Process control of time-varying systems using parameter-less self-organizing maps. (April 2017)

• Record Type: Journal Article
• Authors: Choung, Young Jae; Kang, Jihoon; Kim, Seoung Bum
• Is Part Of: Journal of process control. Volume 52(2017)
• Page Start: 45
• Page End: 56
• Publication Date: 2017-04
• Subjects: Multivariate process control -- Control chart -- Self-organizing map -- Time-varying process -- Data mining -- Machine learning; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2017.02.005
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: We propose a process control technique based on a self organizing map. Proposed technique can monitor both the time-varying and nonlinear processes. Proposed technique reduced false alarms significantly in time-varying situations. We examine the stability of proposed technique with a case study from TFT-LCD process. Abstract: Traditional control charts, such as Hotelling's T 2, are effective in detecting abnormal patterns. However, most control charts do not take into account a time-varying property in a process. In the present study, we propose a parameter-less self-organizing map-based control chart that can handle a situation in which changes occur in the distribution or parameter of the target observations. The control limits of the proposed chart are determined by estimating the empirical level of significance on the percentile using the bootstrap method. Experimental results obtained by using simulated data and actual process data from the manufacturing process for a thin-film transistor-liquid crystal display demonstrate the effectiveness and usefulness of the proposed algorithm.