Figure 1: Predictive Maintenance Data Stream for Heat Exchangers in Polyethylene Process Manufacturing
This data stream monitors and predicts maintenance needs for heat exchangers in polyethylene manufacturing by integrating telemetry, operational, and environmental data with a digital twin model. The combined data is broadcast to predictive models and anomaly detection systems, which forecast fouling and equipment failures while identifying critical conditions. Actionable maintenance recommendations are generated, ensuring proactive maintenance and optimal performance. The results are delivered through the XMPro App, reducing downtime and maintaining efficient production cycles.

Figure 1. High Temperature on Base Bearing Recommendation
This recommendation identifies a high temperature condition on the robotic arm’s base gearbox bearing, triggered by AI model logic. It enables early detection of potential issues, minimizing downtime and extending equipment lifespan. Users can add notes, assign, share, and create work requests with special instructions. The system tracks whether the recommendation solved the problem or was a false positive, ensuring timely responses and continuous improvement in predictive maintenance.

Figure 2. Configure With Granular Rule Logic
This example demonstrates how XMPro’s recommendation system can be configured using granular rule logic, AI model logic, or a combination of both. The rule triggers when temperature data from the data stream exceeds a specified threshold. The embedded AI model continuously analyzes sensor data to detect anomalies and predict potential issues. When triggered, the system can take actions such as sending notifications, creating work requests, and executing other predefined actions.

Figure 3. Close The Loop On Event Response
Closing the loop on event response, the system can take various actions, including sending email and SMS notifications for new recommendations, status changes, note updates, and pending times. Additionally, it can automatically create work orders, send information to ERPs, and execute other predefined actions, ensuring comprehensive monitoring and immediate response to turbine issues with detailed guidance and timely alerts.

Figure 1. Real-Time Heat Exchanger Overview Dashboard for Polyethylene Manufacturing

This advanced dashboard provides operators of polyethylene manufacturing plants with a comprehensive view of their heat exchanger infrastructure. It features an interactive layout that dynamically updates with the condition of various heat exchangers, offering a clear visual representation of their operational health.