We obtain a reliability acceptance sampling plan for independent competing risk data under interval censoring schemes using the Bayesian approach. At first, the Bayesian reliability acceptance sampling plan is obtained where the decision criteria of accepting a lot is pre-fixed. For large samples, computing Bayes risk is computationally intensive. Therefore, an approximate Bayes risk is obtained using the asymptotic properties of the maximum likelihood estimators. Lastly, the Bayesian reliability acceptance sampling plan is obtained, where the decision function is arbitrary. The manufacturer can derive an optimal decision function by minimizing the Bayes risk among all decision functions. This optimal decision function is known as Bayes decision function. The optimal sampling plan is obtained by minimizing the Bayes risk. The algorithms are provided for the computation of optimum Bayesian reliability acceptance sampling plan. Numerical results are provided and comparisons between the Bayesian reliability acceptance sampling plans are carried out.

翻译：本文基于贝叶斯方法，针对区间删失机制下的独立竞争风险数据构建了可靠性验收抽样计划。首先，在预先设定批次接收决策准则的条件下，建立了贝叶斯可靠性验收抽样计划。对于大样本情形，贝叶斯风险的计算需要极高的计算资源。因此，我们利用最大似然估计量的渐近性质推导出近似贝叶斯风险。最后，针对任意决策函数的情形构建了贝叶斯可靠性验收抽样计划。制造商可通过在所有决策函数中最小化贝叶斯风险来推导最优决策函数，该最优决策函数即贝叶斯决策函数。最优抽样计划通过最小化贝叶斯风险获得。本文提供了计算最优贝叶斯可靠性验收抽样计划的算法，给出了数值计算结果，并对不同贝叶斯可靠性验收抽样计划进行了比较分析。