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.

When developing its highly successful digital transformation program, a leading European energy company turned to Aspen Mtell® for predictive maintenance. After deploying Aspen Mtell on more than 50 large assets in a refinery, the company began testing the technology at a wind farm and had five early successes in predicting gear box failures.

日本に本社を置き、創業から140年の歴史を誇るグローバル製薬会社がAspen Plusを導入して新規原薬（API）の合成を改善しました。同社は、創薬に重点を置きながら医薬品や医療機器の研究開発から製造、販売まで行っています。

Descargue este caso de estudio para conocer cómo una refinería en el Reino Unido utilizó Aspen GDOT para incrementar su producción de destilados medios en un 10%. La tecnología de lazo cerrado se ajusta automáticamente a múltiples unidades de proceso con base en condiciones cambiantes para mantener la consistencia del producto y mejorar el desempeño global de la refinería. Descubra cómo puede hacer que sus operaciones sean más rentables al utilizar Aspen GDOT.

A global pulp and paper manufacturer set out to predict risk and improve capacity using the power of automation.

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.

Aprenda cómo una de las compañías de energía multinacionales más grandes del mundo uso Aspen GDOT en una de sus refinerías para maximizar la producción de diésel especifico y de jet. Al usar optimización en tiempo real a través múltiples unidades de APC, la refinería fue capaz de reducir en un 70% el regalo de azufre. Descargue este caso de estudio para conocer cómo puede optimizar su producción y reducir el regalo de calidad de su producto.

Shell’s Manufacturing Margin Optimization team uses AspenTech solutions to optimize its energy and petrochemicals business, including planning and scheduling applications. In a highly collaborative global project with AspenTech, Shell successfully deployed Aspen PIMS-AO in the Cloud resulting in margin uplift, improved work-life balance and reduced IT costs. Read this case study to learn how you can improve margins with Aspen PIMS-AO in the Cloud.

Shell’s Manufacturing Margin Optimization team uses AspenTech solutions to optimize its energy and petrochemicals business, including planning and scheduling applications. In a highly collaborative global project with AspenTech, Shell successfully deployed Aspen PIMS-AO in the Cloud resulting in margin uplift, improved work-life balance and reduced IT costs. Read this case study to learn how you can improve margins with Aspen PIMS-AO in the Cloud.

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.