Anomaly Detection
- AI models to identify anomalous behavior in the asset
- Identify key contributing parameters viz. process as well as mechanical that cause the anomaly
- Minimal false positives and false negatives result in accurate anomaly detection and alerts
- Alerts tracked and reported at an asset or component level
Root Cause Analysis using Generative AI
- AI Agents that understand the symptoms and assist in identifying root cause of the issue
- FMEA, maintenance history and client’s documents based Generative AI models for accurate failure mode/ cause analysis
- Identify component level cause(s) to fix the root cause
Forecasting Models
- AI/ ML models to accurately forecast Time to Failure of the asset
- Forecast remaining time to fail helps operator and technician to take appropriate action to manage the repair or failure of equipment
- Track at the asset level and component level
What-If Analysis and Recommendations
- GenAI based Conversational interface for What-If analysis and perform parameter adjustments to operate asset for longer time and prolong its life
- Generative AI based actionable recommendations to fix the issue
- Integrated into work order management system
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