Case Study

Control Column Performance Using Aspen HYSYS®

Learn how Tupras used the column analysis capability in Aspen HYSYS and its integration with Aspen Exchanger Design & Rating to significantly increase the column capacity and meet the required product specifications.

Case Study

Controle el desempeño de columnas con un Digital Twin de planta usando Aspen HYSYS®

Conozca cómo Tupras utilizó el análisis de columnas en Aspen HYSYS en conjunto con Aspen Exchanger Design & Rating para incrementar en un 40% la capacidad de columna y al mismo tiempo cumplir con las especificaciones de calidad del producto.

Blog

Making Secure Technology Choices in the Energy Industry

To remain competitive, energy companies increasingly look to artificial intelligence and machine learning to boost their advantage. But AI is everywhere now and everybody knows about its potential... so how do you create a real competitive advantage?

Case Study

Westlake Chemical Improves Reaction Time from Hours to Minutes

Learn how Westlake assesses time sensitive supply chain opportunities, such as accepting a modified customer order, in a matter of minutes using Aspen Plant Scheduler rather than four hours using previous spreadsheet methods.

Case Study

Korea's SK E&C Reduces Engineering Estimating Man-Hours by 50% With Aspen Capital Cost Estimator™

Learn how SK Engineering & Construction improved the speed and accuracy of their capital project cost estimates with Aspen Capital Cost Estimator (ACCE).

Case Study

Saudi Aramco Increases Refinery Capacity by 100,000 Barrels/Day Using Plant Digital Twin

Learn how Saudi Aramco used Aspen HYSYS to analyze feasibility of refinery reconfiguration plans by developing plant digital twins of multiple units. The new reconfiguration plan projects a 100,000 barrels/day increase in the refinery’s processing capacity, a substantial reduction in fuel oil production together with a significant boost in diesel production capacity.

Case Study

Refinery Gets Asset Failure Predictions with Nearly a Month of Lead Time

Because traditional diagnostic methods weren’t preventing equipment failures or identifying root causes of historic failures, a U.S. refinery turned to Aspen Mtell prescriptive maintenance to improve internal data science resources. Download this case study to learn how this refinery's pilot program with Aspen Mtell was able to predict failures with nearly one month of lead time, enabling planning for maintenance and rescheduling production.

Case Study

Global Energy Company Improves Safety and Asset Integrity with Machine Learning

In this case study learn how a global oil and gas company was able to detect and predict a variety of pending equipment failures. Download today to uncover how Aspen Mtell enabled the company to correctly identify all reported events – as well as unknown problems.

Blog

The Importance of Seeing the Whole Picture

Aspen Enterprise Insights™ enables you to visualize data across your enterprise, giving you actionable information to make the best decisions.

Executive Brief

デジタルアクセラレーションが価値創造の新たなフロンティアを切り拓く

資産集約型の業界では、IIoTとデジタル化テクノロジーが収益性と信頼性の向上への道を開きます。このホワイトペーパーでは、これらのテクノロジーを適用して最も大きな影響を得る方法について説明し、デジタルアクセラレーションへの移行に成功するために重要な3つの鍵について概説します。

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