AQL Sampling inspection / AQL
Sampling inspection / AQL · Inspección y ensayos · ISO 1101 + ASME Y14.5
Example in plan
How to interpret it
On the drawing, “AQL 1.0 · level II · ISO 2859-1” states a sampling inspection / aql requirement.
What controls
Instruction to verify only part of the lot according to a statistical sampling plan, which gives the sample size and the number of defective parts that lead to accepting or rejecting the lot. The AQL is not a permitted percentage of bad parts in the delivered product: it is the process quality level that the plan will routinely accept. Each individual part must still meet its tolerance; what sampling decides is what happens to the lot.
How to verify
The instrument is the one in the control plan; what sampling adds is how many parts and against which criterion. The record must include the lot size, sample size, inspection level and AQL applied, and the result for each part. For attribute characteristics (go/no-go) the criterion is the number of defectives; for variables characteristics there are different plans that also use the measured spread.
Common mistakes when interpreting it
- Reading the AQL as the percentage of defective parts the customer agrees to receive.
- Taking the sample from consecutive parts or the top of the box instead of at random from the whole lot.
- Repeating the sampling after a rejection until it comes out favorable, instead of moving to 100% inspection and root cause analysis.
How to get it in the workshop / if it comes out of tolerance
Neither the sample size nor the criterion is improvised: they come from the plan's table specified in the control plan, based on lot size and inspection level. Sample parts are taken at random from the whole lot, not the first ones or whichever are at hand, because consecutive parts measure one moment of the process, not the lot. A rejected lot is not fixed by drawing another sample until it passes.
Lot rejected by sampling: the normal response is 100% inspection of the lot to sort out the good parts, plus root cause analysis, not resampling. If rejects recur lot after lot, the sampling plan is acting as a safety net for an unstable process. If the sample always comes out perfect but the customer finds failures, review how the sample is being taken: almost always it is not random.
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