Case Study

Two Looming Failures Stopped Within Two Weeks of Monitoring

Read how this mining company used Aspen Mtell® to predict two failures when deployed on 12 assets during a short online pilot—enabling them to proactively plan for the maintenance and repairs, without exposure to higher downtime costs.

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

Plantas mineras migran desde el mantenimiento planificado al prescriptivo con Aspen Mtell

Descargue este caso de estudio para conocer cómo uno de los complejos más grandes y completamente integrados de fundición y refinería de zinc y plomo deseaba mejorar sus operaciones metalúrgicas. Queriendo hacer un mejor uso de los datos que su sistema de gestión de mantenimiento registraba, la compañía realizó un piloto de Aspen Mtell para evaluar la efectividad del mantenimiento basado en monitoreo de condiciones de equipos.

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

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

Case Study: Prescriptive Maintenance Software Helps Saras Improve Business Performance and Drive Operational Excellence

As part of an effort to drive reliability in its refinery operations, Saras turned to Aspen Mtell prescriptive maintenance to improve equipment uptime and decrease maintenance costs. Learn how Saras executed a project within weeks that predicted equipment failures up to 45 days in advance using prescriptive analytics, and enabled the company to increase revenue and cut operating expenses.

Case Study

规范性维护软件帮助Saras 提升经营绩效并推动卓越运营

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。

Case Study

Digital Transformation with Predictive Maintenance Drives Cost Savings

Read how this large energy company used Aspen Mtell to get notification of pending failures in a hydrogen compressor more than 35 days in advance—enabling as much as $30M USD in potential savings by planning the shutdown to minimize production losses.

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

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.

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