Multivariate control charts based on hybrid novelty scores

Gulanbaier Tuerhong, Seoung Bum Kim, Pilsung Kang, Sungzoon Cho

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

We propose a new nonparametric multivariate control chart that integrates a novelty score. The proposed control chart uses as its monitoring statistic a hybrid novelty score, calculated based on the distance to local observations as well as on the distance to the convex hull constructed by its neighbors. The control limits of the proposed control chart were established based on a bootstrap method. A rigorous simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compare it with existing multivariate control charts in terms of average run length (ARL) performance. The simulation results showed that the proposed control chart outperformed both the parametric and nonparametric Hotelling's T 2 control charts, especially in nonnormal situations. Moreover, experimental results with real semiconductor data demonstrated the applicability and effectiveness of the proposed control chart. To increase the capability to detect small mean shift, we propose an exponentially weighted hybrid novelty score control chart. Simulation results indicated that exponentially weighted hybrid score charts outperformed the hybrid novelty score based control charts.

Original languageEnglish
Pages (from-to)115-131
Number of pages17
JournalCommunications in Statistics: Simulation and Computation
Volume43
Issue number1
DOIs
Publication statusPublished - 2014 Jan 1

Keywords

  • Data mining
  • Multivariate control charts
  • Novelty score
  • Quality control

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation

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