Mean time between failures

From Wikipedia, the free encyclopedia

This article may require cleanup to meet Wikipedia's quality standards. Please improve this article if you can. (December 2007)

This article does not cite any references or sources. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (February 2008)

Mean time between failures (MTBF) is the arithmetic mean (average) time between failures of a system. The MTBF is typically part of a model that assumes the failed system is immediately repaired (zero elapsed time), as a part of a renewal process. This is in contrast to the mean time to failure (MTTF), which measures average time between failure with the modeling assumption that the failed system is not repaired.

Contents 1 Overview 2 Formal definition of MTBF 3 Variations of MTBF 4 See also 5 External links

[edit] Overview

For each observation, downtime is the instantaneous time it went down, which is after (i.e. greater than) the moment it went up, uptime. The difference (downtime - uptime) is the amount of time it was operating between these two events.

MTBF value prediction is an important element in the development of products. Reliability engineers / design engineers, often utilize Reliability Software to calculate products' MTBF according to various methods/standards (MIL-HDBK-217F, Telcordia SR332, Siemens Norm, FIDES,UTE 80-810 (RDF2000), etc.). However, these "prediction" methods are not intended to reflect fielded MTBF as is commonly believed. The intent of these tools is to focus design efforts on the weak links in the design.

[edit] Formal definition of MTBF

Referring to the figure above, the MTBF is the sum of the operational periods divided by the number of observed failures.

The MTBF is often denoted by the Greek letter θ, or

The MTBF can be defined in terms of the expected value of the density function ƒ(t)

with

A common misconception about the MTBF is that it specifies the time (on average) when the probability of failure equals the probability of not having a failure (i.e. a reliability of 50%). This is only true for certain symmetric distributions. In many cases, such as the (non-symmetric) exponential distribution, this is not the case. In particular, for an exponential failure distribution, the probability that an item will fail at or before the MTBF is approximately 0.63 (i.e. the reliability at the MTBF is 37%). For typical distributions with some variance, MTBF only represents a top-level aggregate statistic, and thus is not suitable for predicting specific time to failure, the uncertainty arising from the variability in the time-to-failure distribution.

[edit] Variations of MTBF

There are many variations of MTBF, such as mean time between system aborts (MTBSA) or mean time between critical failures (MTBCF) or mean time between unit replacement (MTBUR). Such nomenclature is used when it is desirable to differentiate among types of failures, such as critical and non-critical failures. For example, in an automobile, the failure of the FM radio does not prevent the primary operation of vehicle. Mean time to failure (MTTF) is sometimes used instead of MTBF in cases where a system is replaced after a failure, since MTBF denotes time between failures in a system which is repaired.

[edit] See also

• Failure rate
• Mean time to repair

[edit] External links

• Usenet FAQ about MTBF.
• Reliability and Availability Basics
• Summary including MTTF discussion
• MTBF Calculation Tutorial
• Online Reliability calculator
• Disk failures in the real world: What does an MTTF of 1,000,000 hours mean to you?
• System to calculate MTBF in realtime and to compare it with failure prediction using Neural Networks
• Free MTBF Calculator - supports 26 reliability prediction methods