Mean time between failures (MTBF) is the predicted elapsed time between inherent failures of a system during operation.[1] MTBF can be calculated as 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 (MTTR), as a part of a renewal process. This is in contrast to the mean time to failure (MTTF), which measures average time to failures with the modeling assumption that the failed system is not repaired (infinite repair rate).
The definition of MTBF depends on the definition of what is considered a system failure. For complex, repairable systems, failures are considered to be those out of design conditions which place the system out of service and into a state for repair. Failures which occur that can be left or maintained in an unrepaired condition, and do not place the system out of service, are not considered failures under this definition.[2] In addition, units that are taken down for routine scheduled maintenance or inventory control, are not considered within the definition of failure.
What is MTBF?
MTBF is an abbreviation for Mean Time Between Failures.
MTBF is a measure of how reliable a product is. MTBF is usually given in units of hours; the higher the MTBF, the more reliable the product is.
For electronic products, it is commonly assumed that during the useful operating life period the parts have constant failure rates, and part failure rates follow an exponential law of distribution. In this case, the MTBF of the product can be calculated as:
MTBF = 1/(sum of all the part failure rates)
and the probability that the product will work for some time T without failure is given by:
R(T) = exp(-T/MTBF)
Thus, for a product with an MTBF of 250,000 hours, and an operating time of interest of 5 years of 24x7 (43,800 hours):
R = exp(-43800/250000) = 0.839289
which says that there is an 83.9% probability that the product will operate for the 5 years without a failure, or that 83.9% of the units in the field will still be working at the 5 year point. Note: the Reliability calculation assumes replacement upon failure.
The MTBF figure for a product can be derived in various ways: lab test data, actual field failure data, or prediction models (such as Telcordia SR-332 or MIL-HDBK-217). The RelCalc for Windows software can help you do your MTBF prediction.
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