Once the anomaly score multiplies in a few days, it is time to maintain the asset and plan for replacement parts and service.
Conclusion
In conclusion, the implementation of triaxial vibration sensors and current signature monitoring (ESA) at the waste recycling plant has significantly enhanced the predictive maintenance capabilities for critical equipment bearings and electrical motors. The use of long-life battery-powered sensors with magnetic bases ensures easy installation and longevity, while the iQunet server and AI service provide real-time data collection and anomaly detection. The system’s ability to monitor trends and detect anomalies allows for timely interventions, thereby reducing the risk of equipment failure and optimizing maintenance schedules. The recent upward trend observed by the Anomaly Monitor underscores the system’s effectiveness in identifying potential issues early, enabling proactive maintenance actions to maintain operational efficiency and minimize downtime. The combination of advanced monitoring technologies and AI-driven analytics ensures that the plant can operate smoothly and sustainably, with minimal interruptions.