An automatic clustering algorithm suitable for use by a computer-based tool for the design, management and continuous improvement of cellular manufacturing systems

As part of the development of Collect, a tool for the design, management and continuous improvement of cellular manufacturing systems, a need was identified for a fully automatic clustering algorithm that takes the information it needs from the Celled database, carries out clustering and returns the cell configurations back to the user for further analysis; all without user interaction. To achieve this, an algorithm called Black Box Clustering was created. This is a modified End Load Ratio algorithm aided by the use of similarity coefficients that carry out rearrangement of a workstation-part matrix to obtain a block diagonal form which is marked off to identify workstation groups and part families. This paper describes the development of Black Box Clustering and demonstrates that when tested, the algorithm was shown to be effective and versatile.