EQUA AIMMS: Governed AI from Fault Detection to Verified Return to Service

CBM+

Problem Statement: A detected fault is not a restored asset. DoW maintainers must still convert alarms, field observations, technical guidance, safety requirements, parts availability, work orders, supplier actions, and approvals into a completed, verified repair. When that work is fragmented across people and systems, MTTR, non-wrench time, expert dependence, cost, and readiness risk increase.

Description of the Innovation Solution: EQUA AIMMS is a governed AI system that handles the digital work from fault detection to verified return to service. AIMMS monitors deviations, anomalies, and alarms; maintainers can also speak to it or show it a problem through images or live video. It grounds diagnosis and prescriptive actions in approved manuals, SOPs, asset history, and operational data. AIMMS advances the event through repair procedures, safety steps, work orders, parts and alternatives, inventory and supplier paths, RFQs/procurement, approvals, verification, closeout, and audit records. Instead of stopping at condition monitoring or troubleshooting, AIMMS carries downstream digital work forward while maintainers retain authority over consequential actions. It integrates with existing maintenance, enterprise, inventory, procurement, document, and SCADA/historian systems rather than replacing systems of record, and never autonomously writes to operational controls.

Benefits to the DoW: AIMMS turns maintenance intelligence into completed action. It reduces digital handoffs, non-wrench work, reliance on scarce experts, and execution variability while increasing maintainer capacity and accelerating safe return to service. Each completed event creates an auditable record that preserves institutional knowledge. The same architecture supports a practical cross-service path for common industrial and support equipment across depots, installations, shipyards, air bases, logistics facilities, and DLA operations.

Innovation Challenges: The primary transition challenges are heterogeneous legacy data and trusted AI use in safety-critical maintenance. AIMMS addresses both through modular integration, source-grounded outputs, role-based permissions, human approval gates, audit trails, tenant isolation, encryption, and no autonomous OT control. The next step is controlled DoW validation on representative equipment and completion of environment-specific authorization requirements.

Technical Maturity / Demonstration Results: AIMMS is commercially operational in three industrial/manufacturing organizations, with a fourth wastewater deployment entering implementation in September 2026. One live deployment spans 150 mission-critical industrial assets. Operational results include a 31.7% reduction in MTTR, a supplier quote cycle reduced from approximately three days to under one hour, and approximately 50% lower safety-risk exposure. AIMMS is ready for controlled DoW evaluation and transition.