This work considers designing of reliability acceptance sampling plan (RASP) when the competing risk data are progressively interval-censored. The methodology uses the asymptotic results of the estimators of parameters of any lifetime distribution under progressive interval censored competing risk data. Therefore, we establish a simplified form of the Fisher information matrix and present the asymptotic properties of the maximum likelihood estimators (MLEs) under a set of regularity conditions. Next, we consider a special case to illustrate the proposed RASP. we assume that the lifetime of the item due to the individual cause follows Weibull distribution. Also, it is assumed that the components are dependent and the gamma frailty model describes the dependent structure between the components. Now, we obtain the optimal RASP in three different ways. First, We present the method for obtaining optimal sample size and acceptance limit using producer's and consumer's risks. Next, we determine the optimal RASP under C-optimal criteria without cost constraints and with cost constraints. Numerical example is performed for both independent and dependent cases. Also, Monte Carlo simulation study is conducted in order to show that the sampling plans meet the specified risks for finite sample size.

翻译：本研究探讨在竞争风险数据为渐进区间删失时可靠性验收抽样方案的设计问题。该方法基于渐进区间删失竞争风险数据下任意寿命分布参数估计量的渐近结果。为此，我们建立了Fisher信息矩阵的简化形式，并在正则性条件集合下给出了最大似然估计量的渐近性质。随后通过特例阐释所提出的可靠性验收抽样方案：假设产品因个体失效原因产生的寿命服从Weibull分布，且组件间存在依赖关系，其依赖结构由gamma脆弱模型描述。我们通过三种不同途径获得最优可靠性验收抽样方案：首先提出基于生产方风险与使用方风险确定最优样本量与验收界限的方法；其次在无成本约束与含成本约束条件下，依据C最优准则确定最优方案。数值算例同时涵盖独立与依赖情形，并通过蒙特卡洛模拟研究验证抽样方案在有限样本量下满足指定风险要求。