SELF-ORGANIZING MAP NETWORK AS AN INTERACTIVE CLUSTERING TOOL - AN APPLICATION TO GROUP TECHNOLOGY

The Self-Organizing Map (SOM) network, a variation of neural computing networks, is a categorization network developed by Kohonen. The theor y 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 i t 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 te chnology. The study demonstrates the potential of using the Self-Organ izing Map as the clustering tool for part family formation in group te chnology.