aspenONE Advanced Process Control (APC) V10 contains new functionality that keeps models accurate across the entire operating range. Additionally, Smart Tune has been enhanced to provide more flexibility, and improvements were made in Aspen DMC3 Builder™ to further simplify project workflow.

During this webinar, Tami and David will walk you through all the exciting new features of the Aspen Plus family of products, including the newest feature – Column Hydraulics. This interactive tool helps new and experienced engineers troubleshoot operational issues with enhanced calculations and visualizations.

Leveraging process modeling tools is vital for accelerating the journey to market for new products, or for optimizing the margins of existing processes. Often, a single tool does not have the capabilities to model entire specialty and fine chemicals processes due to their complexities (batch or mixed batch/continuous, integrated fluid and solid sections, complex reactive systems). As a result, specialty and fine chemicals companies often rely almost exclusively on expensive experimentation and plant trials when innovating their products and processes. View this webinar to learn from AspenTech experts about best practices for end-to-end batch modeling in Aspen Plus.

在瞬息万变的市场环境下，石化企业在管理业务和规划未来面临着巨大的挑战。 使用数字化会使企业保持敏捷性，是实现和保持盈利能力的战略要务。在网络研讨会时，我们的AspenTech专家，王峰，将讨论中国石化行业的前景以及数字化如何使石化企业保持领先地位。

El tiempo de inactividad no planificado tiene un amplio impacto que afecta no solamente a la productividad y la rentabilidad de una planta sino también a la seguridad del personal y de la planta, así como a las emisiones de gases de efecto invernadero y al cumplimiento al medio ambiente. Pero, ¿qué pasaría si realmente se pudiera planificar el tiempo de inactividad? En este documento, conozca cómo los avances en machine learning y el análisis predictivo están eliminando que haya tiempo de inactividad no planificado que sea desconcertante.

As market conditions remain unpredictable, refineries turn to digital strategies to improve agility and stay competitive. Digital twin technology provides valuable insight into operations, enabling companies to run safely, effectively and with maximum margins.

Chemical manufacturing operations provide a huge amount of process data generated in real time. This data is a wealth of information and can provide insight into better operational decision-making when tied to process modeling. Our webinar is designed for both process engineers and operators seeking to improve their distillation column performance.

You’ve heard of Prescriptive Maintenance (RxM), but how can you leverage it to drive real value in your organization? In this on-demand webinar, AspenTech’s Ryan Conger demonstrates how data-driven insights from AI and machine learning mitigate maintenance issues and improve productivity. Through a series of case studies, Ryan shows how Prescriptive Maintenance is being used to:

Aspen Polymersを活用しフリーラジカル共重合モデルを構築できます。実験データから反応速度パラメータを回帰し、バッチ/連続重合シミュレーションでポリマー物性を予測します。 モデルを活用することで、実験回数の削減、バッチサイクルの短縮検討が可能となります。

現実プラントで測定できるプロセスの値は、連続プラントにおいても常に変動しているため、Aspen PlusやHYSYSのシミュレーションの挙動と一致させるのは容易ではありません。このセッションでは、シミュレーションの挙動を現実プラントと一致させるためのPlant Data機能 (プラントヒストリアンからのタグデータインポート、データコンディショニング、定常状態判定など)についてご紹介します。Plant Data機能は、プロセス性能の経時的なモニタリングにも活用でき、例えば長期的に変動する熱交換器の汚れや反応器の触媒活性のモニタリングに役立ちます。