We spoke with Dr. Michael Call of Lubrizol about the three most important things he’s learned about process simulation during his career, and what he’s excited for in the future of batch modeling.

AspenTech and FPCO win 2020 Supply and Demand Chain Executives Green Supply Chain Award. FPCO's reduced CO2 emissions and waste provide sustainable results.

Follow these hints to learn the skills that matter most in your job and discover how to use the latest features in AspenTech software!

Nous entendons beaucoup parler de la "nouvelle normalité" et de ce que cela impliquera, mais le fait est que nous ne savons pas vraiment à quoi ressemblera cette prochaine phase. Elle est encore définie par les conditions sanitaires mondiales, la politique internationale, l'évolution des réglementations et la situation générale de l'économie. C'est une grande incertitude qui nous assaille à grande échelle.

Find out how to create maximum business impact by choosing the method of machine learning that best fits your operation.

Predictive analytics provide alerts to equipment failures weeks or months in advance, so you can manage downtime in a way that makes the most sense for your business.

This article, featured in The Chemical Engineer, discusses why operators often struggle to know where to begin to digitally transform. AspenTech's Paige Morse outlines how many operations, particularly in specialties, have become increasingly complex as customers demand higher levels of performance and quality and a greater range of options from producers. Operators realize they need to diversify product lines to meet these increasingly sophisticated needs. Download this article to learn more.

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

In the Pharma Times article “Working in Silos” AspenTech’s Justin Eames discusses the pitfalls of working in silos in the pharmaceutical industry and explains how AspenTech’s solutions can make an impact at speed using predictive analytics. Discover how to predict asset degradation and failure well in advance of an impending breakdown or disruption and gain the ability to make decisions that can not only minimize cost and disruption, but that can also protect public health by ensuring continuity and resulting quality of drug supply.

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.