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Distribution Identification Calculator

Before fitting parameters you have to choose a distribution, and that choice affects extrapolated life far more than the parameter estimates do. Distribution identification ranks candidate distributions against your data using goodness-of-fit statistics — but the physics of the failure mode should always get a vote alongside the statistics.

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Formula

Anderson-Darling statisticLower AD indicates a better fit; it weights the tails more heavily than Kolmogorov-Smirnov.
Correlation coefficientρ from the probability plot; closer to 1 is better.
Likelihood-based comparisonAIC = 2k − 2·ln(L)
Penalises extra parameters, so a 3-parameter Weibull must earn its third parameter.

How to interpret the result

WeibullWeakest-link failures, wear-out, most mechanical life data. The flexible default.
LognormalMultiplicative degradation — crack growth, diffusion, corrosion — and repair times.
ExponentialConstant hazard only. Justified for some electronics in useful life, rarely elsewhere.
NormalWear-out with a well-defined mean life and symmetric spread; less common for life data.

Common mistakes

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About Reliability Pro

Distribution Analyzer is part of a suite of 126 reliability, maintenance and quality engineering tools covering life data analysis, accelerated testing, system reliability, FMEA and root cause, SPC, and design for reliability. It runs in the browser and as native iOS and Android apps, so the same calculation is available at a desk or in front of the asset.

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