MedTech Manufacturing worked example
Process Validation Sample Size at 12% sampling rate per run: a worked example
What does the result look like when sampling rate per run reaches 12%? The full calculation is worked below with real intermediate numbers. Use this when writing validation protocols, planning lab capacity for PQ activities, or estimating material consumption for validation batches.
The inputs for this scenario
- Number of validation runs: 3 runs (unchanged)
- Sampling rate per run: 12 % (raised for this scenario; the documented default is 10)
- Minimum samples per run: 30 samples (unchanged)
Working through the calculation
- Applying the documented formula (Calculated validation samples = number of validation runs × sampling rate per run) to the inputs above produces each figure below.
- At this operating point the engine returns 30 samples for required sample size, the number this scenario is built around.
- At this operating point the engine returns 1 samples for calculated sample.
- At this operating point the engine returns 30 samples for minimum sample size.
How this compares with the baseline
- Against the tool's baseline example, where sampling rate per run sits at 10% and the headline result is 30 samples, this scenario lands almost exactly on the baseline at 30 samples.
- A figure at this level is achievable when sampling rate per run is genuinely sustained, not just peaked for a shift. It does not derive a statistically rigorous confidence/reliability sample size (e.g., 95/95 from a binomial or normal tolerance table) — it sizes against a rate plus a floor, so for high-risk attributes confirm against an ANSI/ASQ Z1.4 or C=0 plan.
Results at a glance
- Required sample size: 30 samples (headline result)
- Calculated sample: 1 samples
- Minimum sample size: 30 samples
Run it with your numbers
- Every input above is editable in the live Process Validation Sample Size calculator, which recalculates instantly and can be shared with the inputs intact.
Last reviewed 2026-05-12.