The COVID-19 pandemic has caused acute disruptions the world over. The energy sector, in particular, has been severely impacted raising questions like:

The impact of COVID-19 has accelerated digitalisation for the process industry. In this exclusive interview with Pipeline Oil & Gas News, Antonio Pietri, President and CEO of AspenTech®, discusses how this acceleration of digitalisation will lead to the creation of a Self-Optimizing Plant.

In this Pharmaceutical podcast, host Dave Howell from Process Industry Informer discusses with AspenTech's Lawrence Clark, VP and Richard Porter, Director, the latest technologies and future insights for the process manufacturing industries.

Learn how Borealis, a leading provider of innovative solutions in the fields of polyolefins, base chemicals and fertilizers, implemented Aspen PIMS-AO to support the optimization team and bring about better decision-making for more profitable results. This case study explores how Borealis achieved dramatically faster run time, employed nonlinear modeling, deployed planning models to a centralized, virtual environment, and eased software deployment time and maintenance with more efficient use of hardware.

En este vídeo, descubra cómo el mantenimiento predictivo de Aspen Mtell permite a LUKOIL tomar decisiones más rápido y aumentar la confiabilidad en toda la empresa.

In this podcast, Lee Nichols, Editor-in-Chief of Hydrocarbon Processing and Ron Beck, Marketing Strategy Director at Aspentech discuss HPI's digital transformation journey, the future of the self-optimizing plant and how digital technologies will lead to more efficient operations.

Dynamic simulations have many applications. Learn how to create dynamic models in Aspen HYSYS or Aspen Plus Dynamics.

We all want the inside story. Column hydraulic analysis offers engineers a view into column performance to improve design and operational efficiency.

Prescriptive analytics based on machine learning and multivariate analysis are enabling power plants to optimize equipment life and extend their outage intervals. Free yourself from the recommended schedules of OEMs and service providers!

최근의 구조적 인력 이동과 전례없는 시장 변동성에 비추어 볼 때, 기업들은 산업용 AI 애플리케이션에서 비즈니스 성과를 도출할 수 있는 기능들을 더욱 필요로 합니다. 산업용 AI는 오퍼레이셔널 엑셀런스를 이끄는 원동력으로서, 경쟁 우위를 유지하는 데에 필요한 새로운 비즈니스 모델로의 성공적인 전환을 지원할 것입니다.