A major transportation company responsible for delivering customer goods on time, safely and reliably, was plagued by catastrophic failures of locomotives that had gone undetected by its current reliability techniques. Using Aspen Mtell to examine data from engine lube oil samples, a leading U.S. railway was able to save millions of dollars.

IOT Evolution-In Digital Transformation Operational Excellence is the Real Prize April 2018

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

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.

See how Aspen Mtell prescriptive maintenance prevents catastrophic diesel engine failures.

In this interview with ARC Advisory Group analyst Peter Reynolds, AspenTech President and CEO Antonio Pietri describes how the process industries are leveraging new technologies—including cloud computing, data analytics, and machine learning—to drive greater value from their assets.

Have questions about optimizing your batch processes? This FAQ addresses the most common inquiries about the powerful batch modeling technology of Aspen Plus.

Industrial Automation Asia - Manufacturing excellence in specialty chemicals

BLOWDOWN Technology, developed by Dr. Graham Saville and Professor Stephen Richardson of Imperial College London, is now available in Aspen HYSYS, creating the optimal tool for completing depressurization projects. Join technical experts from AspenTech and BLOWDOWN Technology consultants to discover how this technology can ensure the accurate design of depressurization systems that’s vital for safe operations.

Aspen HYSYS has been updated and improved with additional features over the last few years. From concurrent engineering to integrated gas plant modeling and refinery-wide modeling to streamlined process safety analysis, experience the latest innovations in chemical process simulation. This checklist shows the addition of features and incremental improvements by version.