Application of Fuzzy Logic Controller for Machine Load Balancing in Discrete Manufacturing System

  • Grzegorz Kłosowski
  • Arkadiusz GolaEmail author
  • Antoni Świć
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9375)


The paper presents a concept of control of discrete manufacturing system with the use of fuzzy logic. A controller based on the concept of Mamdani was developed. The primary function realized by the controller was the balancing of machine tool loads taking into account the criteria of minimisation of machining times and costs. Two models of analogous manufacturing systems were developed, differing in the manner of assignment of production tasks to machine tools. Simulation experiments were conducted on both models and the results obtained were compared. In effect of the comparison of the results of both experiments it was demonstrated that better results were obtained in the system utilising the fuzzy inference system.


Simulation Modelling Control Fuzzy logic Manufacturing system 


  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.
    Kádár, B., Terkaj, W., Sacco, M.: Semantic virtual factory supporting interoperable modelling and evaluation of production systems. CIRP Ann. Manuf. Technol. 62(1), 443–446 (2013)CrossRefGoogle Scholar
  3. 3.
    Azadegan, A., Porobic, L., Ghazinoory, S., Samouei, P., Kheirkhah, A.S.: Fuzzy logic in manufacturing: a review of literature and a specialized application. Int. J. Prod. Econ. 132, 258–270 (2011)CrossRefGoogle Scholar
  4. 4.
    Sitek, P., Wikarek, J.: A hybrid approach to the optimization of multiechelon systems. Math. Probl. Eng. 2015, 12 (2015)CrossRefGoogle Scholar
  5. 5.
    Gola, A., Świć, A.: Computer-aided machine tool selection for focused flexibility manufacturing systems using economical criteria. Actual Probl. Econ. 124(10), 383–389 (2011)Google Scholar
  6. 6.
    Relich, M., Śwíc, A., Gola, A.: A knowledge-based approach to product concept screening. In: Omatu, S., Malluhi, Q.M., Gonzalez, S.R., Bocewicz, G., Bucciarelli, E., Giulioni, G., Iqba, F. (eds.) Distributed Computing and Artificial Intelligence, 12th International Conference. AISC, vol. 373, pp. 341–348. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  7. 7.
    Kłosowski, G., Gola, A., Świć, A.: Human resource selection for manufacturing system using petri nets. Appl. Mech. Mater. 791, 132–140 (2015)CrossRefGoogle Scholar
  8. 8.
    Filev, D., Syed, F.: Applied intelligent systems: blending fuzzy logic with conventional control. Int. J. Gen Syst 39(4), 395–414 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Onut, S., Kara, S., Mert, S.: Selecting the suitable material handling equipment in the presence of vagueness. Int. J. Adv. Manuf. Technol. 44(7–8), 818–828 (2009)CrossRefGoogle Scholar
  10. 10.
    Naumann, A., Gu, P.: Real-time part dispatching within manufacturing cells using fuzzy logic. Prod. Plann. Control 8(7), 662–669 (1997)CrossRefGoogle Scholar
  11. 11.
    Chan, F., Chan, H., Kazerooni, A.: Real time fuzzy scheduling rules in FMS. J. Intell. Manuf. 14(3–4), 341–350 (2003)CrossRefGoogle Scholar
  12. 12.
    Karatopa, B., Kubatb, C., Uygunb, Ö.: Talent management in manufacturing system using fuzzy logic approach. Comput. Ind. Eng. 86, 127–136 (2014)CrossRefGoogle Scholar
  13. 13.
    Kłosowski, G.: Artificial intelligence techniques in cloud manufacturing. In: Bojanowska, A., Lipski, J., Świć, A. (eds.) Informatics methods as tools to solve industrial problems, pp. 7–19. Lublin University of Technology, Lublin (2012)Google Scholar
  14. 14.
    Nedjah, N., de Macedo Mourelle, L.: Fuzzy Systems Engineering. Springer, Heidelberg (2006)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Grzegorz Kłosowski
    • 1
  • Arkadiusz Gola
    • 1
    Email author
  • Antoni Świć
    • 2
  1. 1.Faculty of Management, Department of Enterprise OrganizationLublin University of TechnologyLublinPoland
  2. 2.Faculty of Mechanical Engineering, Institute of Technological Systems of InformationLublin University of TechnologyLublinPoland

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