SAS Predictive Asset Maintenance helps organizations to accurately predict events that could cause outages and to run their assets at peak performance. The solution uses data integration, automation, analysis and predictive analytics to boost uptime, performance and productivity while lowering maintenance costs and the risk of revenue loss.
Near-real-time monitoring and predictive alerts and models help you avoid major defects, prevent long downtimes and address potential performance issues before they escalate. Workflows and case management speed problem resolution.
Optimize maintenance cycles.
Leading-edge optimization algorithms and solvers let you expand the maintenance cycle without jeopardizing asset uptimes or risking degradations or failures.
Reduce unscheduled maintenance.
Predictive and near-real-time performance alerts allow maintenance teams to fix issues during scheduled outages in a planned, cost-effective way – and choose the optimal time to replace assets.
Improve root-cause analysis.
Award-winning analytics and predictive data mining capabilities drive continuously improved reliability, efficiency and quality – identifying root causes and enabling engineers to troubleshoot and correct performance issues faster and more effectively.
Enhance data visibility.
After capturing large volumes of all types of data – from legacy to modern MES, ERP, CMMS and other systems – the solution transforms, standardizes and cleanses the data to make it accessible to a wide range of users.
- Enterprise maintenance-centric data model.
- Automated monitoring and alerting.
- Predictive modeling.
- Descriptive analysis.
- Reporting and KPI dashboards with drillable alerts and reports.
- Support for asset replacement decisions.