A characterization of diagnosability conditions for variance components analysis in assembly operations

Daniel Apley*, Yu Ding

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Variance component estimation algorithms, in conjunction with automated in-process measurement technology, can be effective tools for identifying and eliminating major sources of manufacturing variation in assembly processes. Whether a particular set of variation sources are diagnosable depends critically on how the sensor system is laid out. Diagnosability tests are mathematical in nature and provide little insight into why a particular sensor layout may be nondiagnosable or how to modify the layout to ensure diagnosability. This paper translates the mathematical diagnosability conditions into a set of more conceptually meaningful conditions that provide better insight into the reasons behind the nondiagnosability.

Original languageEnglish (US)
Pages (from-to)101-110
Number of pages10
JournalIEEE Transactions on Automation Science and Engineering
Volume2
Issue number2
DOIs
StatePublished - Apr 1 2005

Keywords

  • Assembly systems
  • Fault diagnosis
  • Manufacturing variation reduction
  • Sensor layout
  • Variance component estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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