Process control of time-varying systems using parameter-less self-organizing maps

Young Jae Choung, Jihoon Kang, Seoung Bum Kim

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Traditional control charts, such as Hotelling's T2, 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.

Original languageEnglish
Pages (from-to)45-56
Number of pages12
JournalJournal of Process Control
Volume52
DOIs
Publication statusPublished - 2017 Apr 1

Keywords

  • Control chart
  • Data mining
  • Machine learning
  • Multivariate process control
  • Self-organizing map
  • Time-varying process

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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