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The Residual T2 Control Chart of the Multivariate Heteroskedasticity Process with Trend Patterns

机译:趋势模式的多元异方差过程的残余T2控制图

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Statistical process control(SPC) is widely used to improve the product quality. The quality of a product can be attributed to several correlated quality characteristics, all of which need to be controlled and monitored simultaneously. Linear trends in processes are usually due to some type of process decay, such as the wearing out of a tool, where there is often heteroskedasticity. In this paper, the models of the residuals of the process with heteroskedasticity are fitted using Glejser test method which can test the increasing or decreasing heteroskedasticity of the process, which can distinguish three kinds of variables in the processes. Then, the identically independent random residuals after eliminating the linear trend and heteroskedasticity can be controlled by the multivariate T2 control chart. At the end, the axis diameter and surface roughness in the tool wear process are analyzed with the residual T2 control chart proposed.
机译:统计过程控制(SPC)被广泛用于提高产品质量。产品的质量可以归因于几个相关的质量特征,所有这些特征都需要同时进行控制和监视。过程中的线性趋势通常是由于某种类型的过程衰减所致,例如工具磨损,其中经常存在异方差。本文采用Glejser检验方法拟合了异方差过程的残差模型,该模型可以检验过程的异方差的增加或减少,可以区分过程中的三种变量。然后,可以通过多元T2控制图来控制消除线性趋势和异方差之后的相同独立的随机残差。最后,通过提出的残余T2控制图分析了刀具磨损过程中的轴直径和表面粗糙度。

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