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Minimize costly downtime and drive consistent performance with predictive maintenance solutions

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.
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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.

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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%.

Recommended Resources for Predictive Maintenance

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Blog

Why Accurate Predictive Maintenance Requires Digital Twins

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White Paper

The Next Big Leap in Asset Management Comes With Predictive Maintenance at Scale

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Webinar

Predictive Maintenance: A More Proactive and ROI-Driven Business Model