Multi-scale diagnosis of spatial point interaction via decomposition of the K function-based T2 statistic

Xiaohu Huang, Qiang Zhou, Jiakun Xu

Research output: Contribution to journalArticlepeer-review

Abstract

Data in the form of spatial point distribution are commonly encountered in manufacturing processes such as nanoparticles in composite materials. By analyzing their distributional characteristics which are often related to product quality, we can monitor and diagnose the fabrication processes. Based on modeling the K function of point patterns using a Gaussian process, this paper proposes diagnosing point patterns through decomposition of the K function-based T2 statistic. The decomposition provides a novel way for independently analyzing point interactions at multiple spatial scales, which is particularly useful for fault diagnosis when the process is out of control. Effectiveness of the proposed method has been verified through several simulated examples and real data.

Original languageEnglish (US)
Pages (from-to)213-227
Number of pages15
JournalJournal of Quality Technology
Volume49
Issue number3
DOIs
StatePublished - Jul 2017

Keywords

  • Fault Diagnosis
  • Hotelling's T Control Chart
  • MYT Decomposition
  • Spatial Point Pattern
  • The K Function

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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