Asset Performance Management
Combines process information with high frequency vibration to provide asset prediction & prescription.
Modern AI and FMEA
APM 360™ is focused on optimizing the performance of assets to increase reliability and availability, minimize costs, and reduce operational risks. Outcomes include increased asset availability by as much as 5%, reduced reactive maintenance by 10-40% and up to 10% in inventory cost reduction. APM 360™ leverages machine-learning based on artificial intelligence to detect anomalies and take into account complex, dynamic behavioral machinery patterns and contextual data relating to the manufacturing process at large.
Watch An APM 360 Demo
Preview the software with examples as seen by the end user, presented by Sudeep Gowrishankar, SymphonyAI Industrial's Sr Product Manager.
Key Technology Differentiators
- Harnessing of Process and high frequency vibrations to AI models for high fidelity predictions and wide fault coverage
- Unsupervised AI models to detect unknown unknowns and not just known defects based on pattern recognition
- Self-tuning adaptive AI models that self-train based on auto-detection of maintenance events and/or major process changes
- FMEA Engine for cause advisory and actionable recommendations
APM 360™ Key Features
Asset Health Intelligence
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- Asset Health Score for asset and plant
- Asset Performance Degradation
Real-time Asset Monitoring
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- Asset templates for rotating & static equipment
- Predictive Analysis, early detection of asset anomaly
- FMEA Library for cause determination and corrective action
Predictive Maintenance
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- Predictive maintenance advisory
- Maintenance KPI prediction, i.e.: MTBF, MTBM
- Digital twins for What-if analysis – run-time extension, failure prediction
SAAI’s Asset Templates cover major assets:
Rotary Assets:
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- Motors
- Pumps
- Fans
- Blowers
- Compressors
- Turbines
- Engines
Static Assets:
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- Furnaces
- Columns
- Heaters
- Heat Exchangers
APM 360™ User Panel Discussion Videos
Data Driven Decision Making
NRG Energy & Logan Aluminum - 4 Min
ROI & Process Change
Logan Aluminum, Nippon Gases, NRG - 5 Min
AI-based Multivariate Analysis
Nippon Gases - 2 Min
New Technology Challenges
Nippon Gases - 2 Min
New Technology Benefits
Nippon Gases - 2 Min
Avoiding Machine Downtime
Nippon Gases - 2 Min
Early Anomaly Detection
Nippon Gases - 2 Min
Addressing Data Security
University of Tennessee - 2 Min
Bringing End Users Along
Novelis - 2 Min
Better Decisions from Data
University of Tennessee - 2 Min
A View of the Future
Novelis - 2 Min
APM 360™ Architecture
Case Example One: APM for large multi-stage centrifugal compressors
Maximize availability of integrally geared multi-stage centrifugal air compressor in an 3000 tons / hour Ammonia plant by predicting anomalies with cause and mitigation action advisory. Digital twin used blend of unsupervised with supervised ML models – TDA, LSTM encoders, KNN, Decision trees for anomaly detection. Benefit delivered $2M in a year by preventing unplanned outage events.
Case Example Two: Predictive Maintenance of LNG compression train
Minimize unplanned downtime of multi-stage centrifugal fuel gas compressor, gas turbine driven export gas centrifugal compressor, reciprocating boil-off gas compressor trains in a large LNG liquefaction facility by detecting incipient equipment faults & their causes. FMEA-powered blend of unsupervised & semi-supervised ML: TDA, SVM, NN Autoencoder, Random Forest. Benefit delivered over $2M through timely repair recommendations and outage avoidance.
Built on the Eureka AI Industrial Platform
Eureka AI Industrial Platform is the foundation layer of APM 360™. Beyond secure data connectivity, processing and storage, Eureka Industrial Platform provides rich user features such as connectors, analysis, dashboarding, alerts, cases and workflows that are seamlessly integrated into the APM user experience.
EurekaAI Industrial Platform
