acceptance sampling


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Acceptance Sampling

A form of quality control for mass-produced products in which a certain number of the products are tested at random. Acceptance sampling is most useful when it is impossible to test all products. For example, if an armory tested all the bullets it produced, there would be none left. For that reason, acceptance sampling is used to determine whether the majority of the bullets are of sufficient quality to sell.

acceptance sampling

a process in which a sample is taken from a batch of raw materials, work in progress or finished goods to be inspected and tested so as to ensure a predetermined QUALITY standard is consistently achieved. The whole batch will then be accepted or rejected according to whether or not the sample is of an ACCEPTABLE QUALITY LEVEL. This saves the business from having to carry out 100% INSPECTION and testing of the goods involved. For example, a manufacturer taking delivery of 100 identical components from a supplier might inspect and test 10 components (10%) and specify that if more than 2 components (20% of the sample) fail to meet the required specification, then the whole batch will be rejected. In order to specify the performance of a particular sampling plan or evaluate alternative sampling plans, managers can develop OPERATING CHARACTERISTIC CURVES which show the relationship between percentage defects in batches of raw materials or components and the probability of their acceptance.

With JUST-IN-TIME production systems, a company or department may reduce its own acceptance sampling and place the onus of providing fault-free raw materials or components on its supplier. See TOTAL QUALITY MANAGEMENT, QUALITY CONTROL.

References in periodicals archive ?
Incoming material and components, as well as finished goods testing, will be controlled using the new Lot Acceptance Sampling functionality.
The K&F protocol blends all of the latest cost saving techniques like multi-stage discovery, attribute and search analytics for relevance and privilege, advanced de-duplication, de-NISTing, acceptance sampling, and virtual production to name a few.
Ten chapters cover proactive management strategies for dealing with foreign materials; physical separation techniques for controlling contaminants; applications of magnetic separation to prevent contamination of finished food products; principles and strategies for using metal detectors to isolate metallic foreign materials; machine vision and its application, x-ray examination of foods for foreign materials; proper initial validation, ongoing verification, and change control for separation and detection equipment; proper use of acceptance sampling and statistical process control to augment foreign material control programs; and management and communication of risk in situations of crisis.
For quality engineers, Version 4 offers acceptance control charts for processes with a high Cp; acceptance sampling to create sampling plans for attribute and variable data; as well as several special purpose control charts including toolwear charts for data with a built-in linear trend.