Closed-Loop Fault Mitigation
Closed-loop IT and OT asset monitoring that goes well beyond fault detection.
Why It’s Important
Existing IT and OT asset monitoring solutions are limited to fault detection and notification. Other critical routines (impact assessment, root-cause analysis, and corrective action identification) require triage and action(s) that occur external to the asset management solution. Existing shortcomings of these open-ended solutions include:
Delayed impact assessment
Lack of insights required to quickly determine the overall impact (breadth and depth) of an asset malfunction results in ineffective reaction.
Faulty root cause identification
Misidentification of root cause results in delayed fixes, excessive downtimes, and costly consumption of resources.
Ineffective corrective actions
Lack of AI-enabled analysis of historical data and the inability to run trial fix simulations inhibits the ability to rapidly identify and implement the required corrective action.
How We Do It
MicroAI closes the loop by bringing lightweight edge and endpoint AI technologies to the entire asset monitoring ecosystem. In addition to fault detection and notification, MicroAI closes the fault detection loop by providing AI-enabled capabilities to the areas of:
Impact assessment
that provides intelligence-based analytics on probable fault impact on asset (machine, network, etc.) performance as well as predictive overall impact to operations and customers.
Live root-cause assessment
via automated, AI-enabled, analysis of recent asset performance, historical fault analytics, and rapid execution of fault simulation models.
Accurate corrective action identification and execution
via simulation of various corrective measure to predict the most effective course of action and intelligent workflows that automate implementation.
What It Delivers
MicroAI’s closed-loop fault mitigation provides operations with the means to respond to asset faults more quickly, more accurately, and more cost-effectively.
MicroAI closes the loop by bringing edge and endpoint AI to the entire ecosystem. Benefits include:
- Real-time impact assessment
- AI-enabled root-cause analysis
- Quicker corrective action identification & implementation
- Reduced cost of failure
- Less strain on resources
- Faster time to recovery
