IoT Global Network - Big Data Mining

AspenTech Named 2022 Middle Market Leader

Energy and Chemical companies continue to look for new ways to reduce their carbon footprint and remain profitable. Advancements in digital optimization technology are helping industry leaders navigate the energy transition, meet sustainability goals and optimize operations. Learn how companies like Marathon Petroleum, Samref and CEPSA are using Unified Production Optimization to lower CO2 emissions, reduce energy intensity, maximize margins and much more!

Aspen Technology Achieves AWS Energy Competency Status

Los datos generados durante el diseño conceptual y FEED se están volviendo cada vez más importantes desde un punto de vista estratégico. Desde la comprensión de las emisiones y el uso de energía hasta una comprensión más completa del diseño y los costos del proyecto, los propietarios y sus empresas de ingeniería están poniendo más énfasis en la comprensión temprana de las opciones de diseño. Pero con la complejidad de los proyectos de diseño, el desarrollo de información que es tan importante a menudo puede ser lento, ineficiente y propenso a errores. Lo que se necesita es un proceso colaborativo más integral, respaldado por herramientas digitales que ayuden a fomentar una creciente sabiduría colectiva sobre el proyecto, a través de disciplinas y partes.

Companies in capital-intensive industries are facing a dual challenge—meeting the growing demand for resources and higher standards of living from a growing population while also addressing sustainability goals. And to succeed they will require new levels of operational excellence.

AutomationWorld - Pharmaceutical Industry Applies Artificial Intelligence

Hydrogen is an essential yet often limited resource for refiners, with demand increasing due to processing of renewable feedstocks. In addition, hydrogen production is very expensive, particularly with the recent rise in natural gas prices and the significant, costly CO2 emissions it generates. Now more than ever before, refiners need an effective way to manage the hydrogen supply-and-demand balance.

As it relates to asset reliability, Failure Modes and Effect Analysis (FMEA) is a process to identify potential failures in a system as well as their causes and effects. By combining predictive maintenance technology with FMEA tools, companies can associate causation with known failures and their suggested FMEA remedies – leading to earlier intervention, minimized equipment damage, fewer process interruptions and improved production yields.

In this case study, learn how Corteva Agriscience, an American agricultural chemical and seed company, resolved their frequent reboiler shutdowns by using Aspen Hybrid Models™. By combining plant data and AI within an Aspen Plus® model, Corteva improved the heat transfer and duty predictions to provide guidance for a better maintenance strategy.