The DoD recognizes the benefits of resilient, flexible, and responsive sustainment strategies. FTL strives to support these needs by providing essential, targeted applications designed to make inspections and maintenance operations faster, more accurate and effective, and more traceable.
FTL projects address aircraft maintenance involving mechanical systems, fuel and oil quality, and manufacturing or maintenance FOD inspections. These applications can also be applied to ships or other high value assets. Our flaw prediction algorithms can be applied to additive manufacturing processes and structure inspections.
FTL’s DADTMA addresses life cycle sustainment needs at aircraft depots by providing a platform for rapidly ingesting data and digitizing that data in a digital twin database for reporting and comparison across similar aircraft and within repeat maintenance events for the same aircraft.
Similarly, FTL’s SDARIT, automates pier and bridge inspection by detecting and cataloging inventory and damage from 3D point clouds.
While additive manufacturing systems, especially metal, bring revolutionary capabilities and have the potential to reduce supply chain issues and enable new designs through unique layer-by-layer fabrication capabilities, defects such as porosity, inclusions, large-scale voids, and chemical inconsistencies can inhibit the functional performance of a part and reduce confidence in designing parts for AM.
FTL developed “DADTMA”, Distributed Acquisition Digital Twin Maintenance Architecture, is a software solution for accelerating data acquisition and management of maintenance data in the field and for analyzing maintenance and inspection data for a specific aircraft or fleet over time in a Digital Twin framework.
This contamination detection system was developed to identify and analyze fluid-fluid interactions in critical aerospace systems. Using advanced sensors and automated diagnostics, it enables early detection of cross-contamination events to prevent system failure and ensure mission continuity.
FODHAT was developed in collaboration with Northrop Grumman, and uses neural network-enhanced 2D and 3D imaging for autonomous inspection guidance during manufacturing.
FTL’s “FRAMER” (Fast Reconstruction of Architectural Models from Existing Resources) system has been developed for the Chemical and Biological Defense (CBD) program of the DoD. It combines specially trained neural networks with advanced 3D processing algorithms and intelligent data exports to enable high quality building model generation from both blueprints and photographs, and parameter exports for accurate transport and dispersion simulation.
OilEye is a real-time fuel monitoring system developed to detect contamination and performance issues in military aircraft. It combines sensor data with predictive analytics to enhance maintenance efficiency and reduce the risk of in-flight engine failures.
SDARIT (Structural Damage and Repair Inferencing Tool), is an automated inventory, inspection, and repair planning software tool for condition monitoring of assets such as piers, bridges, roads, tunnels, dams, and other structures. SDARIT employs custom AI algorithms for detecting and identifying structural elements and damage caused by wear, seismic effects, fatigue, battle damage, and other environmental factors.
FTL Labs’ SHR3DR (Sub-Seafloor High Resolution 3D Reconstruction) is a
hardware and software solution for the automatic detection of problems such as voids forming in the subterranean environments beneath Navy waterfront facilities.
FTL developed “TRAIDMA”, Transit Reliability and AI-Driven Maintenance Architecture, as a predictive maintenance software platform built upon its proven DADTMA fleet maintenance tool. TRAIDMA enables transit agencies and fleet operators to optimize maintenance activity by leveraging advanced predictive modeling and intuitive data visualization.
VAME (Virtual Assessment and Modeling Environment) is a simulation platform designed to support digital twin development for defense systems. It enables virtual prototyping, behavioral analysis, and performance optimization across a range of operational scenarios.
