Traditional Cpk only applies to normal data. If your data is skewed, censored, or clearly non-normal, this tool auto-fits the best distribution first and then computes process capability for more accurate results.
Paste measurement data
📊 Distribution Fit Comparison (Anderson-Darling; higher p = better fit)
🎯 Process Capability Indices (based on best distribution)
📈 Histogram + Fitted Distribution Curve
🤖 AI Interpretation
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About Non-Normal Process Capability (CpK)
Compute Cp and CpK for skewed data using Box-Cox or Johnson transformations or distribution quantiles, with goodness-of-fit tests included.