B-Life
Definition
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.
Context
B10 life is the most commonly used B-life metric for setting preventive maintenance intervals because it represents the time when only 10% of the population is expected to have failed — an acceptable risk level for many applications. Reliatic calculates B10, B50, and B90 in the Weibull analysis module to support maintenance planning.
Formula
B_p = eta * (-ln(1 - p/100))^(1/beta), where p is the percentage failed
Examples
- Bearing B10 life of 8,000 hours means that 10% of bearings will fail by 8,000 hours. Setting the replacement interval at 8,000 hours limits the expected unplanned failure rate to approximately 10%.
- B50 life (median life) of 20,000 hours means half the population will survive beyond 20,000 hours and half will fail before — a useful metric for spare parts forecasting.
Applicable Standards
- IEC 61649:2008
- ISO 281 (bearings)
Related Terms
A continuous probability distribution widely used in reliability engineering to model the time-to-failure of components and systems. The two-parameter Weibull distribution is defined by the shape parameter (beta) and scale parameter (eta). Its versatility lies in its ability to model increasing, constant, or decreasing failure rates depending on the shape parameter value, making it suitable for all phases of the bathtub curve.
Shape Parameter (Beta)(Beta)The Weibull shape parameter (beta, also written as b or k) that determines the form of the failure distribution and the nature of the failure rate over time. Beta < 1 indicates decreasing failure rate (infant mortality); beta = 1 indicates constant failure rate (random failures, equivalent to exponential distribution); beta > 1 indicates increasing failure rate (wear-out). The value of beta reveals the physics of the dominant failure mechanism.
Scale Parameter (Eta)(Eta)The Weibull scale parameter (eta, also called characteristic life) that represents the time by which 63.2% of the population is expected to have failed. Eta defines the horizontal scale of the Weibull distribution and is always expressed in the same units as the failure time data (hours, cycles, km). At t = eta, the reliability R(t) = e^(-1) = 0.368, regardless of the shape parameter.
Mean Time To Failure(MTTF)The average time from the start of operation until the first failure of a non-repairable item, or the average time between replacement and next failure for items that are replaced rather than repaired. MTTF is technically correct for non-repairable components (bearings, seals, filters, lamps) while MTBF applies to repairable systems. In practice, the terms are often used interchangeably.
ReliabilityThe probability that an item will perform its required function under stated conditions for a specified period of time. Reliability is a quantitative measure expressed as a probability (0 to 1) or percentage. It is a function of the failure rate and time: for constant failure rate systems, R(t) = e^(-lambda*t). Higher reliability means lower probability of failure over the same period.
Where this appears in Reliatic
This concept is used in the Reliability Analytics module.