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

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.

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

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

Energy Company Drives Innovation in Predictive Maintenance via Digital Transformation Program

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.

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

Digital Transformation with Predictive Maintenance Drives Cost Savings

When this large energy company launched its digital transformation initiative, it turned to Aspen Mtell® to execute an online predictive maintenance pilot on a hydrogen compressor.

Case Study

Data-Driven Maintenance Planning Saves $1.8 Million USD Per Year in Shutdown Costs

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.

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.

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