As a traditional statistical quality control method, acceptance sampling plans are widely applied for quality assurance. In a sampling plan, with the aim of acceptance or rejection of a lot of martial, inspection is carried out to determine adherence to standards. Usually, it is assumed that the inspection of the items is error-free. In the present study, this assumption is relaxed. Using Bayesian inferences and considering inspection errors, three mathematical models are developed for the economic single-sampling plans. First, the model is developed based on Binomial distribution. Regarding the application of Poisson model in approximating Binomial distribution, the second model is developed based on Poisson distribution. The third model is presented considering Negative binomial (which is also known as Pascal Distribution). The models determine the sample size and acceptance number to minimize the expected inspection costs incurred during sampling. A numerical example is presented and sensitivity analyses are carried out.
