The 2015 Paris Agreement and other international climate change accords have helped raise global awareness of the need for countries to take urgent action to combat climate change. As companies continue to focus on sustainability, a common theme is taking shape around the role of digitalization as a key enabler. In fact, a recent ARC Advisory Group survey revealed that 75% of respondents rated digital transformation as highly important for achieving sustainability goals.

For food and beverage companies, quality mishaps during production can mean more than a literal poor taste in a customer's mouth. In addition to the potential impact on consumer safety, quality lapses can slow down production and result in money down the drain.

Predictive technologies are taking the mining world by storm, providing new insights to help companies avoid dangerous situations and costly mistakes.

As energy companies shift to a new normal due to the pandemic, the energy transition continues to gain strong momentum. Industry leaders are focused on meeting aggressive sustainability targets and are making investments in digitalization to accelerate innovation.

Industrial organizations are sitting on a decades-old, massive double-edged sword: their data. Until now.

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.

This article (published in PTQ Magazine) describes how the on-line coordination and optimisation of refinery process units led to a 10% increase in middle distillate production without investing in process units or equipment.

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.

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.

Digital technologies offer significant opportunity for improved quality and cost savings across the chemicals industry by enabling more efficient design, operation, and maintenance of assets throughout their lifecycle. However, many chemical companies are still in the early stages of understanding how such opportunities can be applied effectively to their business. This article highlights how top companies are using data to drive business and operational decisions, and are progressing with their own transformation to the next level of performance and operational excellence.