Cpk is a process capability index: it measures the spread of a parameter and its centering relative to the specifications. A Cpk above 1.33 indicates a capable process; above 2, the process is highly robust and well-centered.

How does Cpk justify streamlining controls?

A process with a high Cpk keeps a comfortable margin relative to the limits: an out-of-spec drift between two controls is very unlikely. Cross-referenced with a history free of OOS/OOT, this makes it objective that control frequency can be reduced without increasing risk.

Is Cpk enough to decide?

No. Cpk is a snapshot; you have to cross-reference it with deviation history (the movie), a risk FMEA and machine barriers, then translate all of it into frequency via an AQL sampling plan. It's this body of proof that makes the decision robust and defensible in an inspection.

What should you do with a low-capability process?

You don't streamline: you keep the control and act on the process first (centering, reducing variability, making the settings reliable). Streamlining an unstable process would amount to masking a real risk — the opposite of the goal.

Process · Capability

Process capability (Cpk): the proof for streamlining.

To justify controlling less often, you need objective proof, not a hunch. That proof exists: process capability (Cpk), cross-referenced with deviation history. A highly capable, well-centered process doesn't drift between two controls — and that can be demonstrated, with the numbers to back it up.

Quantify my capability Read: streamlining IPC

Cpk > 1.33

the usual threshold for a "capable" process. Above 2, the process is so robust and well-centered that a deviation between two controls becomes highly unlikely.

Indicative capability benchmarks (Cpk).

Cpk measures both the spread of a parameter and its centering relative to the specifications. The higher it is, the more comfortable the margin. At a pharmaceutical site in Morocco, a tracked parameter showed a Cpk of 3.63 (measurements at 400–403 mg for a 390–410 mg specification): in other words, an out-of-spec drift between two samplings is almost impossible.

The real problem

We measure capability to validate… then forget it when it comes to steering.

Cpk is calculated during validation, then filed away in a report. Instead, it should inform a very concrete decision: how often to control? A process shown to be highly capable and with no deviation history doesn't need to be checked every 30 minutes — the data proves it, you just have to use it.

Reading capability

What Cpk really tells you.

Three simple benchmarks to turn a number into a decision.

Cpk	Reading	Implication for control
< 1.0	Process not capable	Close control justified; act on the process first
1.0 – 1.33	Borderline / to monitor	Keep the frequency; make it reliable before streamlining
1.33 – 2.0	Capable	Streamlining conceivable, cross-referenced with history and FMEA
> 2.0	Highly capable and centered	Strong candidate for lower frequency, with the proof to support it

Indicative benchmarks — the decision is always made by cross-referencing Cpk, deviation history and risk analysis.

The condition

Capable isn't enough: it must also be stable.

A high Cpk is a snapshot; the history is the movie. It's cross-referencing the two that makes the proof: a highly capable process and with no OOS/OOT over several years is demonstrably stable over time. At that level, control frequency mainly guards against a risk that no longer materializes — and machine barriers (automatic rejection out of tolerance, stop on exceedance) already cover the residual chance of error.

The complete method for streamlining IPC →

Go further

From proof to decision.

In-process controls

Frequently asked questions