SPC Guide

Cpk vs Ppk: What's Actually Different

Both compare your process spread to the spec limits. The only difference is which sigma goes in the denominator — and that one choice changes what the number means.

The one-table answer

	Cpk	Ppk
Sigma used	Within-subgroup (σ = R̄/d₂)	Overall (sample standard deviation of all data)
Captures	Short-term, common-cause variation only	Long-term variation incl. shifts, lots, drift
Answers	"What is this process capable of?"	"What did the customer actually experience?"
Typical use	Ongoing production monitoring	PPAP initial studies, monthly/quarterly reports
Common threshold	≥ 1.33	≥ 1.67 (initial studies)

The formulas

Cpk = min[ (USL − X̄) / 3σ_within ,  (X̄ − LSL) / 3σ_within ]
Ppk = min[ (USL − X̄) / 3σ_overall,  (X̄ − LSL) / 3σ_overall ]

σ_within  = R̄ / d₂   (estimated from subgroup ranges)
σ_overall = s        (sample std dev of all individual values)

Same numerator, different sigma. σ_overall ≥ σ_within in practice, which is why Ppk ≤ Cpk in almost every real dataset.

The gap is the diagnosis

Don't just report both numbers — read the difference:

Cpk ≈ Ppk — your process is stable. Between-subgroup variation is minimal. Whatever the value is, it's trustworthy.
Cpk 1.5, Ppk 0.9 — the process is capable but not stable. Something changes between subgroups: shift handovers, material lots, machine warm-up, recalibration. Fix stability before chasing capability.
Both low — the process itself has too much spread for the spec. Centering or tightening variation (or renegotiating the spec) is the only way out.

Calculate Cpk and Ppk from your own data

Paste your measurements — get Cpk, Ppk, PPM and a histogram in seconds. Data never leaves your browser.

Cpk calculator →Ppk calculator →

FAQ

Why is my Ppk lower than my Cpk?

Because overall sigma includes between-subgroup variation (shift-to-shift, lot-to-lot, setup-to-setup drift) that within-subgroup sigma filters out. A Ppk well below Cpk means special-cause variation is leaking into your process between subgroups.

Which one do customers want in a PPAP?

AIAG PPAP typically requires Ppk ≥ 1.67 for initial process studies (short pilot runs) and Cpk ≥ 1.33 for ongoing production. Always confirm the customer-specific requirements — automotive OEMs vary.

Can Ppk ever be higher than Cpk?

Slightly, due to sampling noise, but not meaningfully. If you see Ppk > Cpk by more than rounding error, check your subgrouping — subgroups that mix multiple streams (machines, cavities) inflate within-subgroup sigma.

What sample size do I need for a credible Cpk?

AIAG recommends at least 25 subgroups (typically 125+ individual measurements). Below that, the confidence interval around Cpk is wide — a 'Cpk = 1.40' from 30 points could plausibly be anywhere from 1.0 to 1.8.

Want the full treatment with worked examples and self-check questions? It's Chapter 2 of our SPC Field Manual ($19).