Self-organizing map network as an interactive clustering tool - An application to group technology

Melody Y. Kiang, Uday Kulkarni, Kar Yan Tam

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

The Self-Organizing Map (SOM) network, a variation of neural computing networks, is a categorization network developed by Kohonen. The theory of the SOM network is motivated by the observation of the operation of the brain. This paper presents the technique of SOM and shows how it may be applied as a clustering tool to group technology. A computer program for implementing the SOM neural networks is developed and the results are compared with other clustering approaches used in group technology. The study demonstrates the potential of using the Self-Organizing Map as the clustering tool for part family formation in group technology.

Original languageEnglish (US)
Pages (from-to)351-374
Number of pages24
JournalDecision Support Systems
Volume15
Issue number4
DOIs
StatePublished - 1995

Fingerprint

Group technology
Self organizing maps
Cluster Analysis
Technology
Software
Observation
Brain
Computer program listings
Self-organizing map
Clustering
Self-organizing Map
Neural networks

Keywords

  • Clustering analysis
  • Competitive learning
  • Group technology
  • Kohonen
  • Neural networks
  • Part family formation
  • Self-organizing map

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management

Cite this

Self-organizing map network as an interactive clustering tool - An application to group technology. / Kiang, Melody Y.; Kulkarni, Uday; Tam, Kar Yan.

In: Decision Support Systems, Vol. 15, No. 4, 1995, p. 351-374.

Research output: Contribution to journalArticle

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