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Use independent batches and balanced within-batch sampling to distinguish production variation from specimen and measurement variation.
Updated · NANOLAB Knowledge

Measuring one coating batch many times can estimate some measurement variation, but it cannot establish how production batches differ. A sampling plan must include independent batches when between-batch variation is the question.
Identify batches, specimens within batches and repeated measurements within specimens. Keep those levels in the data rather than entering every reading as an independent production result.
An illustrative plan might sample four independent batches, three specimens from each and two readings per specimen. This creates 24 readings but only four batch units. The numbers are an example, not a universal recommendation; choose the design according to precision needs and available resources.
A suitable nested or mixed model can estimate variance components under its assumptions. Report uncertainty, especially with few batches. Do not interpret a small estimated batch component as proof that all future batches are identical. If every batch was also tested by a different operator on a different day, those effects are entangled. Improve the design before attributing the observed variation solely to manufacturing.
The sources below support the stated concepts or describe their own methods. The worked scenarios are editorial examples, not NANOLAB test results.
Ask NANOLAB about your surface and intended use. For application and care, use the current instructions for the exact product.

Inspector Agreement in Coating QC: Look beyond the Percentage Agreeing