The MODE (Maintenance Optimization Diagnostic Ecosystem) platform harnesses the power of the Digital Risk Twin to enable real-time system monitoring and predictive maintenance optimization, boosting operational availability and driving down lifecycle costs for complex, mission-critical assets.

Through the integration of high-fidelity data with causation-based AI in tools such as Syndrome Diagnostics, MODE transforms maintenance strategies and significantly reduces Total Cost of Ownership (TCO). This model-based, intelligent solution includes a suite of interoperable tools purpose-built to deliver actionable insights, streamline diagnostics, and support proactive, data-driven decision-making.

Causation-based Failure Detection and Isolation (FDI) tool. SD utilizes the MADE Digital Risk Twin where it extracts all the 'Syndromes of Failure' of the system of interest.

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An intelligent failure reporting solution that speeds up the reporting process and Increases the accuracy of operational data capture by maintainers.

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AoAI uses the Digital Risk Twin to optimize real-time maintenance decisions, including opportunistic maintenance, prioritization, effectiveness assessment, and fleet availability optimization.​

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autonomous FRACAS will provide an automated process to address systemic failures in the system. Based on the DRT, relevant analyses and data is used to identify, justify and track corrective actions.​

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