SAS Asset Performance Analytics Features List
Enterprise, maintenance-centric data model
- Measurement data provided in both continuous and categorical measures for sensor and tag data, events and alarms.
- Asset and equipment data.
- Physical failure analysis data.
- Failure data.
- Inspection records.
- Maintenance records.
- Environmental data.
- Organizational data.
- Textual information from any source.
Automated monitoring & alerting
- Drill down by organization.
- Drill down by asset group.
- Drill down by functional area.
- Execute workflow.
Predictive modeling
- Decision trees.
- Neural networks.
- Regression analysis.
- Clustering.
- Scoring.
- Stability monitoring:
- Automatically builds prediction models based on user-selectable predictors.
- Models can be scheduled for continuous scoring.
Descriptive analysis
- Pattern analysis.
- Correlation analysis.
- Regression analysis.
- Asset analysis:
- Flexible framework to support any stored process(es) in the user interface.
- Handles user interactions.
- Surfaces and manages outputs.
- Persists status between sessions.
- Supports independent as well as dependent stored processes.
- Facility integrity and reliability delivered as "blueprint" (specific to the oil and gas industry).
Reporting & KPI dashboards with drillable alerts & reports
- Interactive KPI dashboard.
- Interactive web-based reports.
- Interactive web-based graphs.
Support for asset replacement decisions
- Uses historical data.
- Allows manual intervention.
- Includes scenario analysis.
Seamless integration with the full SAS Quality Analytic Suite
- Common code base and data model simplify enterprisewide operational improvements and allow a modular approach to adding analytic capability as the organization matures.