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.

Energy reduction plays a key role in meeting aggressive sustainability goals. Learn how BPCL deployed an Aspen HYSYS®-based online digital twin of the amine regeneration unit (ARU) supporting the Aspen DMC3™-based (APC) system enabling them to:

More than 1/3 of the world’s population now resides in India and China. As both countries grow, the pressures mount on infrastructure, resources, workforce and environmental sustainability.

Optimal heat exchanger design software is vital for the efficient operation of any process plant. The integration between heat exchanger design and rating software, Aspen EDR, and the process simulators Aspen HYSYS® or Aspen Plus® enables engineers to design heat exchangers best suited to their processes. View this webinar to learn best practices on designing heat exchangers.

Robust heat exchangers designed and delivered on time and on budget are vital for the success of engineering projects. AspenTech offers an integrated design workflow that supports every major type of heat exchanger. The seamless integration between its solutions for process design and the thermal and mechanical design of heat exchangers reduces design time. Learn more about heat exchanger design software.

Heat exchangers can comprise up to 30% of capital equipment and impact 90% of the energy used in a process plant.

Utility providers are facing a period of intense change as the world makes its way through the energy transition. For companies with the vision and determination to take advantage of the opportunity, distributed energy resource management systems (DERMS) offer not only a solution to challenges, but also a pathway to significant value.

Seismic data can provide useful information for prospect identification and reservoir characterization. Combining seismic attributes helps identify different patterns, thus improving geological characterization. Machine learning applied to seismic interpretation is very useful in assisting with data classification limitations.

AspenTech colleagues and members of the Black Leadership Forum share a few insights on the importance of recognizing and celebrating Juneteenth