To achieve operational excellence, process manufacturers must quickly and systematically address the root causes of asset reliability problems, which include inadequate operating procedures, poor design, and improper scheduling of production.

Today, refineries face the difficult challenge of maintaining and improving their gross refinery margin while meeting increasingly stringent emissions regulations. Refineries need to work in anticipation of new evolving emission regulations. Learn how BPCL Kochi refinery used Aspen HYSYS to develop a real-time refinery-wide digital twin for emissions monitoring enabling them to:

A major European refiner implemented Aspen Technology’s reformer inferred property package for control and optimization of their catalytic reformer in two of its refineries. Download this article to learn more about the company's methodology of execution and the benefits derived.

Download this article featured in engineering.com to learn how the partnership between AspenTech and Hexagon PPM will bring value to customers who are digitizing their engineering workflows.

This “getting started” guide covers the process of creating a new case for Acid Gas Cleaning, setting up component lists and fluid packages, and working in the simulation environment to build the model. It is not meant to be a standalone reference document. Knowledge of Aspen HYSYS V10 is assumed for this guide.

The era of the intelligent mine is here and the maintenance department of the future will use insight to improve its decision-making ability based on data.

Activated Dynamics enables users to easily transition from steady-state models to dynamic models to better address costly compressor upset and failure. This guide will walk you through the process of using Activated Dynamics to get started with dynamics modeling compressor performance.

In this article, AspenTech's Paige Marie Morse delves into how digital-transformation technologies can help industrial organizations cut energy costs while reducing environmental impact. Download now to discover how AI and machine-learning technology combined can enable companies to predict asset malfunctions well in advance and have positive financial and sustainable results.

In this guide, you will be introduced to the tools in BLOWDOWN that can be used to perform staggered blowdown analysis. You will configure a simple analysis by using the Staggered Analysis tool, as well as a rigorous analysis using the Multi-Vessel Template.

Real-time condition-based monitoring of assets is an attractive solution for mining companies to minimize their unscheduled downtime and improve reliability of critical equipment. The success of an asset monitoring program depends on how well this data is analyzed, filtered and categorized to enable accurate predictions of impending failures. Focusing on the behavior of an asset only tells a small portion of the story. To fully predict failures, the trends of the entire process must be considered as a whole.