Automatic discovery of the root causes for quality drift in high dimensionality manufacturing processes

Lior Rokach, Dan Hutter

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

A new technique for finding the root cause for problems in a manufacturing process is presented. The new technique is designated to continuously and automatically detect quality drifts on various manufacturing processes and then induce the common root cause. The proposed technique consists of a fast, incremental algorithm that can process extremely high dimensional data and handle more than one root-cause at the same time. Application of such a methodology consists of an on-linemachine learning system that investigates and monitors the behavior of manufacturing product routes.

Original languageEnglish
Pages (from-to)1915-1930
Number of pages16
JournalJournal of Intelligent Manufacturing
Volume23
Issue number5
DOIs
StatePublished - 1 Oct 2012

Keywords

  • Automatic root cause discovery
  • Concept drift
  • Data mining
  • Failure analysis
  • Fault detection
  • Quality control
  • Yield improvement

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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