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

Authors:
Melody Y. Kiang;Uday R. Kulkarni;Kar Yan Tam
Affiliations:
Department of Decision and Information Systems, College of Business, Arizona State University, Tempe, AZ 85287, USA;Department of Decision and Information Systems, College of Business, Arizona State University, Tempe, AZ 85287, USA;Department of Business Information Systems, School of Business and Management, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
Venue:
Decision Support Systems
Year:
1995

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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.