Case Study

Leading Pulp and Paper Manufacturer Detects and Avoids Major Fire with Aspen Mtell

Aspen Mtell provided a nine-day advance warning of imminent kiln overheating, allowing the plant to change operating conditions and avoid an operational shutdown. Download this case study to learn more.

Case Study

Aspen Mtell® Machine Learning Finds Cause of Compressor Failures at LNG Facility

Read how this LNG facility used Aspen Mtell prescriptive maintenance to provide up to 61 days advance notice of catastrophic compressor failures, preventing an economic loss of more than $40M USD per occurrence. Quick to implement and readily scalable, the solution provided key insights into the root cause of the failures.

Case Study

Leaks in Reboiler Detected With Months of Advance Notice

Learn how a manufacturer of engineering thermoplastics discovered the root cause of recurring failures in their shell-and-tube reboilers using Aspen Mtell prescriptive maintenance.

Case Study

US Railway Saves Millions by Preventing Line of Road Failures

A major transportation company responsible for delivering customer goods on time, safely and reliably, was plagued by catastrophic failures of locomotives that had gone undetected by its current reliability techniques. Using Aspen Mtell to examine data from engine lube oil samples, a leading U.S. railway was able to save millions of dollars.

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

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

De reactivo a proactivo: Genere mejores resultados comerciales con machine learning

Conozca cómo se utilizó la tecnología de mantenimiento predictivo de Aspen Mtell para saber con 27 días de anticipación sobre fallas de la válvula central de una planta de plásticos especializada.

Case Study

Ahorre costos con mantenimiento predictivo durante la transformación digital

Lea cómo Aspen Mtell predijo una falla en el compresor con 35 días de anticipación, permitiendo que la empresa de energía evitara una parada de emergencia y cumpliera con las metas de producción. Minimizó las pérdidas de producción planificando la parada de la planta: ahorro potencial de 30 millones de dólares

Case Study

Dos fallas inminentes se detuvieron a las dos semanas del monitoreo

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.

Case Study

Detección de fugas en el rehervidor con meses de anticipación

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.

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