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Reduce carbon footprint and energy-related production costs by an average of 10% for more sustainable manufacturing

Energy Cost Optimization Solutions From SAS

Lower energy usage and cost while maintaining quality and yield with IoT sustainability solutions for manufacturing.

Industrial IoT Product of the Year 2024 award logo

Award

Industrial IoT Product of the Year 2024

The Energy Cost Optimization solution from SAS recently won product of the year, an award that honors the best, most innovative products powering the Industrial Internet of Things. Our award-winning solution helps manufacturers accelerate time to value and provide significant energy cost savings.

How SAS® Helps Lower Energy Usage and Cost

Identify optimum shift parameters

Dynamically compare current and historical production runs and show the drivers of energy consumption.

Minimize energy consumption while maintaining quality

Determine the exact process setpoints to apply by using a set of mathematical optimization solvers.

Improve sustainability efforts

Reduce carbon footprint and help meet ESG requirements.


Why choose SAS for lowering manufacturing energy usage and cost?

Easily gain the insights you need to make setpoint changes fast.

  • IoT data integration. Access, integrate and enrich data from varying sources across your plant, including raw materials, dryers, kilns and weather.
  • Built-in data model. Combine environmental, MES, PLC, SCADA and LIMS data for automated explainers of the process parameters most affecting energy consumption.
  • Prebuilt machine learning models. Easily deploy these models to learn what changes you need to make across the plant with best-in-class analytics.
  • Prebuilt visualizations and dashboards. View data analyses across the organization and enable engineers to take quick, insight-backed actions that result in significant energy savings.

Accelerate time to value with integrated energy modules.

  • Automated explainers. Provide engineers with the missing insights needed to affect key process parameters with a relationship analyzer for energy consumed and process parameters.
  • Golden shift analyzer. Identify optimum shift parameters for each process setting using advanced analytics models to dynamically compare current production runs to historical runs with very low energy consumption.
  • Setpoint analyzer. Gain recommendations for operators on the exact setpoints they should apply to the process to minimize energy consumption while maintaining quality using mathematical optimization solvers.

On-Demand Webinar

Optimizing Energy Use in Manufacturing With AI and Data

Learn how to cut your energy-related production costs by up to 10% and reduce your carbon emissions.

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SAS Energy Cost Optimization

Watch how Wienerberger AG has benefitted from SAS Energy Cost Optimization.

With SAS Energy Cost Optimization, you can reduce energy usage, carbon footprint and CO2 certificate spending while maintaining quality and yield. Take the guesswork out of making improvements – combine and analyze IoT and process data from across the production process, use prebuilt analytic models to predict specific energy consumption and make sense of variable impacts. These capabilities deliver mathematically optimized insights that empower production operators to quickly tune the process recipe setpoints, accelerating time to value and providing an average energy cost savings of 10%.

What Analysts Are Saying

Analyst Report

AI in Manufacturing: Enabling Business-Driven Factory Innovations

Analyst Report

Gartner® Magic Quadrant for Augmented Data Quality Solutions


SAS in Manufacturing – Facts & Figures

2800+

manufacturing customers in more than 52 countries

75%

of manufacturing companies in the Fortune 500 rely on SAS

100%

of subsectors, whether process or discrete


Recommended Resources to Lower Energy Usage & Cost

Solution Brief

Reduce carbon footprint and energy costs for more sustainable manufacturing

Solution Brief

Achieve or exceed product quality targets for higher operating margins

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Wienerberger AG uses SAS to lower energy costs and usage in factories worldwide

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Optimizing energy use in manufacturing with data and AI

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