AI & Automation for Predictive Maintenance — Research Project

A scoped, collaborative research project to identify practical predictive maintenance use cases, data needs, pilot plans, and governance that reduce downtime while avoiding overhyped AI pitfalls.

AI & Automation for Predictive Maintenance — Research Project
Example

Three concrete use-case examples (signals, lead time, actions). 1. Motor bearing faults (manufacturing line). Signals: vibration RMS and spectral bands, bearing housing temperature. Typical lead time: 1–6 weeks depending on failure mode. Action: schedule bearing replacement in maintenance window; perform grease change...

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