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.