AspenTech's Integrated Solutions for Energy Management and Asset Optimization at BPCL's Mumbai Refinery

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.

It’s time to embrace low-touch machine learning, a disruptive technology that uses real asset data to provide months of advanced notice on failures.

Many new improvements have been made to Batch Modeling technology in Aspen Plus, including the integration of the technology previously available with Aspen Batch Modeler and the introduction of new unit operations, including batch crystallization. This document covers our answers to some of the most commonly asked questions about this technology.

Como supervisor de operaciones de facilidades de los campos de San Alberto y San Antonio, de YPFB Andina. Marco tiene mucha experiencia con Aspen HYSYS y explica por qué los simuladores de procesos son tan importantes para los ingenieros químicos.