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Goodness-of-fit Tests Comparison for Statistical Process Control in an Automotive Industrial Unit

机译：汽车工业单位中统计过程控制的拟合优度测试比较

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This paper aims to evaluate whether if the data that form several samples used for the statistical process control (SPC) control charts derive from a population with a normal distribution or not. A piece manufactured in a Portuguese small and medium-sized enterprises (SME) that operates in the automotive industry is used as an example. Knowing if the distribution is normal or not allows identifying what out of control tests should be applied and can also help finding precise false alarm rates. For this purpose, six goodness-of-fit tests are used and then compared. Some of these goodness-of-fit tests could be more sensible than others in detecting departures from normality. The results for two in three scenarios of the same dimensional feature show that some goodness-of-fit tests reject the null hypothesis and that the data of the measured samples do not derive from a population with a normal distribution.
机译：本文旨在评估形成用于统计过程控制（SPC）控制图的多个样本的数据是否来自具有正态分布的总体。以在葡萄牙从事汽车行业的中小企业（SME）制造的零件为例。知道分布是否正常可以确定应应用哪些失控测试，还可以帮助找到准确的误报率。为此，使用了六个拟合优度测试，然后进行了比较。这些拟合优度测试中的某些在检测偏离正常性方面可能比其他更明智。在具有相同维特征的三个场景中，有两个场景的结果表明，某些拟合优度检验拒绝了原假设，并且被测样本的数据并非来自具有正态分布的总体。

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