Designing Bayesian Two-Sided Group Chain Sampling Plan for Gamma Prior Distribution

Acceptance sampling is used to decide either the whole lot will be accepted or rejected, based on inspection of randomly sampled items from same lot. As an alternative traditional plans, it possible use Bayesian approaches using previous knowledge process variation. This study presents a two-sided group chain plan (BTSGChSP) by various combinations design parameters. In BTSGChSP, preceding as well succeeding lots. Poisson function derive probability acceptance defective and non-defective products. Gamma distribution considered suitable prior for distribution. Four quality regions are found, namely: (i) decision region (QDR), (ii) probabilistic (PQR), (iii) limiting (LQR) (iv) indifference (IQR). Producer’s risk consumer’s estimate regions, where acceptable level (AQL) associated with producer’s (LQL) risk. Moreover, AQL LQL in selection parameters BTSGChSP. The values all BTSGChSP presented inflection points’ found. finding exposes that better substitute existing industrial practitioners.