Acceptable Quality Limit (AQL)

Acceptable Quality Limit/level (AQL) is the amount of deviation allowed in a product. This built-in feature allows you another level of quality control to make sure your product is at your exact specifications. Let DataNinja handle the heavy lifting and calculate the amount of product to be inspected and how many can fail before a 100% inspection is required.

Setting Up AQL in DataNinja

AQL is a user specific setting done part-by-part.

Step 1
Go to the part (raw material, sub-assembly, or finished good). Select inspection, then select “Add AQL”

2294

Step 2 Add your sampling instructions to the box labeled “Sampling Instructions”.

2292

Step 3 Set up at least one sampling plan. The three plans, critical, major, and minor, dictate how many items can fail before more items need inspection to release the items. The default values are 2.5 (Minor), 1 (Major), and .01 (Critical). You can customize those levels as well.

2294

FAQ about DataNinja AQL

What are default levels? The three levels (critical, major, minor) quickly identify the importance of the inspection. You should only select one sampling plan per part.

1909

The acceptable quality level is the percentage of items that can fail inspection before DataNinja requires a larger sample size to release that batch. If you produced 100 units at the default critical level (0.010), one failure would require an increased level of inspection before the batch can be released. Those levels can be adjusted by you.

What does the sampling look like in a real batch? When a part with an Acceptable Quality Limit Inspection is received or produced, DataNinja will prompt you to perform an inspection. The inspection will calculate the sample size. The sample size is calculated automatically in DataNinja and depends on the amount of product received. At that point, follow your inspection steps and record what you find in DataNinja.

How are the inspections stored in DN? The approval or rejection is tied to the batch. You can see any notes and if the batch passed the inspection by clicking on the batch. Approval is required for the batch to be released and used in DataNinja.