It provides no modeled spread margin. Whether it is accepted is determined by the governing requirement, but Cpk will be lower whenever the process is off center.

Capability Interpretation

Cp = 1.00: Spread Equals Tolerance

2 min read Last updated July 2026

Cp = 1.00 is the dividing line between a process whose variation fits the spec and one that does not. Cpk can only equal Cp here if centering is perfect.

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The engineering question this page answers

The potential spread exactly fills the tolerance. What am I actually looking at, and what breaks first?

Decision logic

Cp = 1 → 6σ = tolerance; no margin for centering loss ↓ Is Cpk also near 1? → centered; still no drift margin ↓ Is Cpk below 1? → variation is the ceiling and centering already lost ↓ Improvement lever = variation reduction, not offset

Typical PPM and sigma equivalent

Typical PPM: ≈ 2,700 PPM only if centered so Cpk also equals 1.00
Sigma equivalent: ≈ 3σ potential

Engineering procedure

Confirm Cp is a valid metric for the characteristic (two-sided spec).
Check subgrouping — a Cp near 1 on inflated within-σ is worse than it looks.
Prioritize sources-of-variation study over machine adjustment.
Compare Cp to Pp; a large gap means long-term variation dominates.

Typical failure modes

Attacking centering when Cp is already the bottleneck.
Reporting Cp = 1 on a one-sided characteristic where Cp is undefined.

Engineering insight

At Cp = 1.00, centering is not the problem — variation is. No offset can raise Cpk above Cp.
Cp = 1 on a mixed-stream dataset can hide the fact that each individual stream is capable but off-center from each other.

When NOT to use this metric

One-sided specs or attribute data.

Relationship to other capability metrics

Cp = 1 sets the mathematical ceiling for Cpk at 1.
Cp = Pp only if within-subgroup variation equals overall variation — rare in real production.

Recommended actions

Use the free Process Capability Calculator to compute Cp, Cpk, Pp, Ppk, sigma level, and predicted PPM from your measurement data — no sign-up required.

Engineering notes

Never treat Cp = 1 as a launch state; it is a design or process technology problem.

Continue the investigation

Continue with Process Variation Too High and Process Capability Improvement.

Verification checklist

Two-sided spec confirmed
Streams separated before pooling
Cp vs Pp gap examined for long-term variation

Assumptions and applicability

Process condition: statistical stability is required.
Distribution assumption: use a distribution model justified for the data.
Confirm process stability and measurement-system adequacy before interpreting a capability index.
Use a justified distribution model or non-normal method when the normal model is unsuitable.