Advances in the application of artificial intelligence (AI) are starting to have a significant impact on automation technologies used across industry—most notably with machine vision and analytics. And some of the more impactful applications of AI are happening in the pharmaceutical industries. Learn more in this article from Automation World.

This report, which was co-written with Robert Socolow, Professor Emeritus, Princeton University, addresses the findings of a recent survey conducted to better understand the strategies and actions taken by industry leaders as they plan for a sustainable future.

In this case study, discover how Sardeolica used prescriptive maintenance to achieve maximum value and expects to reduce maintenance costs up to 10 percent per year.

Pharma companies continue to strive for tight control of critical quality attributes (CQAs). When Ferring Pharmaceuticals wanted to move from batch to continuous manufacturing, they found that laboratory assays were too time consuming to provide meaningful feedback for real-time control, and 100% product quality inspection was not possible.

Warnings and alerts are not new in the industrial world as some predictive alerts can provide months of warning of catastrophic events. The challenge is how to prioritize and respond to these predictive alerts in a more systematic manner that benefits all areas of an organization.

The ability of bio-pharmaceutical manufacturers to deliver quality drug products during challenging market conditions is critical for ensuring sustainability over the long run. The COVID-19 pandemic underscored the need to transform the traditional bio-pharmaceutical supply chain to have greater agility and resiliency during market swings and periods of volatility.

As energy, chemical and EPC companies continue to adjust to a new normal, the focus on meeting sustainability goals is a top priority for industry leaders. Digitalization and AI are critical in helping companies advance their sustainability efforts. View this video and learn how Industrial AI combines machine learning with deep industry knowledge to help you make faster, smarter decisions that reduce emissions and waste, moving you closer to net zero carbon.

AspenTech is proud to be exhibiting at the ISPE Annual Meeting & Expo in Boston, October 31 -November 4. We look forward to hearing where you are in your digital transformation journey.

During the webinar, Indian refining company, Bharat Petroleum Corporation Limited (BPCL) shared how they gained up to $0.5/bbl of crude by deploying real-time digital twins to optimize its CDU operations with Aspen HYSYS and BPMARRK, BPCL’s patented technology for real-time crude assaying.

Leading asset-intensive companies are using prescriptive maintenance—powered by AI and machine learning—to unlock the value and productivity lying uncaptured in assets. Using a scalable, easy to implement prescriptive maintenance solution, companies can improve the accuracy of failure detection, increase the advance notification period of asset downtime events and reduce maintenance spend.