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小批量计量抽样方案的预测区间方法：正态过程的单次抽样AI 解读

A prediction-interval approach is used to derive variables sampling plans applicable to finite lots. A normally distributed process is assumed, and lots ranging in size from 5 to 70 are considered. The plans are such that, with high probability, accepted lots will have zero defects (defined in terms of one-sided specification limits). Further, tabulations provide information which is useful for selecting sample size for a specified combination of lot size and acceptable…

小批量计量抽样方案的预测区间方法：高斯过程下的一次抽样AI 解读

A prediction-interval approach is used to derive variables sampling plans applicable to finite lots. A normally distributed process is assumed, and lots ranging in size from 5 to 70 are considered. The plans are such that, with high probability, accepted lots will have zero defects (defined in terms of one-sided specification limits). Further, tabulations provide information which is useful for selecting sample size for a specified combination of lot size and acceptable…

有限批量计量抽样方案的决策理论方法：指数与高斯过程的单次抽样AI 解读

A decision-theoretic approach is used to derive a variables sampling plan applicable to finite lots. A sampling distribution is derived for a general manufacturing process, and one-sided acceptance regions are determined for the particular cases in which the manufacturing process is described by either a normal distribution or an exponential distribution. Comparisons show that for a given risk level, a substantial savings in sample sizes can be effected over those required…