Predictive Maintenance: How IoT Sensors Stop Machines Dying Unexpectedly
A bearing on a production line starts to degrade. Nobody notices. The machine keeps running. Three days later it fails catastrophically — the line stops, repair parts are on a six-week lead time, a full shift of output is gone. Now replay that scenario with predictive maintenance running. The vibration sensor notices the shift on day one. The AI flags early-stage bearing degradation. A work order is automatically generated. The bearing is replaced during a scheduled lunch break on day two. The production line never stops. That's not a hypothetical. That's happening right now in factories, power plants, aircraft fleets, and wind farms worldwide. 🔧 The Short Version Most maintenance is either reactive (fix it when it breaks — expensive chaos) or preventive (service on a schedule — up to 30% of work is unnecessary). Predictive maintenance replaces both with a third approach: service it when the data says it needs it. The economics are hard to argue with: 30–50% reductio...
