Refining and petrochemicals producers face increased pressure to maximize margins while improving safety and sustainability. In this on-demand webinar, learn how Pan American Energy implemented a predictive maintenance solution powered by artificial intelligence to predict critical equipment failures – giving time back to production and reducing operational risk.

Accurately predicting the performance of complex, integrated facilities has been an ongoing challenge for capital-intensive industries. However, new innovations in digital technology are helping companies dramatically reduce costs, improve performance and increase revenues. Join industry leaders Covestro and Wood as they share their experiences with reliability modeling software at sites around the world. Hear about their challenges and successes in simulating a range of design and operational scenarios to drive smarter decision making across the organization.

¿Sabía que hasta el 73% de los datos dentro de una empresa no se usan? Con tantos dispositivos y procesos conectados, es fundamental que las compañías capturen, vean y compartan fácilmente los datos en áreas funcionales. Vea el webinar ahora para conocer cómo Aspen Enterprise Insights le aportará estructura y control de agregación de datos y la gestión de proceso en su organización.

Você sabia que até 73% dos dados de uma empresa não são utilizados? Com tantos dispositivos e processos conectados, é fundamental que as empresas capturem, visualizem e compartilhem mais facilmente esses dados de diferentes áreas funcionais. Participe deste webinar para aprender sobre uma solução inovadora. O Aspen Enterprise Insights ™ é uma solução corporativa de visualização e fluxo de trabalho que oferece suporte à decisões em tempo real.

​It’s time to stop equipment breakdowns: but where and how should you start?

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.

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.