Forming part-machine families for cellular manufacturing: A neural-network approach

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


This paper presents a new approach to forming group-technology part families for cellular manufacturing. The approach is based on neural-network technology, which mimics the way biological brain neurons perform to generate intelligent decisions. A procedure of forming part families using parallel and simple artificial neurons is described with examples. The implications and advantages of using neural networks in group technology are discussed.

Original languageEnglish (US)
Pages (from-to)278-291
Number of pages14
JournalArchiv für Mathematische Logik und Grundlagenforschung
Issue number4
StatePublished - Nov 1990
Externally publishedYes


  • Competition model
  • Group technology
  • Interactive activation
  • 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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