issued by Department Of War. The work is located in United States.
- Who is a good fit for this opportunity?
- Aerospace and defense technology company with carrier-based aviation systems expertise
- Experience developing digital twins and condition-based maintenance platforms
- Capabilities in edge computing and high-frequency sensor data processing
- Expertise in hybrid physics, semantic AI, model-order reduction, and adaptive sampling
- Knowledge of maintenance-domain and asset knowledge graphs
- Track record delivering explainable diagnostics and fault isolation for complex military platforms
Analysis generated by Settle AI from the source RFP.
RFP Hunter shows what is open. Settle shows what is forming.
Settle pieces together buyer signals, budgets, contract activity, and the sources your team already monitors. See why an opportunity fits and what to do before the RFP posts.