AQL Calculator

Know Your Acceptance Quality Limit Instantly

Calculate sample sizes and defect thresholds based on AQL tables in seconds — built for QC teams and importers who need fast, accurate answers.

  • Get normal & special sample sizes instantly
  • See maximum allowed major and minor defects
  • Based on standard AQL tables (ISO 2859-1)
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AQL Calculator

What Is an Acceptable Quality Level (AQL)?

The acceptable quality level (AQL) is a crucial measure used in product inspections to determine the maximum number of acceptable defects in a sample size before a batch is rejected. It is usually expressed as a percentage or ratio, indicating the number of defects compared to the total quantity. Importers typically set different AQLs for critical, major, and minor defects to maintain high-quality standards.

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Learn how AQL standards work and see the full tables here

KEY TAKEAWAYS

  • The acceptable quality level (AQL) represents the worst quality level tolerable for a product.
  • AQL varies by product, with items posing higher health risks having lower AQLs.
  • Setting appropriate AQLs ensures product quality and compliance with safety regulations.

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How Do I Determine the Right Sample Size and Acceptance Number?

Determining the right sample size and acceptance number involves agreeing on an AQL standard suitable for the level of risk both buyers and sellers are willing to assume. This standard is used during pre-shipment inspections and is essential for quality control. Common settings for consumer goods in China include:

  • 0% for critical defects (unacceptable as they may harm users or violate regulations).
  • 2.5% for major defects (unacceptable to most end users).
  • 4.0% for minor defects (minor deviations from specifications that most users would tolerate).

AQL Calculator

Based on the Tables

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For a batch to pass inspection based on the AQL Tables, the inspector must select a sample of 0 items and meet the following criteria:

Major defects are found on a maximum of 0 sample(s).

Minor defects are found on a maximum of 0 sample(s).