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首页> 外文期刊>Quality and Reliability Engineering International >COMPUTING PROCESS CAPABILITY INDICES FOR NON-NORMAL DATA: A REVIEW AND COMPARATIVE STUDY
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COMPUTING PROCESS CAPABILITY INDICES FOR NON-NORMAL DATA: A REVIEW AND COMPARATIVE STUDY

机译：计算非标准数据的过程能力指数：回顾与比较研究

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摘要

When the distribution of a process characteristic is non-normal ,C_pk and C_pk calculated using conventional methods often lead to erroneous interpretation of the process's capability. Though various methods have been proposed for computing surrogate process capability indices(PCIs) under non-normality ,there is a lack of literature that covers a comprehensive evaluation and comparison of these methods. In particular, under mild and severe departures form normality, do these surrogate PCIs adequately capture process capability, and which is the best method(s) in reflecting the true capability under each of these circumstances? In this paper we review seven methods that are chosen for performance comparison in their ability to handle non-normality in PCIs.For illustration purposes the comparison is done through simulating Weibull and lognormal data, and the results are presented using box plots. Simulation results show that the performance of a method is dependent on its capability to capture the tail behavior of the underlying distributions. Finally we give a practitioner's guide that suggests applicable methods for each defined range of skewness and kurtosis under mild and severe departures from normality.
机译：当过程特征的分布不正常时，使用常规方法计算的C_pk和C_pk通常会导致对过程能力的错误解释。尽管已经提出了多种方法来计算非正态下的替代过程能力指数（PCI），但仍缺乏有关这些方法的综合评估和比较的文献。尤其是在正常情况下出现轻度和严重偏离时，这些替代PCI是否能充分捕获过程能力，哪种是在每种情况下反映真实能力的最佳方法？在本文中，我们回顾了选择用于性能比较的7种方法在PCI中处理非正态性的能力。出于说明目的，通过模拟Weibull和对数正态数据进行了比较，并使用箱形图展示了结果。仿真结果表明，方法的性能取决于其捕获基础分布的尾部行为的能力。最后，我们提供了一份从业指南，为在轻度和严重偏离正常值的情况下针对偏斜和峰度的每个定义范围提出了适用的方法。

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