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.

Create process models on a solid foundation. Start your modeling efforts with confidence with the most up-to-date and comprehensive portfolio of physical property data.

View this infographic to see how prescriptive maintenance early adopters are reducing downtime and improving reliability – with results in as little as 2 ½ weeks.

Traditional preventive maintenance alone cannot solve the problems of unexpected breakdowns. With asset performance management powered by low-touch machine learning, it’s now possible to extract value from decades of process, asset and maintenance data to optimize asset performance. In this white paper, learn how this disruptive technology deploys precise failure pattern recognition with very high accuracy to predict equipment breakdowns months in advance and advise on prescriptive maintenance. The paper also outlines five best practices for driving state-of-the-art reliability management to increase production and profitability.

Mining companies invest heavily in equipment for all stages of mining, mineral processing, refining and distribution. By monitoring asset condition and behavior and developing profiles of normal operations, anomalies and failures, predictive maintenance tools can notify staff of equipment problems prior to failure. This paper outlines how predictive maintenance provides mining organizations the intelligence needed to:

Licensors of proprietary processes need to respond to requests for proposals, quickly with accurate and sharp bids.  Driving down costs through project design re-use allows timely bids that drive down the costs of CAPEX. aspenONE Engineering's integrated design platform using modular templates allows proven design reuse and speeds time to bid completion. Watch now to learn more.

Learn how Qenos, an Austrailian ethylene manufacturer, used Aspen DMC3 to revamp a demethaniser controller with very limited resources and achieved a 5-10% increase in cold end throughput, a 40% reduction in variability in overhead methane, and a 20% reduction in tower dP.

As part of an effort to drive reliability in its refinery operations, Saras turned to Aspen Mtell® prescriptive maintenance to improve equipment uptime and decrease maintenance costs.

The evolution of IIoT and advanced analytics technologies is transforming how industrial companies of all sizes manage their critical assets. In this report, ARC Advisory Group describes how AspenTech Asset Performance Management delivers prescriptive maintenance solutions to process and other capital-intensive industries.