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Two sample Bayesian acceptance sampling plan
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AI
DOI：10.1007/s10479-023-05804-6.png)
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Abstract
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This article presents the optimal Bayesian acceptance sampling plan (BASP) for two sample cases. In constructing the BASP, the decision-theoretic approach is used with a specified loss function, and the Bayes decision rule is developed by minimizing the Bayes risk. Both batches of products from the production line are accepted or rejected simultaneously based on the observed sample. Such implementation has a significant advantage in reducing the cost and time by deciding on the acceptance or rejection of both the batches in a single-life testing experiment. The optimal BASP is derived under the assumption of Weibull and exponential lifetimes, although it can be extended for other lifetime distributions also. Some numerical results have been presented to show the performances of the proposed BASP. We have presented the analysis of two data sets; (i) real and (ii) simulated, mainly to show how the proposed method can be used in practice.
Keywords:
Acceptance sampling
Bayesian acceptance sampling plan
Bayes decision function
Bayes risk
Joint censoring scheme
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