Acceptance sampling plan is used for decision making in the field of products quality control. These plans provide the producer and the consumer with decision rules for accepting or rejecting the lot. In this paper, a new approach for the economic design of resubmitted and multiple dependent state (MDS) sampling plans is proposed based on the process yield index considering Taguchi loss function and the average number of sample size $n$, which minimizes the costs related to the yield index $S_{\mathit{pk}}$. In the proposed model the loss of a batch is considered rather than a single product. Also, the loss of both producer and consumer based on the yield index is minimized simultaneously through solving an optimization model and the parameters of the proposed sampling plans are obtained. The performance of both proposed sampling plans is analyzed and compared in terms of average sample number and total expected loss. The results indicate that both proposed sampling plans show satisfactory performance. Moreover, the advantages of the proposed model over the existing resubmitted and MDS sampling plans are presented. Finally, the application of the proposed model and sampling plans is illustrated through a real case in batch manufacturing processes.

验收抽样计划用于产品质量控制领域的决策。这些计划为生产者和消费者提供了接​​受或拒绝批次的决策规则。在本文中，基于过程产量指数考虑田口损失函数和平均样本数量，提出了一种重新提交和多重依赖状态（MDS）抽样计划的经济设计新方法。$n$, 最小化与产量指数相关的成本 ${秒}_{\mathit{峰值}}$. 在提议的模型中，考虑的是批次的损失而不是单个产品的损失。此外，通过求解优化模型，同时最小化基于产量指数的生产者和消费者的损失，并获得了所提出的抽样方案的参数。从平均样本数和总预期损失方面分析和比较了两个提议的抽样计划的性能。结果表明，两个提议的抽样计划都显示出令人满意的性能。此外，还介绍了所提出的模型相对于现有的重新提交和 MDS 抽样计划的优势。最后，通过批量生产过程中的一个真实案例说明了所提出的模型和抽样计划的应用。