A predictive maintenance system can flag rising vibration, unusual temperature patterns, or a combination of signals that suggests a component is likely to fail. That may be technically impressive, but it does not reduce downtime by itself.
Someone still has to decide whether the signal matters, how urgent it is, what action should follow, and whether the equipment can keep operating safely in the meantime.
The harder part often starts after the model has raised the flag. The analytics layer is only one part of the system. [Read more…] about Predictive maintenance in the real world: Why service automation and rollout discipline matter more than models