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 language | English (US) |
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Pages (from-to) | 351-374 |
Number of pages | 24 |
Journal | Decision Support Systems |
Volume | 15 |
Issue number | 4 |
DOIs | |
State | Published - Dec 1995 |
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
- Developmental and Educational Psychology
- Arts and Humanities (miscellaneous)
- Information Systems and Management