# Acceptance sampling with OC-curve | Free template

Acceptance sampling with the OC-curve is a free template to create and evaluate a plan for acceptance of an incoming batch of products to decide if the lot should be accepted or not. Acceptance sampling means that you make a selection from an incoming batch of products and calculate the number of defective units in the sample and compare this against a decision rule in the acceptance plan.

An acceptance plan is a rule decided on in advance and calculated from the sample size and the percentage of errors that will be accepted. The sample size multiplied by the accepted proportion of defects represents the critical value and an incoming lot is accepted if the number of defective units is equal to or less than the critical value. If the number of defective units exceeds the critical value, the incoming lot is not accepted, but sent back to the producer.

For acceptance sampling, there are two possible decisions, to accept or not accept a lot and there are two types of errors that can be done, we can accept a bad batch and send back a good lot. The risk of accepting a bad lot is called the consumer risk and the risk of not accepting a good lot is called the producer risk.

To evaluate the acceptance plan we can establish an OC-curve. An OC curve shows the percentage of errors in a whole lot on the horizontal axis and the probability of accepting so many percent of defective units in an entire lot on the vertical axis. An OC curve is created using the binomial probability distribution. The binomial probability distribution approximates the hyper-geometric probability distribution if the sample size is less than 5 % of the total population.

You can use this template to establish an acceptance sampling plan and to evaluate the acceptance plan with the help of an OC curve that shows the probability to accept a batch with a certain number of defective units.

**Updated: **01/01/2015 | Created by All-templates.biz

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purchase supply chain procurment probability