An improved clustering heuristic in cellular manufacturing systems

This paper presents a construction heuristic in cellular manufacturing systems with the objective of maximising grouping efficacy. The proposed method is derived from three criteria, namely, Pearson correlation coefficient, the concentration of operations for a particular machine cell pair or a part family pair, and the density of operations for a particular machine-part cell comprising a machine cell and a part family. The proposed method consists of two phases. In the first phase, the machine-groups and part-families are constructed using Pearson correlation coefficient clustering technique. The second phase involves in selecting the machine-groups and part-families to build the respective machine-part cells to cluster machines and parts into the corresponding machine-groups and part families for the cellular manufacturing problem. The exhaustive computational results based on a set of different benchmark problem instances demonstrate that the proposed method is relatively superior to some well-known state-of-the-art methods.