With the development of modern acquisition techniques, data with several correlated quality characteristics are increasingly accessible. Thus, multivariate control charts can be employed to detect changes in the process. This study proposes two multivariate control charts for monitoring process variability (MPVC) using a progressive approach. First, when the process parameters are known, the performance of the MPVC charts is compared with some multivariate dispersion schemes. The results showed that the proposed MPVC charts outperform their counterparts irrespective of the shifts in the process dispersion. The effects of the Phase I estimated covariance matrix on the efficiency of the MPVC charts were also evaluated. The performances of the proposed methods and their counterparts are evaluated by calculating some useful run length properties. An application of the proposed chart is also considered for the monitoring of a carbon fiber tubing process.

中文翻译：

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用于协方差矩阵有效监测的多元递进控制图

随着现代采集技术的发展，具有多个相关质量特征的数据越来越容易获得。因此，可以采用多变量控制图来检测过程中的变化。本研究提出了两个多变量控制图，用于使用渐进式方法监测过程变异性 (MPVC)。首先，当工艺参数已知时，将 MPVC 图表的性能与一些多元分散方案进行比较。结果表明，无论过程分散的变化如何，所提出的 MPVC 图表都优于其对应图表。还评估了阶段 I 估计协方差矩阵对 MPVC 图表效率的影响。通过计算一些有用的运行长度属性来评估所提出的方法及其对应方法的性能。