The right features for each industrial operation

Anomaly detection

Get advanced alert notifications and use case management for insight capture and comprehensive reporting. Users without programming or data science knowledge can deploy, validate, and interpret the results of predictive models. The software's predefined templates speed configuration, deployment, and expansion.

Fault diagnosis

Use custom data and diagnostic tools to obtain accurate information in real time, allowing users to perform timely and consistent analysis of alert conditions to quickly diagnose and resolve problems. Determine how current performance matches asset failure conditions and identify which individual sensors are contributing to failures. Use sensor preprocessing to detect sensor issues and inconsistencies and improve data quality.

Predicted time to failure

Time-to-failure forecasting provides an estimated time until a failure is likely to occur, so users can determine urgency and plan repair and maintenance strategies that prioritize both safety and cost-effectiveness. With actionable information about operations and maintenance, users can determine whether to continue operations until scheduled maintenance or initiate an urgent shutdown.

Monitor and compare

Easily monitor abnormal conditions during transient periods, such as starts and stops, and automatically identify and compare previous transient events from history. 

Proven scalability

Implement and scale predictive maintenance programs quickly and easily. Create a predictive model once and replicate the model across all assets of the same type, accelerating time to value.

Native integration with AVEVA™ PI System™

Native integration with AVEVA PI System allows you to combine real-time and historical information with artificial intelligence (AI) and machine learning (ML) capabilities. With native integration, users can take advantage of completed work and see results in real time in the AVEVA PI System, so they can make faster, better-informed decisions.

Bring your own algorithm

Data scientists can include specific algorithms in the predictive maintenance loop using Python or a similar language. Monitor all analytics in a single application and complement custom algorithms using built-in model templates, data cleansing, alerting and alert workflow, fault diagnosis, prescriptive actions, forecasting, and case library. Use built-in integration with AVEVA PI System to leverage real-time and historical data.

Prescriptive guidance

Use the prescriptive guidance and recommended actions from the AVEVA Asset Library, a resource containing more than 22,000 hours of experience, to remediate asset failures. Prescriptive actions empower the workforce to improve decision making on asset maintenance and performance issues. Users can take action using predefined guides and minimize repair time by ensuring teams investigate, manage and resolve issues accordingly.

Monitoring and diagnosis

Use AVEVA's remote or on-site monitoring and diagnostic services to learn how to deploy, maintain, and monitor models. Or let AVEVA manage all your monitoring needs. AVEVA's team of expert engineers is here every step of the way to provide helpful information and best practices.

Security

AVEVA Predictive Analytics integrates with existing enterprise security systems. The system supports single sign-on (SSO) authentication and allows administrators to granularly manage user access rights and editing privileges.