Predictive Maintenance From SAS
Discover how predictive maintenance solutions powered by SAS Analytics for IoT can identify and prescribe actions to minimize unplanned costs, operations disruptions and safety hazards.
How SAS maximizes asset performance with predictive maintenance
Anticipate issues before they arise
Detect and diagnose issues faster to prescribe what actions to take.
Forecast asset life into the future
Improve reliability by forecasting remaining useful life to determine when something is likely to fail.
Plan for the future
Mitigate risk and predict future needs with a holistic view and optimized maintenance suggestions.
Why choose SAS for predictive maintenance?
Gain a holistic view of your operations
- Analyze IT and OT data sources. Our solution unifies all your data in one solution to make decisions about critical infrastructures and operations.
- Leverage accelerators to access and explore data. Using the AI of Things (AIoT) sensor-focused data model, get started quickly and easily to access and explore data
- Easily explore high volumes of data. SAS makes it easy to find deeper insights in your data using the language of your choice and open data formats on one platform.
Take advantage of SAS expertise and flexible deployment
- Deploy the solution anywhere. Our predictive maintenance solution can be deployed on-premises, in the cloud of your choice or at the edge.
- Scale to support thousands of analytics models. The enterprise-ready technology grows with your operations to support your long-term analytics goals.
- Gain a partner experienced in manufacturing. For five decades, SAS has solved analytics challenges, from streamlining operations to optimizing supply chains to forecasting.
Featured Offering
SAS Analytics for IoT
Read how Georgia-Pacific has benefited from predictive maintenance solutions.
With SAS Analytics for IoT, Georgia-Pacific enhanced plant production operability, increased yield and created a safer environment for workers. Using SAS Analytics for IoT combined with automated machine learning (AutoML) for IoT, which is a solution accelerator, Georgia-Pacific taps into its on-site historian, open source investments and subject matter experts to dramatically scale up the operationalization of analytics. This strategic approach has reduced unplanned downtime by 30%.
