Technology Title
Digital Maintenance Advisor: Prescriptive AI to Operationalize Nondestructive Inspection
Tech Focus Area
CBM+/Predictive Maintenance
Abstract
The Digital Maintenance Advisor (DMA) directly addresses critical sustainment challenges associated with aging Department of War (DoW) aircraft fleets. Inspection results, maintenance history, technical orders, and discrepancy narratives are distributed across disparate systems and are often unstructured or inconsistent. Troubleshooting relies heavily on time consuming manual research and scarce subject matter experts, resulting in extended mean time to repair (MTTR), increased aircraft downtime, and degraded readiness. DMA is a mature, operationally validated solution developed in collaboration with U.S. Air Force maintainers under the SBIR program. It has been demonstrated at multiple bases across various platforms, including the C-5, C-130, F-16 and F-15. The system has achieved an approved Authority to Operate (ATO) on Department of the Air Force networks at Impact Levels 2, 4, and 5, enabling immediate deployment without additional cybersecurity accreditation.
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DMA reduces this gap by accelerating maintenance decision-making and improving execution. Demonstrated results include up to a 30% reduction in troubleshooting time, enabling faster return to mission-capable status and reducing aircraft downtime. By guiding maintainers through optimized workflows, it improves consistency, enhances safety, and reduces dependence on scarce subject matter experts. The capability increases workforce efficiency by enabling less experienced personnel to perform expert-level diagnostics. DMA provides real-time fleet health insights that support data-driven readiness decisions at both operational and enterprise levels. It also utilizes its comprehensive data layer to optimize maintenance scheduling and tasking, avoiding rework, resolving conflicts in support equipment, and closing gaps in work package data. Projected enterprise-level adoption indicates potential annual savings in tens of millions of dollars through reduced downtime and optimized maintenance labor utilization.
DMA’s architecture supports integration with diverse maintenance systems and data environments, enabling broad adoption across air, land, and sea platforms. The underlying approach of integrating inspection data, maintenance records, and technical guidance into a unified decision-support framework addresses common sustainment challenges shared across the joint force, making DMA highly transferable and scalable. It requires no new hardware and integrates into existing maintenance workflows without disrupting current inspection or maintenance processes. Its modular architecture allows for flexible integration with legacy systems while accommodating variations in data quality and availability. Key implementation challenges such as data heterogeneity, legacy record inconsistencies, and maintainer trust in AI recommendations are mitigated through modular data ingestion, explainable AI outputs, and continuous learning mechanisms that improve performance over time.
