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

  • Damian KrenczykEmail author
  • Grzegorz Bocewicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9375)


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.


ERP Data-driven Simulation Visualization Data mapping Data transformation Automatic model generation 


  1. 1.
    Bzdyra, K., Banaszak, Z., Bocewicz, G.: Multiple project portfolio scheduling subject to mass customized service. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds.) Progress in Automation, Robotics and Measuring Techniques. AISC, vol. 350, pp. 11–22. Springer, Heidelberg (2015)Google Scholar
  2. 2.
    Diering, M., Dyczkowski, K., Hamrol, A.: New method for assessment of raters agreement based on fuzzy similarity. In: Herrero, A., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds.) SOCO 2015. ASIC, vol. 368, pp. 415–425. Springer, Heidelberg (2015)Google Scholar
  3. 3.
    Krenczyk, D., Skolud, B.: Transient states of cyclic production planning and control. Appl. Mech. Mater. 657, 961–965 (2014)CrossRefGoogle Scholar
  4. 4.
    Sitek, P., Wikarek J.: A hybrid approach to the optimization of multiechelon systems. Math. Probl. Eng. 2015, 12, , Article ID 925675 (2015)Google Scholar
  5. 5.
    Wójcik, R., Bzdyra, K., Crisostomo, M.M., Banaszak, Z.: Constraint programming approach to design of deadlock-free schedules in concurrent production systems. In: Proceedings of 10th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2005, vol. 1, pp. 135–142 (2005)Google Scholar
  6. 6.
    Wang, C., Liu, X.-B.: Integrated production planning and control: a multi-objective optimization model. J. Ind. Eng. Manage. 6(4), 815–830 (2013)Google Scholar
  7. 7.
    Lee, S., Son, Y.-J., Wysk, R.A.: Simulation-based planning and control: from shop floor to top floor. J. Manuf. Syst. 26(2), 85–98 (2007)CrossRefGoogle Scholar
  8. 8.
    Heilala, J., et al.: Developing simulation-based decision support systems for customer-driven manufacturing operation planning. In: Proceedings of the 2010 WSC, pp. 3363–3375 (2010)Google Scholar
  9. 9.
    Nordgren, W.B.: Steps for proper simulation project management. In: Proceedings of the 1995 Winter Simulation Conference, pp. 68–73 (1995)Google Scholar
  10. 10.
    Fowler, J.W., Rose, O.: Grand challenges in modeling and simulation of complex manufacturing systems. SIMULATION 80(9), 469–476 (2004)CrossRefGoogle Scholar
  11. 11.
    Chlebus, E., Burduk, A., Kowalski, A.: Concept of a data exchange agent system for automatic construction of simulation models of manufacturing processes. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds.) HAIS 2011, Part II. LNCS, vol. 6679, pp. 381–388. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    Wang, J., et al.: Data driven production modeling and simulation of complex automobile general assembly plant. Comput. Ind. 62(7), 765–775 (2011)CrossRefGoogle Scholar
  13. 13.
    Bergmann, S., Strassburger, S.: Challenges for the automatic generation of simulation models for production systems. In: Proceedings of the 2010 Summer Computer Simulation Conference, SCSC 2010, Ottawa, Canada, pp. 545–549 (2010)Google Scholar
  14. 14.
    Huang, Y., Seck, M.D., Verbraeck, A.: From data to simulation models: component-based model generation with a data-driven approach. In: Proceedings of the Winter Simulation Conference, WSC 2011, pp. 3724–3734 (2011)Google Scholar
  15. 15.
    Pidd, M.: Guidelines for the design of data driven generic simulators for specific domains. Simulation 59(4), 237–243 (1992)CrossRefGoogle Scholar
  16. 16.
    Krenczyk, D., Skolud, B.: Production preparation and order verification systems integration using method based on data transformation and data mapping. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds.) HAIS 2011, Part II. LNCS, vol. 6679, pp. 397–404. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  17. 17.
    Krenczyk, D., Zemczak, M.: Practical example of the integration of planning and simulation systems using the RapidSim software. Adv. Mater. Res. 1036, 1662–8985 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Faculty of Mechanical EngineeringSilesian University of TechnologyGliwicePoland
  2. 2.Faculty of Electronics and Computer ScienceKoszalin University of TechnologyKoszalinPoland

Personalised recommendations