Statistical-Based Predictive Maintenance is characterized by:

• A. Uses Historical Data
• B. Uses Real-Time Sensor Data
• C. Requires No Data
• D. Based On Calendar Schedules

Answer: (A)

Statistical-based predictive maintenance centers on using past data to forecast when a component will fail. By analyzing historical failure times, maintenance records, and operating conditions, you build a reliability model (often fitting a distribution like Weibull) to estimate the probability of failure and the remaining useful life. That model then guides when to service parts before they fail, optimizing downtime and costs. Real-time sensor data can enhance these predictions, but the defining feature is deriving the forecast from historical data rather than relying on constant monitoring or fixed calendar intervals.