• 품질경영학회지
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• 제35권1호
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• pp.10-19
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• 2007

ANOVA is widely, used for measurement system analysis. It assumes that the measurement error is normally distributed, which nay not be seen in some industrial cases. In this study the estimates of the measurement system variability and PTR (precision-to-tolerance ratio) are obtained by using weighted standard deviation for the case where the measurement error is non-normally distributed. The Standard Bootstrap method is used foy estimating confidence intervals of measurement system variability and PTR. The point and confidence interval estimates for the cases with normally distributed measurement error are compared to those with non-normally distributed measurement errors through computer simulation.

• 산업경영시스템학회지
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• 제30권2호
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• pp.37-43
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• 2007

ANOVA is widely used for measurement system analysis. It assumes that the measurement error is normally distributed, which may not be seen in certain industrial cases. In this study, the exact and bootstrap confidence intervals for precision-to-tolerance ratio (PTR) are obtained for the cases where the measurement errors are normally and non-normally distributed and the reproducibility variation can be ignored. Lognormal and gamma distributions are considered for non-normal measurement errors. It is assumed that the quality characteristics have the same distributions of the measurement errors. Three different bootstrap methods of SB (Standard Bootstrap), PB (Percentile Bootstrap), and BCPB (Biased-Corrected Percentile Bootstrap) are used to obtain bootstrap confidence intervals for PTR. Based on a coverage proportion of PTR, a comparative study of exact and bootstrap methods is performed. Simulation results show that, for non-normal measurement error cases, the bootstrap methods of SB and BCPB are superior to the exact one.