What data is used to trigger predictive maintenance?

• A. Calendar-based intervals.
• B. Past maintenance history alone.
• C. Manufacturer's recommendations only.
• D. Condition data from sensors and monitoring that indicate degradation or risk.

Answer: (D)

Predictive maintenance relies on condition data from sensors and monitoring that indicate degradation or risk. By continuously capturing measurements like vibration, temperature, pressure, oil analysis, wear debris, and other health indicators, you can detect patterns or threshold breaches that signal a component is moving toward failure. Analyzing these signals allows you to forecast remaining useful life and schedule maintenance just before a breakdown.

This distinguishes it from calendar-based intervals, which schedule work on a set timetable regardless of actual condition; from past maintenance history alone, which doesn’t reflect current health; and from relying only on manufacturers’ recommendations, which are generic and may not reflect real operating conditions. The trigger for predictive maintenance is the real-time or near-real-time condition data that reveals degradation or rising risk.