Wednesday, July 11, 2012

What is AQL (Acceptable Quality Level)

Acceptance Quality Limit
The “AQL tables” are statistical tools at the disposal of buyers (for product inspections). They help determine two key elements:
  • How many samples should be inspected?
  • Where is the limit between acceptability and refusal, when it comes to defective products?
The need for an objective measurement of quality
In virtually every production batch, there will be defective products. It is true even after the manufacturer has checked each individual product and has repaired the defective ones.
Thus, in a supplier/buyer relationship, the supplier cannot be expected to deliver defect-free goods. However, the buyer wants to control the quality of purchased goods, since he does not want too many defects. But what does “too many” mean?
How to set the limit between acceptability and refusal in a way that can be agreed upon and measured?

Definition and application of ‘AQL’

The limit, as described above, is called the ‘AQL’. It stands for ‘Acceptance Quality Limit’, and is defined as the “quality level that is the worst tolerable” (ISO 2859 standard).
For example: “I want no more than 1.5% defective items in the whole order quantity” means the AQL is 1.5%.
In practice, three types of defects are distinguished. For most consumer goods, the limits are:
  • 0% for critical defects (totally unacceptable: a user might get harmed, or regulations are not respected).
  • 2.5% for major defects (these products would usually not be considered acceptable by the end user).
  • 4.0% for minor defects (there is some departure from specifications, but most users would not mind it).
These proportions vary in function of the product and its market. Components used in building an airplane are subject to much lower AQL limits.

Getting familiar with the AQL tables

Before using the AQL tables, you should decide on three parameters:
  • The ‘lot size’. If you ordered different products, the quantity of each product is a lot size, and separate inspections should be carried out for each lot. If you ordered only one product, the lot size is your total order quantity.
  • The inspection level. Different inspection levels will command different number of samples to inspect. In this article, we will stick to the so-called “level II”, under “normal severity”.
  • The AQL level appropriate for your market. If your customers accept very few defects, you might want to set a lower AQL for both major and minor defects.
There are basically two tables. The first one tells you which ‘code letter’ to use. Then, the code letter will give you the sample size and the maximum numbers of defects that can be accepted.
First table: sample size code letters

How to read this table? It is very easy.
If you follow my example, I assume your ‘lot size’ is comprised between 3,201pcs and 10,000pcs, and that your inspection level is ‘II’. Consequently, the code letter is “L”.

Second table: single sampling plans for level II inspection (normal severity)

How to read this table?
Your code letter is “L”, so you will have to draw 200pcs randomly from the total lot size.
Besides, I assume you have set your AQL at 2.5% for major defects and 4.0% for minor defects. Therefore, here are the limits: the products are accepted if NO MORE than 10 major defects AND NO MORE than 14 minor defects are found.
For example, if you find 15 major defects and 12 minor defects, the products are refused. If you find 3 major defects and 7 minor defects, they are accepted.
Note: in quality inspections, the number of defects is only one of the criteria. It is sometimes called “quality”, or “quality findings”. The other criteria are usually on the inspector’s checklist, which typically includes:
  • Packaging conformity (barcodes, inner packing, cartons, shipping marks…).
  • Product conformity (aspect, workmanship…). If all the products are in red color instead of orange, there is no need to count each sample as a defect. It makes more sense to refuse for product conformity.
Specific tests defined in the inspection protocol (they might not be performed on all samples).