The present study presents additional properties of Topp-Leone Gompertz (TL-G) distribution developed by Nzei et al. (2020). All derived mathematical properties play an essential role in reliability analysis. The aim is not only to derive properties of TL-G distribution but also to develop acceptance sampling plans for lot sentencing in which the quality characteristic of the products follows the TL-G distribution. Two acceptance sampling plans, single and repetitive, based on TL-G distribution using the time truncated scheme, have been considered. The application has been observed on a real dataset of the strength of 1.5 cm glass fiber. A simulation-based study has also been conducted when the quality characteristic of the items follows the TL-G distribution. The effect of the misspecification of the parameters has been discussed for the repetitive acceptance sampling plan. Optimal parameters and the minimum average sample number have been obtained for both plans by satisfying consumer’s and producer’s risks simultaneously. The findings indicate that the sample size and acceptance number decrease as the termination ratio, consumer’s risk, and acceptable quality level increase. The repetitive sampling plan performs better than the single sampling plan in terms of sample size and the probability of accepting a lot of products whose lifetime follows the TL-G distribution. It has also been concluded that there is no misspecification of the TL-G distribution parameters for the termination ratio, $a=1.0$. Hence, the same repetitive sampling plans can be used for lot sentencing.

本研究介绍了 Nzei 等人开发的 Topp-Leone Gompertz (TL-G) 分布的其他特性。(2020)。所有导出的数学属性在可靠性分析中都起着至关重要的作用。目的不仅在于推导出 TL-G 分布的特性，而且还为批次判定制定验收抽样计划，其中产品的质量特性遵循 TL-G 分布。两个验收抽样计划，单一的和重复的，基于使用时间截断方案的 TL-G 分布，已被考虑。该应用已在 1.5 cm 玻璃纤维强度的真实数据集上观察到。当项目的质量特征遵循 TL-G 分布时，还进行了基于模拟的研究。已针对重复验收抽样计划讨论了参数指定错误的影响。通过同时满足消费者和生产者的风险，获得了两个方案的最优参数和最小平均样本数。结果表明，随着终止率、消费者风险和可接受的质量水平的增加，样本大小和接受数量减少。在样本大小和接受生命周期遵循 TL-G 分布的大量产品的概率方面，重复抽样计划的性能优于单一抽样计划。还得出结论，没有错误指定终止比的 TL-G 分布参数，通过同时满足消费者和生产者的风险，获得了两个方案的最优参数和最小平均样本数。结果表明，随着终止率、消费者风险和可接受的质量水平的增加，样本大小和接受数量减少。在样本大小和接受生命周期遵循 TL-G 分布的大量产品的概率方面，重复抽样计划的性能优于单一抽样计划。还得出结论，没有错误指定终止比的 TL-G 分布参数，通过同时满足消费者和生产者的风险，获得了两个方案的最优参数和最小平均样本数。结果表明，随着终止率、消费者风险和可接受的质量水平的增加，样本大小和接受数量减少。在样本大小和接受生命周期遵循 TL-G 分布的大量产品的概率方面，重复抽样计划的性能优于单一抽样计划。还得出结论，没有错误指定终止比的 TL-G 分布参数，在样本大小和接受生命周期遵循 TL-G 分布的大量产品的概率方面，重复抽样计划的性能优于单一抽样计划。还得出结论，没有错误指定终止比的 TL-G 分布参数，在样本大小和接受生命周期遵循 TL-G 分布的大量产品的概率方面，重复抽样计划的性能优于单一抽样计划。还得出结论，没有错误指定终止比的 TL-G 分布参数，$\mathrm{一种}=1.0$. 因此，相同的重复抽样计划可用于批次量刑。