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Process Capability Analysis for NonLinear Profiles Using Depth Functions

机译:使用深度函数对非线性轮廓进行处理能力分析

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There are practical situations in which the quality of a process or product can be better characterized by a functional relationship between a response variable and one or more explanatory variables, which is called profile. Such profiles frequently can be represented adequately using linear or nonlinear models. While there are several studies in monitoring profiles, there are few studies to evaluate the capability of a process with profile quality characteristic; specifically, there is no method in the literature to analyze process capability characterized by nonlinear profiles. In this paper, we propose two methods to measure the capability of these processes, based on the concept of functional depth. These methods do not have distributional assumptions and extend to functional data the Process Capability Indexes proposed by Clements to measure the capability of a process characterized by a random variable. Performance of the proposed methods is evaluated through simulation studies. An example illustrates the applicability of these methods.
机译:在实际情况下,过程或产品的质量可以通过响应变量和一个或多个解释变量之间的函数关系更好地加以表征,这称为概要。通常可以使用线性或非线性模型适当地表示此类轮廓。虽然有许多研究监视轮廓,但是很少有研究评估具有轮廓质量特征的过程的能力。具体而言,文献中没有方法来分析以非线性轮廓为特征的过程能力。在本文中,我们基于功能深度的概念提出了两种方法来衡量这些过程的能力。这些方法没有分布假设,而是将Clements提出的过程能力指数扩展到功能数据,以衡量以随机变量为特征的过程的能力。通过仿真研究评估了所提出方法的性能。一个例子说明了这些方法的适用性。

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