Mitsubishi Electric offers a Smart Condition Monitoring (SCM) Kit solution that uses the latest advanced FAG SmartCheck sensors for monitoring and feedback. The kit provides an integrated approach to monitoring the condition of individual assets, and enables a holistic approach to monitoring the asset health of the whole plant. Individual sensors retain the traffic light system for local warning indication at the machine, but at the same time information from multiple sensors is transferred over Ethernet to the intelligent sensor controller (this can be a Mitsubishi Electric PLC) for in-depth monitoring and more detailed analysis. 

The SCM Kit provides a plug-and-play solution for machine condition monitoring. SmartCheck sensors can be added to machines as and where required, with a simple teach function allowing the sensor and controller to learn the normal operating state of the machine, generating a memory map of key parameters. Once set up, the SCM provides 24/7 monitoring of each asset, with functions including bearing defect detection, imbalance detection, misalignment detection, lack of lubricant, temperature measurement, cavitation detection, phase failure recognition and resonance frequency detection.

Linking multiple sensors into the control system enables the controller to analyze patterns of operation that are outside the norm, with a series of alarm conditions that can provide alerts that attention is needed. The SCM analysis provides detailed diagnostics, offers suggestions for where additional measurements should be taken, and provides maintenance staff with more precise error identification. It even provides recommendations as to what rectification actions should be taken, with clear text messages presented to personnel. Further, this information can be networked to higher-level systems for ongoing trend analysis across all of the assets around the plant.

Thus the SCM offers comprehensive analysis on the health of individual machines as well as a complete overview on the health of the wider plant. The result is vastly improved predictive maintenance and optimized asset lifecycle management. With maintenance able to be planned in advance, there is far less unplanned downtime and significant reductions in short notice loss of service.