Developing automated 3D models during pre-FEED and FEED can drive down material costs, enhance asset visualization and help identify an optimal design early, minimizing revisions in later engineering phases.

Learn how Generative AI within Aspen OptiPlant 3D Layout™ automatically produces multiple 3D layout options for a carbon capture plant within minutes instead of weeks.

Learn how a multinational energy company that was looking to improve integration and collaboration between engineers and disciplines across different locations, implemented Aspen Basic Engineering™(ABE).

Reactors are critical for any refinery, impacting both quality and yield of products. With the emergence of bio-feed and co-feed processing reactors, new challenges arise as operators are unfamiliar with feed streams, creating operational risks.

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Digitalization solutions offer significant efficiency improvements to existing assets as well as the planning and design capabilities to prepare for new technologies.

As sustainability targets drive the energy industry towards a net zero future and energy security concerns intensify, companies are challenged to meet these competing demands within financial and workforce restraints. Owners and EPCs must cater to short-term energy demands while simultaneously positioning themselves for the long-term energy transition projects gaining traction.

The release of aspenONE® V14 can help customers achieve new levels of efficiencies while accelerating progress toward Net Zero goals, harnessing the innovations needed to address the Dual Challenge.

The data generated during conceptual design and FEED are quickly becoming more strategic. From understanding emissions and energy use to layout and project costs, owners and their engineering firms are placing more emphasis on early design choices.

To remain competitive, companies must develop new levels of operational excellence, gaining agility, flexibility and insight via digitalization.