Why does PPAP ask for 1.67 and not 1.33?

Some programs use 1.67 as an initial-study target to provide launch margin, but PPAP does not create one universal threshold. Use the applicable customer-specific requirement.

Capability Interpretation

Cp = 1.67: PPAP-Level Potential

2 min read Last updated July 2026

Cp 1.67 is the potential capability that corresponds to a healthy PPAP launch. It assumes centering will follow.

Open the Process Capability Calculator Quality Statistics Knowledge Center

The engineering question this page answers

Cp is at the PPAP launch reference. What has to be true for that potential to become sustained delivered capability?

Decision logic

Cp 1.67 → Cpk_max 1.67 if centered ↓ Long-term Pp usually below Cp → plan for Ppk decay ↓ If Cpk far below 1.67 → centering plan required ↓ If Cpk near 1.67 → protect with SPC reaction plan

Typical PPM and sigma equivalent

Typical PPM: ≈ 0.545 PPM only if centered so Cpk also equals 1.67
Sigma equivalent: 5.01σ potential to each limit when centered

Engineering procedure

Confirm the study window supports launch claim (short-term OK, long-term better).
Compare Cp with Pp; the gap forecasts the Cpk-to-Ppk decay.
Design SPC control limits to catch centering drift early.

Typical failure modes

Reporting Cp 1.67 as evidence of long-term capability.

Engineering insight

Cp 1.67 is the potential; Ppk 1.33 is often the survivor in production. Plan the transition explicitly.

When NOT to use this metric

One-sided specs, unstable processes, non-normal data without documented method.

Relationship to other capability metrics

Cp 1.67 caps Cpk at 1.67; Pp/Ppk usually lower on the same process.

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

Attach the Cp-to-Pp gap to the PPAP submission — it is the audit-relevant number.

Continue the investigation

For the long-term counterpart, see Cp vs Pp and Cpk vs Ppk.

Verification checklist

Study window aligned with launch requirement
Cp-to-Pp gap disclosed
Reaction plan protects the launch margin

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.