This webinar explains how to build a practical predictive maintenance program by combining the right data acquisition measurements with alerting and analysis workflows. It starts by defining predictive maintenance and why it matters—reducing unplanned downtime, lowering maintenance costs, improving safety, and increasing overall equipment effectiveness by detecting failure conditions before a breakdown occurs. The presenter then walks through best practices for choosing critical assets, identifying common failure modes, and setting appropriate sampling intervals to establish baselines and detect abnormal trends.
From there, the video demonstrates several DAQ-based approaches using ICP DAS USA hardware: power monitoring to detect rising motor load and mechanical jams (shown with smart power meters and a power meter concentrator), vibration monitoring using high-speed accelerometer data loggers for rotating equipment fault detection, and high-speed signal acquisition using signal conditioners plus a high-speed Ethernet DAQ module to capture conditioned temperature, strain gauge, current, and voltage signals. The webinar closes by showing how these measurements can be logged, trended, and used to trigger alarms so maintenance can be scheduled proactively—improving machine life and keeping production running smoothly.
