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Rockwell Automation Improves the Quality of Life

Accelerating Digital Transformation

See how Rockwell Automation is using Ansys simulation software to optimize the smart devices that are the help to control, optimize, and automate modern manufacturing processes. The company, which has partnered with Ansys for more than 20 years, pairs Ansys simulation with their industrial automation solutions to enable engineers and industrial companies to more productively design, deploy, test, and maintain their industrial operations. 

“We’re really putting technology and tools in the hands of engineers to help them be more productive. Simulation tools can help build a digital twin of a system and project performance where companies can look at actual performance versus simulated performance of a system to identify bottlenecks and areas for improvement.”

Tessa Myers,
Senior Vice President of Intelligent Devices at Rockwell Automation

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Ansys Deploy Your Digital Twin

Deploy Your Digital Twin as a Runtime in Rockwell Automation’s Studio 5000 Simulation Interface

See how Rockwell Automation’s Studio 5000 Simulation Interface connects to Ansys Twin Builder, enabling engineering teams to implement simulation-based digital twins by unlocking an extensive range of insights that can improve system design, performance, and maintenance of your assets in operation.

An engineer monitors job progress on a digital display

The Industrial Internet of Things (IIoT)

Learn how the Industrial Internet of Things (IIoT) creates enormous opportunities for business growth. It connects devices across a wide spectrum of industrial equipment and assets in industries like manufacturing, metal and mining, energy production, processing, transportation, and end use applications.

Future concept

Transform Your Operations With Data-Driven and Simulation-Based Digital Twin Software

See how digital twins can be used in real-time systems analysis to schedule predictive maintenance and implement performance optimizations. Engineers can reach an unparalleled level of accuracy using predictive analytics by combining machine learning (ML)-based analytics with a physics-based approach.