A close neighbour algorithm for designing cellular manufacturing systems

Abstract

The first step in creating a cellular manufacturing system is to identify machine groups and form part families. Clustering and data organization (CDR) algorithms (such as the bond energy algorithm) and array sorting (ARS) methods (such as the rank order clustering algorithm) have been proposed to solve the machine and part grouping problem. However, these methods do not always produce a solution matrix that has a block diagonal structure, making visual identification of machine groups and part families extremely difficult. This paper presents a ‘close neighbour algorithm’ to solve this problem. The algorithm overcomes many deficiencies of the CDR and ASM methods. The algorithm is tested against ten existing algorithms in solving test problems from the literature. Test results show that the algorithm is very reliable and efficient.