Abstract
By definition, an Average Outgoing Quality Limit (AOQL) sampling plan leads to inspection of the whole population if the sample shows a number of defective items k exceeding an acceptance number k 0. The literature shows how this constant k 0 and other related parameters can be chosen such that the expected value of p ̃ , the fraction of defectives after inspection and possible correction, does not exceed a prespecified constant p ̃ m . This paper studies several other criteria that are ignored in the literature. It is based on an extensive Monte Carlo simulation. Its main conclusion is that AOQL sampling is useful in practice, including applications in auditing. Yet the probability that the average yearly outgoing fraction p ̃ exceeds the given constant p ̃ m can be sizable, if the original before-sampling fraction p exceeds p ̃ m ‘mildly’. The paper further investigates the effects of splitting the yearly population into subpopulations and the effects of underestimating the original fraction.
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