Case Study of Digitization of the Production Cell

  • Michal HolubEmail author
  • Zdenek Tuma
  • Jiri Kroupa
  • Jiri Kovar
  • Petr Blecha
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


This paper focuses on the introduction of digitization in the production process. When deploying Industry-Oriented 4.0 components in the plant, emphasis is placed on HMI and workplace visualization. Designing a suitable way to visualize data obtained from the production process can have a significant impact on the workplace response. Timely and properly conducted responses to potential changes in the production process have a positive impact on the resulting quality of the production process. Continuous development of the elements of virtual and augmented reality also increases their usability in the field of data visualization from the production process. These technologies make it possible to meet the high demands on the clarity of a great deal of information.

This paper introduces the creation of a production cell into virtual and augmented reality. Particular emphasis is placed on the way of data visualization, including the environment, geometric accuracy of the CNC machine tool, and information from the safety parts. For efficient information handling, access to their display in virtual and augmented reality has been chosen.

The first part of the publication introduces methods for creating a virtual model based on photogrammetry. In the second part of the publication, procedures are presented for collecting and visualizing information on the geometric accuracy of the machine. Finally, procedures related to the risk analysis and functional safety of CNC machine tools are presented. In conclusion, the advantages, disadvantages, and recommendations of the presented solution, the critical places and the difficulty with the realization of the virtual workplace are referred to.


Production cell Digitalization Industry 4.0 Virtual reality 



These results were obtained with financial support of the Faculty of Mechanical Engineering, Brno University of Technology (grant no. FSI-S-17-4477).


  1. 1.
    Blecha, P., Durakbasa, N., Holub, M.: Digitized production – its potentials and hazards. In: Proceedings of the International Symposium Production Research 2018, pp. 402–411. Springer, Cham (2019).
  2. 2.
    Ruzarovsky, R., Holubek, R., Sobrino, D.R.D., Janicek, M.: The simulation of conveyor control system using the virtual commissioning and virtual reality. Adv. Sci. Technol. J. 12, 164–171 (2018). Scholar
  3. 3.
    Kroupa, J., Tuma, Z., Kovar, J., Singule, V.: Virtual laboratory for study of construction of machine tools. MM Sci. J. 2018, 2503–2506 (2018). Scholar
  4. 4.
    Kovar, J., Mouralova, K., Ksica, F., Kroupa, J., Andrs, O., Hadas, Z.: Virtual reality in context of Industry 4.0 proposed projects at Brno University of Technology. In: Proceedings of 2016 17th International Conference Mechatronics - Mechatronika, ME 2016 (2017)Google Scholar
  5. 5.
    Holub, M., Bradac, F., Pokorny, Z., Jelinek, A.: Application of a ballbar fordiagnostics of cnc machine tools. MM Sci. J. 12, 2601–2605 (2018). Scholar
  6. 6.
    Archenti, A.: Prediction of machined part accuracy from machining system capability. CIRP Ann. 63, 505–508 (2014). Scholar
  7. 7.
    Szipka, K., Laspas, T., Archenti, A.: Measurement and analysis of machine tool errors under quasi-static and loaded conditions. Precis. Eng. 51, 59–67 (2018). Scholar
  8. 8.
    Vichare, P., Nassehi, A., Flynn, J.M., Newman, S.T.: Through life machine tool capability modelling. Procedia Manuf. 16, 171–178 (2018). Scholar
  9. 9.
    Wąsik, M., Kolka, A.: Machining accuracy improvement by compensation of machine and workpiece deformation. Procedia Manuf. 11, 2187–2194 (2017). Scholar
  10. 10.
    Belforte, G., Bona, B., Canuto, E., Donati, F., Ferraris, F., Gorini, I., Morei, S., Peisino, M., Sartori, S., Levi, R.: Coordinate measuring machines and machine tools self calibration and error correction. CIRP Ann. 36, 359–364 (1987). Scholar
  11. 11.
    Mendikute, A., Leizea, I., Yagüe-Fabra, J.A., Zatarain, M.: Self-calibration technique for on-machine spindle-mounted vision systems. Measurement 113, 71–81 (2018). Scholar
  12. 12.
    Givi, M., Mayer, J.R.R.: Validation of volumetric error compensation for a five-axis machine using surface mismatch producing tests and on-machine touch probing. Int. J. Mach. Tools Manuf 87, 89–95 (2014). Scholar
  13. 13.
    Mutilba, U., Gomez-Acedo, E., Sandá, A., Vega, I., Yagüe-Fabra, J.A.: Uncertainty assessment for on-machine tool measurement: an alternative approach to the ISO 15530-3 technical specification. Precis. Eng. (2019). Scholar
  14. 14.
    Florussen, G.H.J., Spaan, H.A.M., Spaan-Burke, T.M.: Verifying the accuracy of five-axis machine tool focused on kinematic ISO tests using a torus-shaped test work piece. Procedia Manuf. 14, 58–65 (2017). Scholar
  15. 15.
    Florussen, G.H.J., Spaan, H.A.M.: Dynamic R-test for rotary tables on 5-axes machine tools. Procedia CIRP 1, 536–539 (2012). Scholar
  16. 16.
    Brecher, C., Behrens, J., Klatte, M., Lee, T.H., Tzanetos, F.: Measurement and analysis of thermo-elastic deviation of five-axis machine tool using dynamic R-test. Procedia CIRP 77, 521–524 (2018). Scholar
  17. 17.
    Theissen, N., Laspas, T., Szipka, K., Archenti, A.: Virtual machining system simulator: analysis of machine tool accuracy. Procedia Manuf. 25, 338–343 (2018). Scholar
  18. 18.
    Fujishima, M., Ohno, K., Nishikawa, S., Nishimura, K., Sakamoto, M., Kawai, K.: Study of sensing technologies for machine tools. CIRP J. Manuf. Sci. Technol. 14, 71–75 (2016). Scholar
  19. 19.
    Augste, J., Holub, M., Knoflíček, R., Novotny, T., Vyroubal, J.: Monitoring of energy flows in the production machines. In: Mechatronics 2013, pp. 1–7. Springer, Berlin (2014). Recent Technol. Sci. Adv

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Michal Holub
    • 1
    Email author
  • Zdenek Tuma
    • 1
  • Jiri Kroupa
    • 1
  • Jiri Kovar
    • 1
  • Petr Blecha
    • 1
  1. 1.Department of Production Machines, Systems and Robotics, Faculty of Mechanical EngineeringBrno University of TechnologyBrnoCzech Republic

Personalised recommendations