Glossary

Process capability (Cp, Cpk)

Definition

Capability indices compare process variability with the customer's tolerance limits. Cp says how many times the ±3σ width fits into the tolerance; Cpk additionally accounts for how well the process is centred. Cpk ≥ 1.33 is usually considered capable, 1.67 very good; a value below 1 means the process produces rejects even when running stably.

Quality control & SPC

Cp and Cpk use short-term (within-subgroup) variability and assume a process in statistical control; Pp and Ppk use total long-term variability including shifts between subgroups. The gap between Cpk and Ppk shows how much room there is in better process stability.

The indices assume a normal distribution — for skewed data (runout, roughness) use percentile variants or a transformation. Always complement them with a histogram with tolerances and an estimate of the nonconforming share (PPM), which production understands better than the index itself.

In Statistica

Statistics → Industrial Statistics & Six Sigma → Process Analysis computes Cp, Cpk, Cpm, Pp, Ppk, the PPM estimate and confidence intervals of the indices, including variants for non-normal distributions (Weibull, Johnson, percentile method), with a tolerance histogram and a normal probability plot. Capability can be monitored continuously alongside control charts.

Related terms

Knowledgebase guides

FAQ

What is the difference between Cpk and Ppk?
Cpk uses short-term within-subgroup variability, Ppk the total. A large gap means the process drifts between subgroups.
Why is Cpk smaller than Cp?
Because the process is not centred in the tolerance. Cp = Cpk only when the mean sits exactly in the middle of the tolerance band.

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