金属・鉱業

Create process models on a solid foundation. Start your modeling efforts with confidence with the most up-to-date and comprehensive portfolio of physical property data.

View this infographic to see how prescriptive maintenance early adopters are reducing downtime and improving reliability – with results in as little as 2 ½ weeks.

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.

When one of the world’s largest fully integrated zinc and lead smelting and refining complexes wanted to improve their metallurgical operations, the company turned to Aspen Mtell® prescriptive maintenance.

Strategically leverage data with technology to quickly capture savings and increase profits to create the mine of the future. View this infographic and discover the recommended steps to transform data into value on the Road to the Digital Mine.

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.

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.

Real-time condition-based monitoring of assets is an attractive solution for mining companies to minimize their unscheduled downtime and improve reliability of critical equipment. The success of an asset monitoring program depends on how well this data is analyzed, filtered and categorized to enable accurate predictions of impending failures. Focusing on the behavior of an asset only tells a small portion of the story. To fully predict failures, the trends of the entire process must be considered as a whole.

For metals and mining, a prescriptive maintenance solution marries the inherent knowledge of operations with existing process data to automatically create an alert when a failure will occur - reducing the time spent searching for root causes.