Part family formation by memory association

Y. Kao, Y. B. Moon

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Most of the part family formation methods are concerned with "how to form" the families as opposed to "how to identify" the families. However, a more appropriate approach would be to identify "naturally occurring" families since these methods are based on the production flow analysis, which uses already implemented routing data. This paper presents a new approach using the memory association of neural networks to identify naturally existing families. The developed system, Feature-Based Memory Association Network (FBMAN), operates by the exhaustive association approach which deals with the difficult problem of exceptional parts. Comparison with the results generated by other methods proves the effectiveness of FBMAN.

Original languageEnglish (US)
Pages (from-to)649-657
Number of pages9
JournalInternational Journal of Advanced Manufacturing Technology
Volume13
Issue number9
DOIs
StatePublished - Jan 1 1997

Keywords

  • Group technology
  • Neural networks
  • Part family formation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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