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Many companies use sampling plans for the acceptance or rejection of lots of products. The final outcome of this decision-making process is based on the inspection of a sample of products selected from a lot under inspection, where a quality characteristic is observed. An important parameter of interest related to acceptance sampling for attributes is the proportion of defective items. This parameter is unknown for a given lot of products, but it can be estimated from the aforementioned sample information. Additional quality characteristics can be observed at the inspection stage. We propose to use this auxiliary information to obtain more accurate estimators of the lot fraction defective at the estimation stage. Various relevant applications of this process are described. For possible scenarios that may arise in practice, the empirical properties of the suggested estimation methods are investigated using Monte Carlo simulations, and desirable results are obtained when there is a strong relationship between the quality characteristic of interest and the auxiliary quality characteristic.
Rosas et al. (2024) studied this question.