SAS® Field Quality Analytics Features

Data management

  • Standard, extensible data model.
  • Multiple databases supported, including SAP HANA.

Early-warning analytics

  • Automatically determines analytically driven critical values.
  • Enables entry of manual thresholds for safety and regulatory issues.
  • Simultaneously monitors changes across production period, usage and event period.
  • Generates automated alerts and notifies relevant issue owners.
  • Attach comments so current status is easily ascertained.
  • Drill into alerts to conduct further analysis.

Issue analysis & prioritization

  • Ad hoc warranty analysis, including Pareto charts, control charts, exposure charts, reliability analysis, decision trees and sequence analysis.
    • Drill into results to conduct further analysis.
    • Review raw event data.
  • Advanced analysis with hundreds of analyses and charting options, including descriptive analysis, table analysis, ANOVA, regression, multivariate, survival analysis, capability analysis, control charts and graphs.

Integrated text analysis

  • Analytic models to recognize patterns in text.
  • Ability to identify similar comments.
  • Word search that includes synonyms, misspellings and other related words.

Easy reporting capabilities

  • Project-oriented interface for creating both simple and complex reports:
    • Workflow mirrors the warranty analysis processes.
    • Powerful filters for easily subsetting and combining data.
    • Group analyses by project.
  • Report library:
    • Searchable repository of information.
    • Content can include special studies, documents posted by users and automatically generated standard reports.

Seamless integration with the full SAS® Quality Analytic Suite, including SAS® Asset Performance Analytics & SAS® Production Quality Analytics

  • Integrated analysis across the quality spectrum. Follow the root-cause path from field data through the production process and the heavy assets that manufacture your products.
  • Ability to deploy models to identify issues before they make it to the field.
  • SAS Event Stream Processing to monitor data in real time and alert as issues occur.

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