Preventive Maintenance(PM)

A maintenance strategy that uses condition monitoring data, analytics, and failure prediction models to determine the optimal timing for maintenance intervention. Predictive maintenance aims to perform maintenance just before failure is expected, maximizing equipment life while minimizing unplanned downtime. It goes beyond condition monitoring by adding prediction — estimating the remaining useful life based on degradation trends.

A deliberate maintenance strategy where no preventive or predictive maintenance is performed, and the item is allowed to operate until it fails, at which point it is repaired or replaced. RTF is a valid strategy for non-critical items where the consequence of failure is low, the item is not safety-related, redundancy exists, or the failure mode is random (no wear-out pattern). RTF is not the same as neglect — it is a conscious, risk-based decision.

The process of monitoring a parameter of condition in equipment (vibration, temperature, pressure, flow, oil quality, acoustic emission, electrical properties) to identify significant changes indicative of a developing failure. Condition monitoring is the technical enabler of predictive maintenance, detecting degradation at the P point on the P-F curve to allow planned intervention before functional failure.

The time between the point at which a potential failure is first detectable (P — the onset of detectable degradation) and the point of functional failure (F — the point at which the item can no longer perform its required function). The P-F interval determines the maximum inspection interval for condition-based maintenance — inspections must occur at intervals shorter than the P-F interval to detect the developing failure before functional failure occurs.

The time by which a specified percentage of a population is expected to have failed, derived from the Weibull distribution parameters. B10 life is the time by which 10% of the population has failed (90% survival); B50 is median life (50% survival); B90 is the time by which 90% have failed. B-life values are used to set preventive replacement intervals and warranty periods.

The late-life period of a component or system characterized by an increasing failure rate over time (Weibull beta > 1), caused by progressive degradation mechanisms such as fatigue, corrosion, erosion, creep, and material aging. Wear-out failures are predictable and age-related, making them amenable to time-based or condition-based preventive maintenance strategies.