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。

This article, featured in The Chemical Engineer, discusses why operators often struggle to know where to begin to digitally transform. AspenTech's Paige Morse outlines how many operations, particularly in specialties, have become increasingly complex as customers demand higher levels of performance and quality and a greater range of options from producers. Operators realize they need to diversify product lines to meet these increasingly sophisticated needs. Download this article to learn more.

After an electrical storm stopped gas production at one of its plants, SABIC executives and reliability engineers turned to Aspen Fidelis Reliability to calculate the probability of it—or a similarly debilitating event—happening again. Read this article from Plant Services to learn more.

Sustainability is emerging as a critical business topic, as companies focus resources toward lowering emissions, waste and energy use in their production process. In this article, Paige Morse, Chemicals Industry Marketing Director, shares how sustainability affects four key areas within a processing plant and how digital transformation supports sustainability efforts through efficiency improvements.

“We have been able to generate a lot of value at our plants: minimizing changeovers, reducing inventory because of a better sequence plan, and gaining better visibility” – William Duty, Director of Momentive’s Supply Chain Center of Excellence

To be a leading 'player' today's specialty chemicals environment, overcoming these challenges is crucial to staying competitive and ensuring the entire supply chain is optimized.

See how you can use Aspen Technology solutions to develop a refinery wide process model that would enable refinery process engineers to evaluate the economic impact of operational changes and help planners achieve a more accurate assessment of profit margins.

In this article, Robert Golightly explains the limitations of traditional maintenance practices and how new advancements in predictive maintenance are pushing assets and equipment to the limits of performance. Learn how today's industry leaders are using low-touch machine learning to extract value from design and operations data to predict when and where failures will occur.

To achieve operational excellence, process manufacturers must quickly and systematically address the root causes of asset reliability problems, which include inadequate operating procedures, poor design, and improper scheduling of production.

To achieve operational excellence, process manufacturers must quickly and systematically address the root causes of asset reliability problems, which include inadequate operating procedures, poor design, and improper scheduling of production.