Application of Cluster Analysis in Making Decision About Purchase of Additional Materials for Welding Process

The concept of Industry 4.0 requires a computerized manufacturing environment which permits to increase flexibility of processes, faster communication and integration of various areas of business operation. It also involves collecting and processing a lot of information in databases. In order for an enterprise to develop, it must be able to transform this data into useful knowledge. Extraction of knowledge from datasets is made possible by Data Mining methods. The paper presents an analysis of the use of Data Mining methods in support of purchases of manufacturing materials. The practical problem of selection of fluxing agents for Submerged Arc Welding (SAW) is solved by applying cluster analysis. The authors present the results of an analysis for 213 combinations of flux-welding wire, conducted by the hierarchical (Ward method) and non-hierarchical (generalized k-means method) cluster methods. The approach proves to be suitable for aiding the decision making process.

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