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A High-dimensional Control Chart for Profile Monitoring

机译:用于轮廓监控的高维控制图

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Profile monitoring is an important and rapidly emerging area of statistical process control. In many industries, the quality of processes or products can be characterized by a profile that describes a relationship or a function between a response variable and one or more independent variables. A change in the profile relationship can indicate a change in the quality characteristic of the process or product and, therefore, needs to be monitored for control purposes. We propose a high-dimensional (HD) control chart approach for profile monitoring that is based on the adaptive Neyman test statistic for the coefficients of discrete Fourier transform of profiles. We investigate both linear and nonlinear profiles, and we study the robustness of the HD control chart for monitoring profiles with stationary noise. We apply our control chart to monitor the process of nonlinear woodboard vertical density profile data of Walker and Wright (J. Qual. Technol. 2002; 34:118-129) and compare the results with those presented in Williams et al. (Qual. Reliab. Eng. Int. 2007; to appear). Copyright © 2010 John Wiley & Sons, Ltd.
机译:概要文件监视是统计过程控制的重要且迅速兴起的领域。在许多行业中,过程或产品的质量可以由描述响应变量与一个或多个自变量之间的关系或功能的配置文件来表征。轮廓关系的变化可以指示过程或产品的质量特征发生变化,因此,出于控制目的需要对其进行监视。我们提出了一种用于轮廓监测的高维(HD)控制图方法,该方法基于对轮廓的离散傅立叶变换系数的自适应Neyman测试统计量。我们研究了线性和非线性轮廓,并研究了HD控制图用于监测具有固定噪声的轮廓的鲁棒性。我们应用我们的控制图来监视Walker和Wright的非线性木板垂直密度分布数据的过程(J. Qual。Technol。2002; 34:118-129),并将结果与​​Williams等人提供的结果进行比较。 (Qual。Reliab。Eng。Int。2007;出现)。版权所有©2010 John Wiley&Sons,Ltd.

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