Step 1: Determine sample size and acceptance criteria for a sampling plan
When you create an acceptance sampling plan, you must determine how many items to inspect from a lot of product, and determine when to accept or reject a lot of data based on the sample measurements.
Using your specifications for lot size, AQL, RQL, producer's risk (α), consumer's risk (β), and the specifications for your process, Minitab determines an appropriate sampling plan with a specific sample size and critical distance.
The critical distance is the value that Minitab uses to compare with the sample mean and specification limits to determine whether to accept or reject a lot.
After you collect your sample measurements, you will compare the Z values that are calculated from the mean and standard deviation to the critical distance and decide whether to accept or reject the entire lot.
If you had an upper specification, you need to consider that criteria, as well, and accept if (upper specification – mean) / standard deviation is ≥ 3.55750. Both of these criteria must be true, or you should reject the entire lot.
Step 2: Compare the probability of accepting or rejecting lots from alternative plans
After you create an acceptance sampling plan, you can vary the sample size and critical distances to reduce overall sample size.
You can compare plans by varying the sample size, the critical distance, or both together, and examine how the risks of acceptance vary.