Green hydrogen plays an increasingly important role in meeting decarbonization and energy transition targets. As electrolyzer technology rapidly advances as part of a green hydrogen solution, it’s vital that engineers capture these process enhancements to meet design targets and optimize performance.

Industrial data from a variety of sources and locations has the potential to help organizations meet energy efficiency goals, avoid raw materials/feedstock shortages, decrease downtime, increase profitability and improve ESG reporting. But the chemical industry, like other asset-intensive industries, generates large amounts of data that never gets collected, contextualized and used to its full potential.

The successful execution of engineering projects requires intense collaboration among multi-discipline teams, but manual data handoffs often lead to errors, inconsistencies and delays that can derail a project.

To chemical and polymer manufacturers, achieving site optimization and resiliency to disruptions is key to meeting the world's ever-changing demand. Take a deep dive look into the flywheel effect of how Advanced Process Control (APC) and Scheduling synergies takes manufacturing sites to another level of performance and resilience. Leverage both of these crucial layers together to multiply the benefits of each other.

Watch this webinar on Aspen InfoPlus.21® (IP.21) from AspenTech, exploring the potential of contextualizing historical data to transform your business.

The environment in which pipelines must operate is changing rapidly and dramatically, as constant shifts in the global marketplace have underscored a need for increasing flexibility.

Aspen Mtell introduces exciting new features, including Alert Manager, industry-specific asset templates, custom models (BYOM) and intuitive dashboards and KPIs for improved visibility, health insights and recommended actions. This infographic provides a comprehensive overview of the capabilities now available in Aspen Mtell.

Aspen Mtell® combines the power of data and technology to enable reliability and maintenance engineers to monitor the performance of assets, providing real-time visibility into asset health and actionable insights for faster decision-making. Discover why companies like LG Chem, Evolution Mining, OCP Ecuador and others have opted for AspenTech´s prescriptive maintenance solution to improve their operational efficiency and achieve carbon mitigation and sustainability goals.

AspenTech provides over 140 easy-to-use application models that you can adapt to your own initiatives, along with the supporting documentation to help you get started. Models cover areas such as bio-based feedstocks, carbon capture, emissions management, hydrogen economy, materials circularity and more.

A recent study conducted by ARC Advisory Group analyzed how leading manufacturing companies are leveraging artificial intelligence (AI) and machine learning tools to improve asset performance. While condition-based maintenance is most prevalent, the study found that leaders have successfully built AI capabilities to enhance asset performance practices through in-house platforms, commercial solutions and a combination of both.