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Dear Executive, | |||

* How
to Calculate FITs and MTBF * |
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Since publishing this article last May in the Atlanta-based magazine TechLINKS, it has drawn more responses and requests than any other article. This business article is appropriate for anyone requiring an understanding of the quality, and reliability requirements for electronic components. Calculating Failures In Time (FITs) is an important design step in predicting the likelihood of a failure, or the Mean Time Between Failures (MTBF). Arrhenius
Equation - Acceleration Models The
three variables in the Arrhenius model are the Use (T Censored
Data Distribution
Models The exponential distribution model is used in this example, and many other applications in reliability. A unique value of the exponential distribution for reliability use is that it is the only distribution which has a constant failure rate λ, which is also the reciprocal of the MTBF. With the characteristic bathtub curve, we think of the first part as early failures, the middle as the intrinsic failures, or normal life expectancy, and the end as wear-out failures. The long, flat middle section, or normal life expectancy can be modeled as an exponential distribution, where we can then view those failures as random failures, occurring at a constant rate. Chi-Square:
Goodness-of-Fit FITs
Calculator The example below uses the Arrhenius equation and Chi-Square distribution, respectively: ... Table 1
Table 2
Chi-Square Table |
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