Neural network-based design of cellular manufacturing systems Academic Article uri icon

abstract

  • A neural network based on a competitive learning rule, when trained with the part machine incidence matrix of a large number of parts, classifies the parts and machines into part families and machine cells, respectively. This classification compares well with the classical clustering techniques. The steady state values of the activations and interconnecting strengths enable easier identification of the part families, machine cells, overlapping parts and bottleneck machines. Neural networks are mostly applied by treating them as a blackbox, i.e. the interaction with the environment and the information acquisition and retrieval occurs at the input and the output level of the network. This paper presents an approach where knowledge is extracted from the external and internal structure of the neural network. 1991 Chapman & Hall.

published proceedings

  • Journal of Intelligent Manufacturing

author list (cited authors)

  • Malav, C. O., & Ramachandran, S.

citation count

  • 59

complete list of authors

  • Malavé, César O||Ramachandran, Satheesh

publication date

  • January 1991