In this case study, learn how Braskem Idesa used Aspen ProMV™ to proactively identify and correct for conditions that historically led to high reactor fouling.

Saras拥有地中海最复杂的炼油厂，每天的炼油产能为30万桶。作为数字化项目的一部分，他们正在评估如何提高资本和资产密集型炼油厂运营的可靠性。他们选择了AspenMtell，基于一个竞争性试点项目选择过程，最初的重点集中在关键炼油设备上，比如大型压缩机和水泵。 Aspen Mtell通过挖掘历史和实时操作以及维护数据来发现资产性能下降和故障发生之前的精确特征，预测未来故障并制定详细的行动以缓解或解决问题。

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.

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.

If you’re like most food and beverage process manufacturers, it could take you weeks or months to sift through and interpret all your data. In an industry where quality and precision is everything, delays can result in unplanned downtime, defective batches, product recalls and cost overruns—all with the potential to negatively impact your company’s reputation and bottom line.

Discover how predictive maintenance and planned downtime can deliver positive results for your company when it comes to Safety, Sustainability and Productivity.

Descubra cómo un fabricante de termoplásticos de ingeniería descubrió la causa raíz de fallas recurrentes en sus calderas de tubos y calderas utilizando el mantenimiento prescriptivo de Aspen Mtell.

In production environments, changing conditions means increased risk. Operating companies have been shouldering more of this risk in recent years as insurance coverage becomes less readily available.

Lea cómo esta compañía minera utilizó Aspen Mtell para predecir dos posibles fallas cuando se implementó en 12 activos durante un breve piloto en línea. Permitiendo así, un tiempo de inactividad planificado de equipos críticos, ahorrando dinero por cortes inesperados.

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