A Neural Network-Based Algorithm for Group Technology

Abstract

In this paper, we propose a neural network-based algorithm for grouping machine and parts in cellular manufacturing. For grouping machines, we develop similarity coefficients which take into account both similarity and dissimilarity between machines. The machine cells are formed by an algorithm which is based on the maximum neural network. Another algorithm is used to find the part families associated with each machine cell. When compared with an existing algorithm, our algorithm shows better performance in terms of grouping efficiency and grouping efficacy.