While biotherapeutics is one of the fastest growing sectors in life sciences today, the tech transfer process still takes many years. Regulatory approval can be time consuming—from conducting clinical trials to achieving a validated process design.

Carbon capture utilization and storage (CCUS) is an essential pathway to meet net zero emissions targets. However, for capital-intensive industries to reach these commitments, it’s critical that companies have confidence in the efficient, widespread deployment of carbon capture projects worldwide.

현재 많은 기업들이 디지털 트윈을 활용하기 위해 노력하고 있습니다. 공정 산업에서 디지털 트윈을 구축하려면 실제 플랜트 운전 상황의 변화를 실시간으로 정확하게 시뮬레이션 할 수 있어야 합니다. 이번 웨비나는 Aspen Plus의 EO (Equation-Oriented) 모델링이 플랜트의 운전과 시뮬레이션을 실시간으로 일치시키는 방법에 대해 알아보겠습니다.

With an increased focus on climate change and energy transition, companies are pivoting to more sustainable operations raising questions such as:

Operations in the process industries are challenging due to the inherent complexities and lack of insights. Plant digital twin technology helps solve these challenges. Learn how Burns & McDonnell developed and deployed a plant digital twin of a refinery’s FCC unit using rigorous process simulation to:

As the hydrogen economy continues to gain momentum, organizations are looking for faster, more efficient ways to design and deploy hydrogen projects. Growing pressure to meet sustainability targets is only increasing the demand to make these initiatives both viable and profitable.

Join Hydrocarbon Processing Editor-in-Chief/Associate Publisher Lee Nichols for a lively discussion with industry experts Heath Stephens, Engineering Leader, Hargrove; Gerald Delaney, Process Engineering Manager, Zachry Group; and Paul Donnelly, EPC Industry Director, AspenTech, on these timely, relevant topics:

本セッションでは、ACCEにおけるコストパラメータのキャリブレーション方法について紹介します。ACCEを使用することにより、最新のコストデータ、設備のコストカーブ、標準P&IDに基づき、確度の高い見積りを迅速に簡単に得ることが可能となり、意思決定までのリードタイムの短縮化が可能となります。 また、ACCEのデフォルトのパラメータを調整（キャリブレーション）することにより、プロジェクト固有の条件を反映したコスト調整を行える他、コスト積算業務の作業負荷及び時間を50%削減することができます。

大型组织将在2050年之前率先实现温室气体净零排放，这使得今天的化工企业面临越来越大的压力，他们必须采用能源效率解决方案和加快循环经济创新来确保可持续地运营。

Aspen Data Science Studio™とAspen IoT Analytics Suite™を組み合わせてAspen Industrial AI Workbenchを作成し、すぐに使用できる分析ライブラリ、AI開発コラボレーションツールを作る方法をご紹介します。これらと組み込みのMES統合は、ドメインエキスパートやデータサイエンティストがデータが豊富なAIアプリを開発するのに役立ちます。