Designing acceptance single sampling plans:An optimization-based approach under generalized beta distribution

The availability of information that suppliers possess about the production\r\nprocess, as well as about the technical and economic consequences for customers,\r\nencourages the development and application of acceptance sampling\r\nplans that follow economic criteria, such as the Bayesian ones proposed in the\r\nliterature. The combination of prior knowledge described by the prior distribution\r\nand empirical knowledge based on the sample leads to the decision to accept\r\nor reject the lot under inspection. The main purpose of this study was to derive\r\nacceptance sampling plans for attributes based on a prior generalized beta distribution\r\nfollowing the economic criterion to minimize the expected total cost\r\nof quality. Specifically, a procedure is proposed to define the optimal sampling\r\nplan based on the technical characteristics of the production process and the\r\ncosts inherent in the quality of the product. After the methodological aspects are\r\ndescribed in detail, an extensive simulation study is reported that demonstrates\r\nhow the optimal plan changes according to the main parameters, providing\r\nguidance for practitioners.