Article ID: | iaor19921695 |
Country: | United States |
Volume: | 10 |
Issue: | 1 |
Start Page Number: | 73 |
End Page Number: | 91 |
Publication Date: | Jan 1991 |
Journal: | Journal of Operations Management |
Authors: | Souza R.B.R., Bell R. |
Keywords: | statistics: multivariate |
The management of tooling systems in cell-based flexible manufacturing systems is described. The use of cluster analysis in the management of cutting tools is presented. The role and functioning of a cluster based tool management strategy is described with respect to the management of the cutting tools, scheduling of the work flow and the number of captive tools. The research findings are described and supported by an example. A Rank Order Clustering (ROC) algorithm was used, selected for its simplicity and rapid implementation, to cluster tools. The ROC algorithm is applied to cluster tools. These clusters are scheduled on work stations based on part (the primary priority) and cluster (secondary) priority management rules. This provides the dynamics of managing the change of tool clusters as well as providing for the case where resident tool clusters are desired. A spreadsheet-based computer assisted tool clustering model, intended for industrial usage, is described. The clustering model reduces the requirement for robust advance schedule generation and encourages the adoption of smaller tool magazine capacities. The cluster based model advances beyond just tool kitting to provide rapid on-line generation of tooling configurations where part mix and production ratios may be varied almost instantaneously on a spreadsheet and where rigidity in scheduling may be relaxed by allowing a tool cluster to attract any part in the cluster set. The paper concludes with a brief description of on-going research effort in applying cluster analysis to cell tool management.