Reactors are critical for any refinery, impacting both quality and yield of products. With the emergence of bio-feed and co-feed processing reactors, new challenges arise as operators are unfamiliar with feed streams, creating operational risks.

AspenTech® has introduced a new way to interact with APC controllers to evaluate real-time operating scenarios and provide actionable guidance with a 24x7 virtual advisor. Additional innovations include workflow improvements and synergies to empower users to further optimize APC technology.

The future of the upstream industry lies in the adoption of innovative geoscience digitalization solutions to optimize operations. Machine learning applications for geoscience data have been in use for more than 25 years but have recently become critical due to massive growth in the amount of petrotechnical data being acquired. As machine learning evolves, it will play an increasingly visible role in analyzing surface and subsurface data.

AspenTech's Ron Beck uncovers key areas within supply chain to understand technology’s role in energy transition.

With mounting pressure to reduce carbon emissions—and still meet critical production targets—today’s energy and chemical companies are challenged to stay on top of changing operating conditions and respond in a timely, efficient and coordinated manner.

In today's complex and ever-changing technological landscape, integration between Information Technology (IT) and Operational Technology (OT) is not just a buzzword; it's a necessity.

Machine learning technology can now predict equipment failures weeks in advance. But how do you decide when and how to perform the repair to maximize productivity and minimize risk? Learn how Aspen Mtell and Aspen Fidelis enable you to quickly evaluate hundreds of possible future scenarios, and understand the financial consequences and risk involved in different operational decisions.

For decades, first principle models have been used for process design and optimization in the chemical industry. Recent innovations employ machine learning techniques—enriched with first principle constraints—to create a hybrid model that closely represents real plant behavior. Fast, easy access to industrial AI is helping organizations make accurate decisions to select an optimum design quickly and improve operations, maximizing productivity and minimizing energy usage.

With more focus on sustainability, frequent changes in global gas markets and evolving processing technologies, gas plants are always looking to improve operations by accurately simulating and predicting increasingly complex processes.

See how AspenTech DataWorks is improving our best-in-class data management solutions with new capabilities and synergies.