מחשבון פרוגנוסטיקה של יתרת אורך חיים שימושי (RUL)

RUL is the estimated time remaining before an asset reaches a predefined failure or alarm threshold. It is a core concept in prognostics and predictive maintenance defined by ISO 13381-1.

RUL estimation allows maintenance to be planned proactively, avoiding unexpected downtime while maximizing asset utilization.

The choice depends on the degradation pattern:

• Linear — constant-rate degradation (e.g. gradual wear, steady contamination buildup)
• Exponential — accelerating degradation (e.g. bearing spalling, fatigue crack growth)
• Polynomial — non-linear trends where rate changes (e.g. initial break-in followed by stable degradation then rapid failure)

Compare R² values to find the best fit for your data.

A minimum of 3 data points is required for any regression. For better confidence:

• Linear model: 4–5 points recommended
• Exponential: 5–6 points recommended
• Polynomial: 6+ points recommended

More data points, especially near the current operating time, improve the prediction.

Confidence is derived from the R² (coefficient of determination) of the fitted model:

• High (R² ≥ 0.95) — Model fits data very well, RUL estimate is reliable
• Moderate (R² 0.80–0.95) — Reasonable fit, use with caution
• Low (R² < 0.80) — Poor fit, consider a different model or more data points

This calculator supports multiple parameter types (vibration, temperature, wear particles, etc.), multiple regression models, quantitative goodness-of-fit assessment, and extrapolation to a user-defined threshold — providing a full prognostic analysis rather than just a visual trend.