Statistics

Pp / Ppk Calculator

Measure long-term process performance using overall standard deviation — and compare it to short-term capability to reveal instability, drift, and variation that only appears over time.

Formulas
Pp  = (USL − LSL) ÷ (6s)
Ppk = min[(USL − x̄), (x̄ − LSL)] ÷ (3s)
s = overall sample standard deviation

Enter your values

Use the overall (long-term) standard deviation — calculated from all measurements, not within subgroups.

Highest acceptable value Enter a valid USL.
Lowest acceptable value Enter a valid LSL.
Average of all measurements Enter a valid process mean.
Standard deviation of all data points Enter a valid standard deviation (greater than 0).
Optional — for Pp vs Cp comparison
Short-term variation estimate (from R-bar/d₂ or s-bar/c₄). Leave blank to skip comparison. Enter a valid within-subgroup standard deviation (greater than 0).
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Ready to calculate

Enter your specification limits, process mean, and overall standard deviation. Optionally add within-subgroup standard deviation to compare long-term vs short-term performance.

Long-term performance results
Pp — Long-term potential
Ppk — Long-term actual
Process centering
What this means

Long-term Process Distribution
Overall variation relative to specification limits — reflects actual performance over time
Defect zone
Within spec
LSL / USL
Mean (x̄)
How to Improve Your Performance
Tailored recommendations based on your Pp, Ppk, and process stability
How it works

Understanding Pp and Ppk

Pp

Long-term potential

Pp uses the overall standard deviation — all data over time, including variation from shifts, batches, operators, and environment. It tells you how the process actually behaves in the long run, not just under ideal short-term conditions.

Ppk

Long-term actual

Ppk adds centering to Pp — it takes account of where the mean sits relative to the spec limits. A large gap between Pp and Ppk means the process is off-centre. A large gap between Cpk and Ppk means the process is unstable over time.

Pp/Cp

Stability ratio

Dividing Pp by Cp (or Ppk by Cpk) gives the stability ratio. A ratio close to 1.0 means the process is stable — long-term and short-term variation are similar. A ratio significantly below 1.0 indicates drift, shift, or instability between subgroups.