What are the core components of a predictive maintenance system?
Predictive maintenance has become a cornerstone of modern reliability programs across manufacturing, oil & gas, metals, cement, power generation, and process industries. In this episode, we explore the core components of a predictive maintenance system, including industrial sensors, condition monitoring technologies, IIoT connectivity, data management infrastructure, AI-driven analytics, and maintenance workflow integration.
Drawing on industry best practices and real-world implementations from companies such as Infinite Uptime, this discussion explains how organizations leverage vibration monitoring, temperature analysis, anomaly detection, and machine learning models to predict equipment failures before they occur. Learn how predictive maintenance helps improve asset reliability, reduce unplanned downtime, optimize maintenance costs, and support operational excellence initiatives.
Key Topics: • Industrial sensors and condition monitoring • IIoT data collection and connectivity • AI and machine learning for failure prediction • Asset health monitoring strategies • Maintenance workflow integration • Reliability and operational performance improvements















