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Generalized confidence intervals for process capability indices of log-normal distribution in the one-way random model

机译:单向随机模型中对数正态分布的过程能力指标的广义置信区间

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Traditional process capability indices require that quality characteristics follow normal distribution. But in the actual production processes, quality characteristic usually has a non-normal distribution and almost all the production processes exhibit the between batch variability besides the within batch variability. This paper proposed confidence intervals for process capability indices for log-normal process under the one-way random model based on the generalized confidence interval. Motivated by the generalized confidence intervals, the confidence interval of the process capability indices of log-normal distribution are constructed based on the one-way random model. The good performance of generalized lower confidence limits and its coverage probabilities are studied via simulation, and simulation results show the good performance of the generalized confidence interval method in the log-normal distribution case. Finally, examples are provided to illustrate the implementation of the proposed method.
机译:传统的流程​​能力指数要求质量特征遵循正常分布。但在实际生产过程中,质量特性通常具有非正常分布,并且几乎所有的生产过程除了在批量变异性内,几乎所有的生产过程都表现出批量变异性。本文提出了基于广义置信区间的单向随机模型下对数正常过程的过程能力指标的置信区间。通过广义置信区间的激励,基于单向随机模型构建了对数正态分布的过程能力指标的置信区间。通过模拟研究了广义较低置信限制及其覆盖概率的良好性能,仿真结果表明了在日志正态分布箱中的广义置信区间方法的良好性能。最后,提供了示例以说明所提出的方法的实现。

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