Watch how Aspen Mtell analyzed 220 million sensor values to identify the top 10 maintenance cost failures at one world-class refinery, and predicted a compressor breakdown 49 days in advance.

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

Learn how Aspen Mtell connects big data and prescriptive maintenance to deliver IIoT solutions.

What if all your data could easily provide strategic insights to your users across your entire enterprise? That's Aspen Enterprise insights, the first hybrid cloud visualization and workflow management solution that brings new levels of performance to operations and capital projects.

A customer case study of the use of Aspen HYSYS, PSV in Aspen HYSYS, dynamic modeling and flare to achieve lower CAPEX solutions and rapidly conduct safety studies for refining.

Over the past 40 years, maintenance best practices have greatly improved, but equipment continues to break down. So how can asset reliability be improved? With Aspen Mtell prescriptive maintenance software, you can predict breakdowns weeks in advance and take action to protect your machines, business investments, the environment, and most importantly, people.

Maintaining optimal inventory levels to achieve outstanding customer service sounds simple enough, but the timing of customer shipments can have a huge impact on plant storage tank inventory levels.

In just a few minutes, a scheduler can simulate the addition of a last minute customer order, determine its impact, and modify the production schedule to resolve any issues and fulfill last minute orders using Aspen Plant Scheduler.

Waymon Lofton, Mike Monteith and Harvey Welker provide compelling testimonials about how AspenTech is driving innovation across the estimating lifecycle.

Column Analytics gives one "X-ray vision" to see what is going on in a column to prevent process abuse and notify the operator of needed process changes before the column goes down due to flooding.