Technology such as virtual sensors and online models can help operators optimize returns from their older assets.

Machine learning, big data and analytics are disrupting the upstream industry — and creating opportunities to achieve sustained operational excellence.

Are you exploring all avenues to enhance operational productivity, efficiency and safety at your plant? Download this article to learn how Statoil introduced one standard solution for storing and presenting process data to achieve cost savings and simplification.

Rob Brooks of Axiall talks about the benefits of a1PE.

In a challenging economic environment, where can executives look for relief? Asset reliability and maintenance are becoming key value drivers, thanks to big data technologies, analytics and machine learning.

Increase visibility and responsiveness to batch production problems through monitoring of important business metrics via dashboards, alerts and pattern matching.

Improve operational performance with real-time visualization to increase visibility, agility and responsive to production problems with batch performance management.

This article appeared in the 2018 American Fuel & Petrochemical Manufacturers (AFPM) Conference Daily (Oct 2018) that highlighted the Operational Planning, Control and Automation Technologies session during which Chevron talked about the closed-loop, real-time coordination of a refinery middle distillate system, the benefits and key takeaways.

It is critical for combined cycle power plants to control costs and increase efficiency. In order to accomplish these goals, these plants must make every effort to avoid costly shutdowns, including implementing the newest innovative technologies. This white paper details how combined cycle power plants can leverage the lessons learned from other industries to capture more value from capital equipment, thereby improving operations overall.

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.