AlertX
Tired of overwhelming alarms? AlertX filters the noise. AlertX’s intelligent monitoring catches equipment anomalies such as gradual drifts, short spikes, and abnormal trends in real-time by tracking live process data using AI/ML algorithms for rotating equipment and process units across refineries, petrochemical plants, and power facilities. This platform has capability to scan thousands of equipment tags and catches performance deviations in critical assets. Most plants struggle with reactive maintenance and generic alarms. AlertX addresses this with intelligent filtering, contextual alerts, and engineer-tunable thresholds. It enables early fault detection in compressors, heat exchangers, and reactors—minimizing unplanned shutdowns, improving safety, and driving predictive maintenance at scale.
Salient Features
Differentiation
The chemical and process industries have traditionally relied on powerful historian and analytics platforms like OSIsoft PI System, Aspen InfoPlus.21 (IP.21), TrendMiner, Seeq, and Honeywell Uniformance for monitoring asset performance and detecting anomalies. While these platforms offer broad capabilities across data aggregation, visualization, and analytics, they often require complex setups and intensive configuration.
AlertX differentiates itself by offering a specialized, process engineer-friendly solution laser-focused on real-time deviation detection, intelligent prioritization, and flexible fine-tuning by process experts.
Unlike general-purpose analytics tools, AlertX provides rapid deployment, minimal complexity, and actionable insights that directly empower engineers to drive proactive troubleshooting and operational excellence. Unlike traditional systems that generate overwhelming alarms, AlertX intelligently filters and prioritizes actionable insights, helping engineers focus on what matters most.
Client Benefits
60% Fewer Unplanned Downtimes
Detect faults early using AI-based anomaly detection across 1000+ tags and variables.
90% Reduction in False Alarms
Advanced noise filtering and prioritization reduce alert fatigue and improve focus on critical issues.
70% Faster Fault Detection
Enable quicker issue identification with contextual alarm grouping and sensitivity tuning
24/7 Autonomous Monitoring
AI/ML continuously tracks plant behavior—even beyond human attention spans.
$1M+ Annual Maintenance Savings
Prevent equipment failures and optimize preventive maintenance schedules.
Dashboard & Snapshots
Use Cases
Example Use Case: Refrigeration Compressor Deviation Tracking in an Ethylene Plant
Case 01: Ethylene Compressor Stage One Suction Temperature Deviation
- Deviation Detected: 1st Stage Suction Temperature at -139.5°F
- Observations:
- First Stage Flow increased to ~145 KLBH
- Heat Exchanger (Chiller) exceeded its permissible heat duty
- Conclusion:
Load hike is affecting 1st Stage compressor operation
Case 02: Ethylene Compressor Stage Four Discharge Temperature Deviation
- Deviation Detected: 4th Stage Discharge Temperature at 111.5°F
- Observations:
- Fourth Stage Temperature rose just above ~110°F.
- Heat Exchanger HE-168 breached permissible load, highlighted in red.
- Conclusion:
Temperature rise is impacting 4th Stage compressor operation. Possibility of load shifting of exchanger to reduce the load on 4th stage can be evaluated.
Case 03: Propylene Compressor Stage Four Discharge Temperature Deviation
- Deviation Detected: 4th Stage Discharge Temperature at 152.4°F
- Observations:
- Fourth Stage Temperature slightly exceeded ~150°F.
- Heat Exchanger HE-130 exceeded design heat duty.
- Conclusion:
High temperature is stressing 4th Stage compressor operation. Load shifting of exchanger can be evaluated to reduce load on 4th Stage.
