Introduction—the challenge of maintaining a global defense asset base
The current US military asset fleet includes not only 14K-15K aircraft across all service branches (ranging in age from the very newest F-35s to legacy platforms like the C-130 and B-52), but also hundreds of vessel types for the US Navy and armored/ground vehicles for the Army and Marine Corps.
Mission capable rates for many US military aircraft have been in steady decline for nearly a decade. The USAF readiness reached its lowest level in a decade in fiscal 2024, 67% across the entire fleet. With an average platform age of 32 years, improving on these results will be a significant challenge without implementing new maintenance processes and technologies, particularly given the escalating maintenance cadence required for older aircraft and the increasing difficulty of finding replacement parts.
Navy and Marine Corps aircraft have somewhat better overall performance levels, with the readiness rate for the F-18 fleet currently meeting the services’ stated goal of 80%. And the Navy’s surface fleet readiness has, as well, hovered in the high 60’s in recent years, suggesting significant operational improvement opportunity for these multi-billion-dollar platforms.
Driving these outcomes is not only the extraordinary breadth of the military’s platforms and the difficulties of global, frequently contested, operations, but also the shortage in fully qualified technicians and the challenges associated with operating a global logistics and supply chain, adversely affecting readiness rates both domestically and in forward locations.
DMA’s capabilities expand the performance envelope
To meet the challenge of delivering high readiness rates, whether it’s for the USAF’s F-16 and C-17 fleets, the Navy’s surface vessels, or the Army and Marine Corp’s ground and air assets, defense maintenance teams require every tool available to keep platforms performing optimally, and artificial intelligence (AI) is at the top of that list of tools. AI’s unique ability to ingest and analyze vast quantities of real-time performance data, evaluate that data for incipient problems, and make targeted maintenance recommendations enables maintainers to have confidence in the readiness of the fleet when they are called upon to deploy to forward locations.
The Digital Maintenance Advisor (DMA) solution built upon Avathon’s Autonomy Platform is a modular, scalable, AI-powered virtual maintenance assistant that empowers improved performance across a wide range of military platforms, ensuring that technicians have access to the information and materials they need to effectively deliver the mission readiness services demand.
Integration of the full range of data sources ensures effective outcomes
Using natural language processing (NLP), DMA integrates data from diverse, structured and unstructured sources like maintenance logs, operating manuals, tech orders, and project job guides to provide a high-quality assessment of the root causes of problems, appropriate maintenance actions, and the remaining useful life of systems. This integration includes, as well, a scheduling component that coordinates current work with other pending maintenance, e.g., coming depot time.
By giving maintenance and repair personnel access to the widest possible breadth of information on a single platform and with a single search, maintenance intervals are greatly reduced, and outcomes made more efficient and effective. This not only facilitates the optimization of work schedules, it also empowers available resources to maximize aircraft availability. By directly linking maintenance processes to supply chains and forward inventory management, readiness becomes a holistic process, with all needed information at the fingertips of maintainers. By establishing relationships across the full range of documents and resources, repair work is accomplished quickly, and fleet availability levels are optimized.
Predictive/prescriptive maintenance keeps assets in the fight
By analyzing vast quantities of sensor data (e.g., vibration, temperature, flow rates, and current draw) in real-time, DMA accurately predicts when a system or component is likely to fail, often long before a technician can detect the issue. This allows for timely, proactive maintenance, preventing unexpected breakdowns that can disable mission-critical assets. By accurately predicting component failure and providing action recommendations, AI systems enable maintainers to schedule work precisely when it’s needed, rather than adhering to rigid, time-based schedules, while also recognizing the importance of effectively integrating non-scheduled, non-routine repairs with scheduled maintenance programs.
By identifying and addressing issues early, AI extends the operating life of critical, expensive components and, in turn, the assets themselves. Proactive repairs prevent minor issues from escalating into expensive, catastrophic failures. AI-driven predictive maintenance significantly reduces maintenance and labor costs by automating time-consuming steps, avoiding over-maintenance (replacing functional parts too early), or costly emergency repairs. This improves system readiness and reduces Mean Time to Repair (MTTR), particularly for technicians with less experience, upskilling these individuals and capturing tribal knowledge for future use.
Augmenting DMA’s ability to efficiently and effectively maintain defense assets, more effective inspections can also be accomplished using Avathon’s Visual AI tools with camera-equipped drones and computer vision systems to autonomously inspect aircraft/vessel/vehicle surfaces for defects like corrosion, dents, or paint issues.
And early detection of potential mechanical or system failures dramatically reduces the risk of emergencies or catastrophic events at sea, on the ground, or in the air, ensuring the safety of crews and maintenance personnel.
AI-enabled logistics ensures that parts are where they’re needed
DMA analyzes usage patterns, failure rates, and mission schedules to forecast the precise need for spare parts, ensuring that components, tools, and technicians are where they need to be when they need to be there. This proactive approach minimizes the cost of maintaining a large, potentially redundant inventory while ensuring the right parts are available when repairs are needed.
DMA better manages global inventories, autonomously determining if parts are available, how many are in stock, and where they are located. The system also autonomously manages inventory levels to avoid stock-out situations and place replacement orders when needed to ensure part availability. These capabilities ensure timely repairs and avoid the need to cannibalize parts from other aircraft, vessels, or vehicles.
In addition, as defense platforms age, parts inevitably age as well, with many achieving obsolescence and requiring updated replacements. DMA supports planners in this challenge by highlighting high-risk parts/components and planning alternative courses of action as they become increasingly obsolete.
Conclusion—AI empowers defense asset effectiveness
There are three times when defense asset maintenance can be performed: too soon, too late, or just in time. Too soon means you’ve wasted time and money on unnecessary work, replacing parts that still retain useful life. Too late and things may progress to the point of catastrophic failure, increasing cost and risk to crews and maintenance personnel. But just in time maintenance optimizes cost, part/technician availability, and mission readiness.
The Digital Maintenance Advisor capabilities provided by Avathon’s Autonomy Platform expand defense asset management processes from just post-mission, operator-reported problems to more proactive maintenance based on history, sustainment, and depot-level work. So, it’s no longer reactive maintenance, but proactive and autonomous based on platform history, manufacturer recommendations, and mission requirements.
DMA provides a commercially proven, prescriptive maintenance capability set that addresses the pressing issues presented by complex military assets and the challenge of extracting maximum performance from maintenance personnel and processes. By streamlining workflows and eliminating inefficiencies in current maintenance processes, DMA reduces the time maintainers spend locating tools, tech orders, and subject matter experts, while also feeding diagnostic and outcome data back into the system to capture knowledge and improve AI models’ ability to provide better insights over time.
The impact of AI-powered capabilities like DMA for military asset maintenance increases the speed, reliability, and cost-effectiveness of operating complex military systems, enabling a high operating tempo in contested environments, and ensuring mission readiness.
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