Imagine a plant that is no longer at risk of a random shutdown. Imagine not worrying about losing a year’s worth of hard-fought optimization value in just two to three days due to a maintenance emergency. Through the science of maintenance, historical and real-time operational data combine to predict when a breakdown will occur with months — not just days — of advance notice.

The PSV sizing capabilities in Aspen HYSYS have helped HGA achieve approximately 50% time savings on the entire overpressure protection workflow.

По мере того, как мы привыкаем к "новой реальности" масштабной волатильности, неопределенности, сложности и неоднозначности (ВНСН), компании по всему миру признают необходимость более устойчивого, гибкого и оперативного управления активами и цепочками создания добавленной стоимости, для возможности реагирования на меняющиеся условия на рынке.

Pan Pacific Technologies was seeking a rigorous approach to validate the technical and economic feasibility of its proprietary algal conversion concepts. Through innovative use of Aspen Plus and Aspen Process Economic Analyzer, they developed successful technical and economic models with applications in both academia and industry.

Descubra por qué PEMEX eligió una solución de aspenONE para ayudarlo a construir un Centro de Excelencia para impulsar el rendimiento operativo.

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.

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。

Learn how Process Ecology, a Calgary-based oil and gas consultancy that assists gas processing plants in the operation of their facilities, used Aspen HYSYS to model and provide operating strategies to minimize air emissions, optimize use of solvents and eliminate permit violations.

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.

Learn how S&B reduces estimating manhours by between 50-80% depending on project stage through use of ACCE on all bids and estimates.