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

Silvia Facchinetti*, Silvia Angela Osmetti*, Umberto Magagnoli

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo in rivista


The availability of information that suppliers possess about the production process, as well as about the technical and economic consequences for customers, encourages the development and application of acceptance sampling plans that follow economic criteria, such as the Bayesian ones proposed in the literature. The combination of prior knowledge described by the prior distribution and empirical knowledge based on the sample leads to the decision to accept or reject the lot under inspection. The main purpose of this study was to derive acceptance sampling plans for attributes based on a prior generalized beta distribution following the economic criterion to minimize the expected total cost of quality. Specifically, a procedure is proposed to define the optimal sampling plan based on the technical characteristics of the production process and the costs inherent in the quality of the product. After the methodological aspects are described in detail, an extensive simulation study is reported that demonstrates how the optimal plan changes according to the main parameters, providing guidance for practitioners.
Lingua originaleEnglish
pagine (da-a)830-846
Numero di pagine17
RivistaApplied Stochastic Models in Business and Industry
Volume38 (5)
Stato di pubblicazionePubblicato - 2022


  • acceptance sampling plans
  • cost function
  • generalized beta distribution
  • statistical quality control


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