Case Study

Análisis estadístico multivariable encuentra la causa de un problema de alta viscosidad en el aceite de enfriamiento

Una de las empresas más grandes a nivel mundial para productos químicos, plásticos y de refinación utilizó Aspen ProMV para entender y resolver sus problemas de producción causado por un problema de alta viscosidad en el aceite de enfriamiento. En este caso de estudio conozca cómo Aspen ProMV permitió a la empresa a destacar las principales variables de proceso que están altamente correlacionadas con problemas de viscosidad y que guio rápidamente a los ingenieros de proceso al problema subyacente para limitar las pérdidas.

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

Japanese Pharmaceutical Company Improves Quality with Aspen Plus<sup>®</sup>

A 140-year-old global pharmaceutical company with headquarters in Japan adopted Aspen Plus to improve the synthesis of a new active pharmaceutical ingredient (API). Aspen Plus provided an in-depth understanding of a new API process leading to equipment improvements and optimized recipes that enabled development of a continuous process.

Case Study

UK Refinery Increases Middle Distillate Production with Aspen GDOT™

Download this case study to learn how a refinery in the UK used Aspen GDOT to increase middle distillate production by 10%. The closed loop optimization technology, adjusts multiple process units in real-time to maintain product consistency and improve overall refinery performance. Discover how you can drive more profitable operations with Aspen GDOT.

Case Study

Refinery Optimizes Middle Distillate System in Real Time with Aspen GDOT™

Learn how one of world’s largest multinational energy companies used Aspen GDOT to maximize production of specific diesel and jet fuel products at one of its refineries. By using real-time optimization across multiple APC units, the refinery was able to decrease sulfur giveaway by 70%. Download this case study to learn how you can optimize production and reduce product giveaway.

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.

Case Study

Data-Driven Maintenance Planning Saves $1.8 Million USD Per Year in Shutdown Costs

A global provider of knowledge-based maintenance, modifications and asset integrity services wanted to take a more data-driven approach to planned maintenance and reduce unplanned downtime to optimize lifecycle costs.

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

Optimización de la producción en transporte e instalaciones de producción de gas natural con una solución integral de ingeniería

Aprenda cómo YPFB Andina aumentó su producción de gas utilizando una solución de modelo integrado que proporcionó un aumento en las ganancias por $ 280 millones en 1 año.

Case Study

Two Looming Failures Stopped Within Two Weeks of Monitoring

Executives at this mining company were looking for a new approach to proactively handle reliability issues for critical equipment.

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