AI Basics · Plain English
Predictive Maintenance
Using sensor data and machine learning to predict equipment failures before they happen — powerful, and routinely oversold.
Predictive maintenance uses sensor readings and failure history to warn that a machine is drifting toward failure — so you service it on your schedule instead of its schedule. Done well, it converts unplanned downtime into planned work.
It is also the most oversold application in industrial AI. A useful model needs quality sensor coverage, years of history, and — awkwardly — enough recorded failures to learn from. Vendors who promise savings before auditing that data are selling futures.
This plan takes the conservative path: predictive maintenance sits in the final phase, behind an explicit data-readiness audit, and nobody quotes a savings number before the audit is done.
Where it shows up in this proposal: Phase 5 of the Roadmap, and the readiness-first framing on the AI Opportunities sheet.