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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:传统的过程能力指标要求质量特性遵循正态分布。但是在实际的生产过程中,质量特性通常具有非正态分布,并且几乎所有生产过程除了批次内的可变性外,还表现出批次间的可变性。基于广义置信区间,提出了单向随机模型下对数正态过程的过程能力指标的置信区间。基于广义置信区间,基于单向随机模型构造了对数正态分布过程能力指标的置信区间。通过仿真研究了广义置信区间下限的良好性能及其覆盖概率,仿真结果表明,在对数正态分布情况下,广义置信区间方法具有良好的性能。最后,提供示例来说明所提出方法的实现。

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