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 k0. The literature shows how this constant k0 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 pm. This paper studies several other criteria tha 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 nℝ6p exceeds the given constant pm can be sizable, If the original before-sampling fraction p exceeds pm ‘midly’. The paper further investigates the effects of splitting the yearly population into subpopulations and the effects of underestimating the original fraction.
