Sampling procedures for inspection by attributes — Part 4: Procedures for assessment of declared quality levels
|Publication Date:||1 June 2020|
|ICS Code (Application of statistical methods):||03.120.30|
This document establishes single sampling plans for conformance testing, i.e., for assessing whether the quality level of a relevant audit population (lot, process, inventory, file etc) conforms to a declared value. Sampling plans are provided corresponding to four levels of discriminatory ability. The limiting quality ratio (LQR) (see Clause 4) of each sampling plan is given for reference. For levels I-III, the sampling plans have been devised so as to obtain a risk no more than 5 % of contradicting a correct declared quality level. The risk of failing to contradict an incorrectly declared quality level which is related to the LQR is no more than 10 %. The sample sizes for level 0 are designed in a way that the LQR factors of the sampling plans are compatible with the LQR factors for level I.
In contrast to the procedures in the other parts of the ISO 2859 series, the procedures in this document are not applicable to acceptance assessment of lots. Generally, this document mainly focuses on controlling type I error, which differs from the balancing of the risks in the procedures for acceptance sampling.
This document can be used for various forms of quality inspection in situations where objective evidence of conformity to some declared quality level is to be provided by means of inspection of a sample. The procedures are applicable to entities such as lots, process output, etc. that allow random samples of individual items to be taken from the entity.
The sampling plans provided in this document are applicable, but not limited, to the inspection of a variety of targets such as:
- end items;
- components and raw materials;
- materials in process;
- supplies in storage;
- maintenance operations;
- data or records;
- administrative procedures;
- accounting procedures or accounting entries;
- internal control procedures.
This document considers two types of quality models for discrete items and populations, as follows.
i) The conforming-nonconfor
ii) The nonconformities model, where the number of nonconformities is counted on each item, and where the quality indicator of a population of items is the average number λ of nonconformities found on items in the population, or, equivalently, the percentage 100 λ of nonconformities on items in the population.