Maintain and expand APC benefit improvements with patented technology that automatically adapts and optimizes to ever-changing plant conditions.

Learn how Aspen Mtell prescriptive maintenance uses Autonomous Agents to predict equipment failures, detect deviations from normal behavior and prescribe detailed actions to mitigate or solve future problems.

Understand how Aspen Mtell’s Autonomous Agents share failure signatures across similar assets, enabling rapid time to value.

Imagine a plant that is no longer at risk of a random shutdown. Imagine not worrying about losing a year’s worth of hard-fought optimization value in just two to three days due to a maintenance emergency. Through the science of maintenance, historical and real-time operational data combine to predict when a breakdown will occur with months — not just days — of advance notice.

“Automation also can help identify issues before something critical fails. Finding problems as early as possible helps improve asset management,” says CSX Executive Vice President and Chief Operating Officer, Cindy Sanborn. Read this article to learn more about CSX’s exciting project with Mtell, which uses patented machine learning technologies with industrial assets to perform predictive maintenance which no longer runs parts to failure.

When developing its highly successful digital transformation program, a leading European energy company turned to Aspen Mtell® for predictive maintenance. After deploying Aspen Mtell on more than 50 large assets in a refinery, the company began testing the technology at a wind farm and had five early successes in predicting gear box failures.

Prescriptive maintenance technology is transforming how companies increase asset availability. With more advance warning of equipment failures comes more opportunity to mitigate the negative impact of those events.

Data analysis can get bogged down in identifying, selecting, and preparing data. These tasks consume 50% or more of the time spent doing analysis. Now, with Maestro for Aspen Mtell®, you can automate much of that data preparation. Through automated workflows, time and effort is minimized while reducing the skills and experience required by the end users. Maestro also tackles the selection of the hyperparameters that control the machine learning algorithm and automates feature selection to further reduce the need for data science skills. Watch this video to learn how this powerful AI technology can help you build better Agents in a fraction of the time.

Aspen Mtell uses predictive maintenance technology to deliver the earliest, most accurate warning of equipment failures—enabling companies to increase safety, improve asset performance, and reduce emissions.

Increase production by up to 5%, reduce energy usage by 10% and improve yields by 3% with the most profit-hungry engine available for advanced process control.