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Acceptance Sampling Tutorial - Operating Characteristic (OC) Curve

The OC curve quantifies the α and β risks of an attribute sampling plan. Below is an ideal OC curve (the bold line) for a situation in which we might want to accept all lots that are, say, ≤ 1% defective and reject all lots that are > 1% defective:

Acceptance Sampling Tutorial - Operating Characteristic (OC) Curve

With this ideal (no risks) curve, all batches with ≤ 1% defective incoming quality level would have a probability of acceptance (Pa) of 1.0. And, all lots with > 1% defective would have a Pa of 0. The Pa is the probability that the sampling plan will accept the lot. It is the long-run % of submitted lots that would be accepted when many lots of a stated quality level are submitted for inspection. It is the probability of accepting lots from a steady stream of product having a fraction defective P.

Typical OC Curve


Since there will always be some risks, a more typical looking OC curve looks more like the one listed in the next page. It is based on the Poisson distribution* (with the defective rate < 10% and n is relatively large compared to N).
Copyright © 2000-2010 Michael G. White. All rights reserved.
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