Predictive maintenance platform combining plant historian data with wireless vibration sensors to detect and name machine faults.
Control Seat is an industrial predictive maintenance platform that learns each machine's normal operation baseline from historian/SCADA data and wireless vibration and ultrasound sensors, then identifies specific fault types such as bearing wear, unbalance, misalignment, gear mesh, cavitation, and filter loading. It integrates read-only with AVEVA PI, Ignition, OPC UA, MQTT, and common databases, deployable on-prem or in the cloud. The platform provides synchronized machine-process timelines, investigation worksheets, and natural-language queries for root-cause analysis. Control Seat is a product of Control Seat.