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

  • Agnieszka Kujawińska
  • Michał RogalewiczEmail author
  • Marcin Muchowski
  • Magdalena Stańkowska
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 213)

Abstract

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.

Keywords

Data mining Cluster analysis Generalized k-means method Ward method Welding process 

Notes

Acknowledgements

The presented results derive from a scientific statutory research conducted by Chair of Management and Production Engineering, Faculty of Mechanical Engineering and Management, Poznan University of Technology, Poland, supported by the Polish Ministry of Science and Higher Education from the financial means in 2017.

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.Poznań University of TechnologyPoznańPoland

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