C. Norton
Qualtech Systems Inc, Connecticut, United States
Keywords: Prognostics and Health Management, Artificial Intelligence, Digital Twin, Autonomous Maintenance, Condition Based Maintenance PLUS
Qualtech Systems, Inc. (QSI) has developed an AI-enabled digital twin solution that improves the health management, maintenance, and readiness of mission-critical defense systems. Built on QSI's proven TEAMS® platform, the technology combines causal digital twin models, model-based diagnostic reasoning, machine learning prognostics, and real-time operational data to create a continuously updated representation of system health. The solution addresses major defense sustainment challenges, including increasing system complexity, workforce shortages, rising lifecycle costs, and the need for predictive maintenance. Unlike purely data-driven approaches, QSI's digital twins encode system structure, functionality, and failure propagation logic, enabling explainable fault diagnosis and root-cause isolation even when historical failure data is limited. AI-enhanced prognostic capabilities can provide Remaining Useful Life (RUL) estimates and failure forecasts, supporting proactive maintenance planning and logistics readiness. By translating diagnostic and prognostic insights into actionable maintenance recommendations, guided troubleshooting, and mission-impact assessments, the platform reduces downtime, improves system availability, and lowers maintenance burden. The technology is applicable across naval, aerospace, autonomous, manufacturing, and depot environments. QSI's roadmap advances from anomaly detection and diagnosis to prediction, prescription, and ultimately autonomous sustainment, supporting Department of Defense priorities for Condition-Based Maintenance Plus (CBM+), predictive logistics, and digital engineering adoption.