BHC3TM Reliability provides reliability engineers, maintenance managers, and executives with comprehensive monitoring across critical and non-critical assets, and enables proactive, AI-based predictive maintenance. BHC3 Reliability identifies anomalous behavior across systems and assets, provides prioritized alerts, recommends prescriptive actions, and enables collaboration through an integrated workflow. With BHC3 Reliability, enterprises can maximize uptime, reduce maintenance costs, and improve operational efficiency.
Reduce unplanned downtime, maximize asset availability, and increase safety
BHC3 Reliability demo video
Demonstrated Benefits
Next Generation AI-based Reliability
Issues
BHC3 Reliability Solution
Reactive, time-based, and expensive maintenance programs
AI-based asset risk predictions provide continuous visibility into overall asset health
Too many false alerts generated by rules-based systems
Early warnings for assets at risk are prioritized using machine learning and codified domain expertise
Difficult to track asset risks across thousands of systems and sensors
AI approach is scalable across complex assets, fleets, and systems
Operational knowledge siloed within an aging workforce
Automatic failure mode identification to prescribe mitigation steps and feedback loops augmented by AI
Disparate and unconnected reliability systems
Closed-loop workflow for all asset, maintenance, and operational systems
Key Capabilities
AI-based asset risk predictions
- Proactively assess real-time asset health, detect anomalies in asset operating conditions, and perform root cause analysis.
- Contextualize asset and system behavior with thousands of features.
- Prioritize maintenance activities for planned maintenance windows based on failure predictions.
Prioritized early warnings
- Identify anomalies using next-generation deep learning and machine learning algorithms.
- Prioritize issues and reduce the number of false alerts through AI/ML.
- Early warning of asset risks months ahead of time.
Scalable AI approach
- Scale application rapidly across any type of facility or asset fleet.
- Automated diagram parsing map sensors to assets and generate asset hierarchies.
- ML model management & configuration provide end-to-end management to end users.
Failure mode identification and mitigation
- Leverage AI/ML interpretability to explain factors contributing to asset risks.
- Identify failure modes using codified domain expertise with cross-industry diagnostic libraries.
- Prescribe remediation actions to guide engineers in rapid risk resolution.
Closed-loop workflows
- Streamline workflows across software tools by launching work orders in existing CMMS systems
- Collaborate across the organization with operator, engineer, and manager views
- Tune the machine learning models to accommodate operations complexity
Benefits for BHC3 Reliability Users
