CALCULATORS / FOUNDATIONS

Reliability and engineering statistics

Explicit distribution, independence and sample assumptions.

component reliabilities, architecture, independence assumption → system reliability

failure-rate assumption, mission duration → survival probability, expected failures

shape/scale parameters or qualified failure data → survival curve, quantiles, fitted uncertainty

variance, target interval width, confidence convention → required sample size

specification limits, process mean, variation, stability assumption → Cp/Cpk estimates, interpretation limits

input distributions, correlations, model, random seed → output samples, quantiles, convergence diagnostics

model derivatives, covariance, input uncertainties → output variance, dominant contributors

failure/repair assumptions, downtime model → steady-state availability estimate

target reliability, confidence, mission profile, sample model → test sample size, exposure assumptions