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Data Mining Model Building as a Support for Decision Making in Production Management

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 166))

Abstract

The paper gives the next stages of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. Production data was obtained in previous stages of project. This production data are stored in data warehouse that was proposed and developed by authors. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The main focus of our article is the proposal of data mining model.

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References

  1. Vazan, P., Kebisek, M., Tanuska, P., Jurovata, D.: The data warehouse suggestion for production system. In: Annals of DAAAM and Proceedings of DAAAM Symposium, Vienna, Austria, vol. 22(1), pp. 0017–0018 (2011) ISBN 978-3-901509-83-4

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Correspondence to Pavol Tanuska .

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Tanuska, P., Vazan, P., Kebisek, M., Moravcik, O., Schreiber, P. (2012). Data Mining Model Building as a Support for Decision Making in Production Management. In: Wyld, D., Zizka, J., Nagamalai, D. (eds) Advances in Computer Science, Engineering & Applications. Advances in Intelligent and Soft Computing, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30157-5_69

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  • DOI: https://doi.org/10.1007/978-3-642-30157-5_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30156-8

  • Online ISBN: 978-3-642-30157-5

  • eBook Packages: EngineeringEngineering (R0)

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