Discover how to predict equipment breakdowns and perform prescriptive maintenance using a new approach to asset performance management. In this white paper, learn how nine early adopters of prescriptive analytics have reduced unplanned downtime and improved asset reliability. Download the paper to read real stories about the bottom-line results that have been achieved—in as little as 2 ½ weeks.

领先的资产密集型公司正在使用人工智能和机器学习支持的规范性维护，以释放资产中未被捕获的价值和生产力。使用可扩展、易于实施的规定性维护解决方案，公司可以提高故障检测的准确性，延长资产停机事件的提前通知期，并减少维护开支。

Despite comprehensive maintenance efforts in place by some mines, equipment failures still occur. In order to achieve an overall high level of asset reliability, it’s essential that operators invest regularly and significantly in equipment and infrastructure.

Las empresas líderes en uso intensivo de activos están utilizando el mantenimiento prescriptivo, impulsado por inteligencia artificial y machine learning, para desbloquear el valor y la productividad que se encuentran sin utilizar en los activos. Al emplear una solución de mantenimiento prescriptivo escalable y fácil de implementar, las empresas pueden mejorar la precisión de la detección de fallas, aumentar el período de notificación anticipada de los paros de planta y reducir los costos de mantenimiento.

Leading asset-intensive companies are using prescriptive maintenance—powered by AI and machine learning—to unlock the value and productivity lying uncaptured in assets. Using a scalable, easy to implement prescriptive maintenance solution, companies can improve the accuracy of failure detection, increase the advance notification period of asset downtime events and reduce maintenance spend.

Apesar dos esforços de manutenção abrangentes em algumas minas, ainda ocorrem falhas de equipamento. A fim de atingir um alto nível geral de confiabilidade de ativos, é essencial que as operadoras invistam regular e significativamente em equipamentos e infraestrutura.

Mining companies invest heavily in equipment for all stages of mining, mineral processing, refining and distribution. By monitoring asset condition and behavior and developing profiles of normal operations, anomalies and failures, predictive maintenance tools can notify staff of equipment problems prior to failure. This paper outlines how predictive maintenance provides mining organizations the intelligence needed to:

Las compañías mineras invierten fuertemente en activos para todas las etapas del proceso minero: extracción, procesamiento, refinería y distribución del mineral. Al monitorear la condición y el comportamiento de los activos y desarrollar perfiles de operaciones normales, anomalías y fallas, las herramientas de mantenimiento predictivo pueden notificar al personal sobre los problemas del equipo antes de que ocurra falla. Este documento describe cómo el mantenimiento predictivo proporciona a las organizaciones mineras la inteligencia necesaria para:

Enhance mine-to-mill-to-metal operations with cutting-edge technologies that drive production increases, cost savings and increased safety for employees, the community and the environment. Learn how machine learning in AspenTech’s asset performance management solutions helps ensure reliable operations, enhance process efficiencies and increase mineral recovery.

Prescriptive maintenance technology is transforming how companies increase asset availability. With more advance warning of equipment failures comes more opportunity to mitigate the negative impact of those events.