ISO/TC 69/SC 5/WG 10 - Audit sampling

This document specifies two-stage (double) sampling plans by attributes for inspection for a proportion of nonconforming items in a target population of discrete units, in particular: a) the proportion of nonconforming items in a lot of product items; b) the proportion of nonconforming function instances of an internal control system (ICS); c) the proportion of misstatements in a population of accounting entries or booking records; d) the proportion of nonconforming test characteristics of an entity subject to an acceptance test, e.g. in product and process audits. The plans are preferable to single sampling plans where the cost of inspection is high or where the delay and uncertainty caused by the possible requirement for second samples is inconsequential. The statistical theory underlying the plans, tables and figures are provided in Annexes A through K.

This TR provides an overview of the use of prior information in acceptance sampling. The methods described in the present TR can be applied for the inspection of both processes and lots. Not only do manufacturing or production processes lie within the scope of the present TR; but the scope also covers any process whose outcome are discrete physical or digital units whose conformity can be assessed. In particular, the method described in the present TR can also be applied to AI-based classification systems. The production unit would then consist of the pair (object to be assigned to a class, assigned class) and a conforming unit would be defined as a correct classification. As far as lots are concerned, the scope of the present TR includes both the inspection of isolated lots and serial lot inspection. The term “isolated lot inspection” does not mean that the consumer has no access to information regarding lot quality prior to the inspection of the current lot. Rather “isolated lot inspection” means that there are no switching rules and that the acceptance sampling plan is calculated separately for each new lot. In particular, the consumer having past experience with or knowledge regarding the producer of the lot currently under inspection is perfectly compatible with the concept of “isolated lot inspection.” This TR consists of three main parts. First, a risk-based approach is described (Section REF _Ref187325464 \r \h 7 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100380037003300320035003400360034000000 ). This approach is based on concepts (such as specific consumer’s risk and conformance probability) defined in JCGM 106. It is shown how the sample size and the acceptance number can be calculated once a region for lot conformance and a tolerance for the specific consumer risk have been specified. In addition, an overview of information-based risks is provided. Second, a utility-based approach is described (Section REF _Ref193969454 \r \h 8 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003400350034000000 ). This approach replaces the underlying principle of risk aversion with a rational cost-benefit calculus. Indeed, risk-based approaches consider neither the testing & sampling costs, nor hidden costs such as administrative overhead, nor the potential benefits associated with lot acceptance. By contrast, in the utility-based approach, all potential benefits, costs, losses and damages—including testing & sampling costs, potential costs associated with recalling a lot or healthcare, reputational costs, costs caused by the ingestion of contaminated food, and the bureaucratic and administrative costs associated with the implementation of regulations—are internalized in one utility function. In this sense, the utility approach bridges the gap between the “old world” of risks and the “new world” of utility. Tables with standard plans for various cost-structures and lot size values are provided. Third, an approach for serial lot inspection is described (Section 9). In this approach, a Bayesian updating framework is provided in which data-ageing is reflected in a downweighting mechanism for older data. Prior to these three parts, there are five preliminary sections: · Introduction (Section REF _Ref193969493 \r \h 2 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003400390033000000 ) · Background information regarding the plans in the ISO 2859 and ISO 3951 standards (Section REF _Ref187317559 \r \h 3 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100380037003300310037003500350039000000 ) · Background regarding prior and posterior distributions (Section REF _Ref193969590 \r \h 4 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003500390030000000 ) · Overall framework in which the classical and information-based risks c