Chemical and energy companies continue to look for an edge to achieve their critical sustainability goals. Advancements in online digital twin technology now provide valuable, real-time insights to help you further reduce emissions and ensure regulatory compliance across your entire site. In this on-demand webinar AspenTech and Equinox Software Services discuss the value created by an emission-monitoring digital twin with robust KPI reporting.

Enter the era of autonomy and take the first steps to the self-optimizing plant – a self-learning, self-adapting and self-sustaining operation driven by industrial AI that will start your industrial metaverse journey and help you thrive in any market condition. Watch this video to learn how you can start realizing this vision today.

The concept of digital twins has been around since 1960s, but the term was first introduced nearly a decade ago by NASA's John Vickers. Until very recently, adoption of digital twins has been fairly inconsistent but acceptance looks to be accelerating with recent market shifts. Today’s users are seeing exponential benefits by deploying multiple digital twins across sites. The next wave of digitalization innovations, powered by digital twins and AI, is creating new levels of agility and flexibility, paving the way to autonomous operations.

Our employee resource groups (ERGs) serve as part of AspenTech’s ongoing and evolving efforts for a diverse, equitable and inclusive work environment and culture.

In recent decades, energy and chemical companies have benefited from digital technologies to increase the efficiency of hydrogen (H2) processes while ensuring safe and economical production, storage and transportation. Today, digitalization is increasingly crucial as hydrogen systems grow in complexity, utilizing green power sources and getting deployed at a larger scale.

The Aspen SKUA Fault Seal Analysis Workflow contains powerful tools for rigorously evaluating the sealing capacity of faults and fractures in the reservoir.

Aspen Big Loop™ is an open ecosystem for setting up automated, reproducible and auditable subsurface workflows. The workflows help propagate uncertainties and capture their dependencies while calibrating reservoir models to observed data. The result is reliable probabilistic predictions.

As the process industries face the challenge of digitally transforming their plants and assets, they need tools and technology to support this change. Integrating the use of process simulation, operator training systems (OTS) and digital twin technology is an essential first step on this journey.

See how digital twin technology and Industrial AI provide real-time insights on system performance, helping to optimize operations and reduce costs with recommendations to maximize uptime.

Start your journey to the self-optimizing plant and view this interactive e-book that highlights how your assets can be safer, more reliable, more flexible and more profitable with the help of Industrial AI.