what is the meaning of MTBF in industrial products?

Answer 1

*It is "Mean Time Between Failure".

*MTBF is a basic measure of reliability for repairable items. It can be described as the number of hours that pass before a component, assembly, or system fails. It is a commonly-used variable in reliability and maintainability analyses.

MTBF can be calculated as the inverse of the failure rate for constant failure rate systems. For example: If a component has a failure rate of 2 failures per million hours, the MTBF would be the inverse of that failure rate.

MTBF = (1,000,000 hours) / (2 failures) = 500,000 hours

*Mean time between failures (MTBF) is the mean (average) time between failures of a system, the reciprocal of the failure rate in the special case when the failure rate is constant. Calculations of MTBF assume that a system is "renewed", i.e. fixed, after each failure, and then returned to service immediately after failure. A related term, mean distance between failures, with a similar and more intuitive sense, is widely used in transport industries such as railways and trucking. The average time between failing and being returned to service is termed mean down time (MDT).

A common misconception about the MTBF is that it specifies the time (on average) when the likelihood of failure equals the likelihood of not having a failure. 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 after a MTBF is approximately 0.63. 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.

On commercial product descriptions, the "MTTF lifetime" is the amount of time the product should last, assuming that it is used properly.

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Answer 2

the MTBF has to do with products that are expected to fail.

For example light bulbs on average will burn so many hours, a few will burn less, a few will burn more. This allows you to predict costs for a given situation. A typical spec for 40 watt bulbs is 1500 hours. If you have to supply bulbs for a factory that has 200 fixtures, you need to order about 1168 a year. It also allows you to estimate the work. If it takes 15 minutes for each replacement job as needed, then that is about 292 man-hours per year, which comes to a lot more money than just the price of the bulb.

What MTBF does not do is predict with any accuracy the time that a particular component will fail. For example, keeping a log book of when a bulb was last replaced won't tell you what day it will go dark again.

It is not always prudent to run divices to failure. returning to the previous example, you may find that arbitrarily replacing working bulbs at half the MTBF will double the cost of supplying bulbs. But the time it takes to replace large groups of fixtures at a pre-scheduled pace could easily reduce the man power to 5 minutes each, cutting the direct labor cost by 3, netting an over-all savings without undue risk of too many dark fixtures between changes.

MTBF has no particular meaning to devices that are not routinely replaced on failure, except to create a theoretical life expectancy. For example MTBF factors are important to designing a communication satellite that is expected to have a 10 year service life. If the composite MTBF calculation for the satellite was 10 years, that means it only has half a chance of doing the required job which is not acceptable.

MTBF is also a measure of the complexity of large systems. For example first generation computers would only work a few minutes. While vacuum tubes were properly made, there were so many in use by the device that the composite MTBF was very low. The real danger of computational failure required that routine results had to be double/triple checked to provide confidence that a failure had not occured during the run. The early NASA space missions used 5 computers, 3 main, 1 referee and 1 spare. All three had to concur for every calculation. If not the referee voted so that there was confidence of having 3 agreements. The spare insured that a bad computer could be replaced so that computational confidence was not impaired.

MTBF is monitored in complex systems to watch overall health. I operated a minicomputer system, and found that room temperature affected MTBF as measured by system reboots. The system improvement paid the cost of adding air conditioning. Earlly failure, 'premature death syndrome' meant that burning in electronic circuits even just a few hours resulted in delivering a product with subsequent superior MTBF characteristics.

Answer 3

MTBF - Mean Time Before Failure

It is the inverse of the sum of all the failure rates for each component in the product.

Each component has a failure rate associated with it (usually given in failures per million hours of operation, or FITs -- failures per billion hours). Manufacturers provide failure rates for most electronic and mechanical components, and if they don't those rates may be calculated using established empirical formulas.

What it means is, the product is expected to perform its function, statistically, for that amount of time (the MTBF time). More specifically, the mean time for a large sample of said product to fail is, the MTBF. Some may fail sooner, some may last longer. The distrubution of failure versus time is a Gaussian bell curve, with the MTBF at the peak of the bell curve.

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Answer 4

Mean Time Between Failure (MTBF)

Answer 5

Mean Time Between Failures