Acceptance Sampling (AQL)

Acceptance sampling is a statistical inspection method in which a random sample from a lot is inspected and the whole lot is accepted or rejected according to a sampling plan, often indexed by an acceptance quality limit (AQL).

A sampling plan specifies the sample size and the acceptance and rejection numbers for a given lot size and inspection level. In attribute sampling, if the number of nonconforming items in the sample is at or below the acceptance number the lot is accepted, otherwise it is rejected. ISO 2859-1 provides attribute sampling schemes indexed by AQL, the quality level that is the worst tolerable process average when a continuing series of lots is submitted, with switching rules between normal, tightened and reduced inspection. The ISO 3951 series covers sampling by variables, which uses measurements and usually needs smaller samples.

Acceptance sampling is used in goods-in inspection of purchased parts and materials, in final inspection before shipment, and in contract inspection in industries such as textiles, consumer goods and electronics, where 100 per cent inspection would be too costly, slow or destructive. Operating characteristic curves describe how likely a plan is to accept lots of different quality, showing the risks to producer and consumer.

An AQL does not mean that defects up to that level are acceptable to the customer, and accepted lots can still contain nonconforming items. Sampling only works when samples are random and lots are homogeneous. Modern quality practice favours preventing defects through capable, controlled processes and supplier development, using sampling as a check rather than the main means of assuring quality. Plans with an acceptance number of zero are often preferred for critical characteristics.

Key points

Accepts or rejects a lot based on inspecting a random sample.
ISO 2859-1 covers attribute sampling schemes indexed by AQL.
The ISO 3951 series covers sampling by variables.
An AQL is not a level of defects the customer finds acceptable.

Where AiVibe comes in

AiAmbA AI Factory use cases include predictive maintenance and visual inspection on textile, automotive and electronics lines. AiAmbA IoT normalises industrial signals from protocols such as OPC UA and MQTT, with driver availability confirmed per installation.

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Related terms

Terms that refer to Acceptance Sampling (AQL)

IATF 16949Quality, Reliability & Maintenance