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International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2015: Intelligent Data Engineering and Automated Learning – IDEAL 2015 pp 264–272Cite as

Data-Driven Simulation Model Generation for ERP and DES Systems Integration

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9375))

Abstract

In the paper the concept of data driven automatic simulation model generation method based on hybrid parametric-approach and data mapping and transformation methods in combination with concept of neutral data model is presented. As a key element of the proposed approach, author’s own method of data transformation into internal programming languages script code, based on the transformation template is described. Developed simulation model generator is also an effective tool for the integration of ERP and DES systems. A practical implementation of the presented methodology - original software RapidSim is presented as well.

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Author information

Authors and Affiliations

  1. Faculty of Mechanical Engineering, Silesian University of Technology, Gliwice, Poland

    Damian Krenczyk

  2. Faculty of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland

    Grzegorz Bocewicz

Authors
  1. Damian Krenczyk
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  2. Grzegorz Bocewicz
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Corresponding author

Correspondence to Damian Krenczyk .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology, Wroclaw, Poland

    Konrad Jackowski

  2. Department of Systems, Wroclaw University of Technology, Wroclaw, Poland

    Robert Burduk

  3. Wroclaw Univ of Tech, Wroclaw, Poland

    Krzysztof Walkowiak

  4. Wroclaw University of Technology, Faculty of Electronics, Wroclaw, Poland

    Michal Wozniak

  5. School of Electrical & Electronic E, University of Manchester, Manchester, United Kingdom

    Hujun Yin

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© 2015 Springer International Publishing Switzerland

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Krenczyk, D., Bocewicz, G. (2015). Data-Driven Simulation Model Generation for ERP and DES Systems Integration. In: Jackowski, K., Burduk, R., Walkowiak, K., Wozniak, M., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2015. IDEAL 2015. Lecture Notes in Computer Science(), vol 9375. Springer, Cham. https://doi.org/10.1007/978-3-319-24834-9_32

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  • DOI: https://doi.org/10.1007/978-3-319-24834-9_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24833-2

  • Online ISBN: 978-3-319-24834-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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