Adaptive nonparametric control chart for time-varying and multimodal processes

作者：Kang Ji Hoon; Yu Jaehong; Kim Seoung Bum^*

来源：Journal of Process Control, 2016, 37: 34-45.

DOI：10.1016/j.jprocont.2015.11.005

• Clustering
• Data mining algorithm
• Multivariate control chart
• Multimodality
• Time-varying process
• False alarms

Multivariate statistical process control techniques have been widely used to improve processes by reducing variation and preventing defects. In modern manufacturing, because of the complexity and variability of processes, traditional multivariate control charts such as Hotelling's T-2 cannot efficiently handle situations in which the patterns of process observations are nonlinear, multimodal, and time varying. In the present study, we propose a nonparametric control chart, which is capable of adaptively monitoring time-varying and multimodal processes. Experiments with simulated and real process data from a thin film transistor-liquid crystal display (TFT-LCD) demonstrate the effectiveness and accuracy of the proposed method.

• 出版日期2016-1
• 单位rutgers