Abstract
Value stream mapping is the most widely used method for analyzing material and information flows in production. The first step of the method is the identification of product families, which can be suitably supported by cluster analysis. In order to evaluate the suitability of different cluster algorithms and proximity measures, this paper conducts a study based on synthetically generated test data. Seven performance measures are used to evaluate the quality of clustering solutions. Based on the results of the study, recommendations are derived for the appropriate use of cluster analysis for product family identification.
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