Automatic generation of group technology families during the part classification process

Y. B. Moon, Y. Kao

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Initial part family formation and subsequent part classification are two important problems to be addressed in applying the group technology principle. Although these two problems are closely related, they have been treated separately. As an aggregate problem, the automatic creation of new part families during the classification process, is investigated. A two-layer neural network using the adaptive resonance theory is adopted. The capability of this neural network model of dealing with the stability-plasticity dilemma is utilised in classifying the parts into families and creating new families if necessary. A heuristic algorithm using the neural network is described, with illustrative examples.

Original languageEnglish (US)
Pages (from-to)160-166
Number of pages7
JournalArchiv für Mathematische Logik und Grundlagenforschung
Volume8
Issue number3
DOIs
StatePublished - May 1993

Keywords

  • Adaptive resonance theory
  • Group technology
  • Neural networks
  • Part family formation and classification

ASJC Scopus subject areas

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

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