Case Study

Cabot Improves Quality by 30% and Reduces Variability with Global Manufacturing Execution System

Cabot standardized on Aspen InfoPlus.21 across all manufacturing sites, improving product quality by 30% and reducing product variability by 20%.

Case Study

Experienced Engineering Services Provider Achieves Enhanced Productivity in Natural Gas Processing Plant Design

Read how experienced engineering service provider, Bilfinger, has been able to design entire gas processing projects, including new innovations such as acid gas cleaning and relief valve sizing, all within the comprehensive Aspen HYSYS engineering environment, faster and with optimal process selections.

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

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

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

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

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

Reliance Industries Ltd Troubleshoots with Aspen Plus and Saves $2.4M USD per Year

Reliance, an Indian conglomerate, built an Aspen Plus model in-house for a distillation column revamp with Aspen Plus which resulted in increased production by $2.4M/year. Learn how they saved money by building the simulations themselves and coming up with a cost-effective solution.

Case Study

Petrofac Improves Process Design Accuracy by Debottlenecking Gas Processes Increasing Capacity by 20%

Download this case study to learn how Petrofac used Aspen HYSYS with Activated EDR models to optimize heat exchanger selection and configuration for a gas production client. This solution achieved the client's goal by increasing gas field production 20%, and as a bonus, reduced CAPEX 25%.

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