Predix Asset Performance Management
Achieve less unplanned downtime by predicting equipment issues before they occurRequest a demo
With APM Reliability, part of Predix Asset Performance Management (Predix APM), asset-intensive organizations can leverage advanced predictive diagnostics to analyze data, and detect and diagnose asset issues before they occur. This allows companies to schedule downtime and control costs on their own terms. APM Reliability is designed to work across all assets (fixed, rotating, and non-rotating), all equipment types and manufacturers (GE and non-GE), and all industries—across the plant and across the enterprise.
Collaborate across functional teams to make better operational and maintenance decisions.
Measure the effectiveness of asset strategies to know when corrections are warranted.
Develop and retain best practices from an ever-changing workforce to continuously improve decision making.
Digital twin blueprints
Digital twin blueprints enable the analyst to anticipate or identify failure of an asset with longer lead time to improve reliability and performance by modeling the asset’s expected versus observed states. The analyst can leverage structured time-series data and unstructured data, including process parameters and condition alerts, in the context of the assigned maintenance strategy and actual maintenance performed. It can also compare operating conditions and performance with other like assets.
Reliability analysis provides a comprehensive set of analytical tools to help better understand causes of asset failure patterns and the true cost of failure. Understanding the historical costs, failure frequencies, and trends of production assets in a critical component of any asset performance management program.
As a result of implementing the APM solution, we're expecting qualitative improvements in the following aspects of asset management: enhancing equipment reliability by means of constantly improving strategies of maintenance, reducing the costs of repair and maintenance scheduling, effectively reallocating resources, and hence decreasing production risks.
Standardize the collection, integration, modeling, and analysis of disparate data into a single, unified view.
Develop asset strategies to optimize across availability, reliability, and costs.