Incorporating Automatic Model Checking into GPenSIM

  • Reggie Davidrajuh
  • Bozena SkoludEmail author
  • Damian Krenczyk
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 241)


Large-scale manufacturing systems involve hardware and software that are highly interconnected and complex. Unexpected failures in these systems can cause material damages and can risk human lives too. The definite way of avoiding unexpected failures is to make a model of the system and to perform model verification and validation on it. Petri nets are a highly effective way of modelling discrete-event systems. Model checking is the terminology that is used for model verification on Petri Nets. General-purpose Petri Net Simulator (GPenSIM) is a tool for modelling, simulation, performance evaluation, and control of discrete-event systems (GPenSIM: a general purpose Petri net simulator,, 2019, [15]). GPenSIM is developed by one of the authors of this chapter. This chapter explores the potentials of incorporating the model checking functions to GPenSIM. In this chapter, the problem of model checking is presented. The chapter introduces Activity-Oriented Petri Nets (AOPN) and GPenSIM for model checking of cyclic production systems.


  1. 1.
    Antunes, R., González, V.A., Walsh, K.: Identification of repetitive processes at steady- and unsteady-state: transfer function. In: Proceedings of the 23rd Annual Conference of the Int’l. Group for Lean Construction, Perth, Australia, 28–31 July 2017, pp. 793–802 (2017)Google Scholar
  2. 2.
    Araki, T., Kasami, T.: Some decision problems related to the reachability problem for Petri nets. Theor. Comput. Sci. 3(1), 85–104 (1977)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Banaszak, Z.A., Polak, M.: Deadlock-free distributed control for repetitive flows. In: Sixth International Workshop on Discrete Event Systems, Proceedings, Zaragoza, Spain, 4 October 2002, pp. 273–278. IEEE (2002)Google Scholar
  4. 4.
    Bocewicz, G., Nielsen, P., Banaszak, Z.A., Dang, V.Q.: Cyclic steady state refinement: multimodal processes perspective. In: Frick, J., Laugen, B.T. (eds.) Advances in Production Management Systems. Value Networks: Innovation, Technologies, and Management. APMS 2011, pp. 18–26. Springer, Berlin (2012)Google Scholar
  5. 5.
    Bocewicz, G., Wójcik, R., Banaszak, Z.A., Pawlewski, P.: Multimodal processes rescheduling: cyclic steady states space approach. Math. Probl. Eng. 2013 (2013)Google Scholar
  6. 6.
    Bocewicz, G., Janardhanan, M.N., Krenczyk, D., Banaszak, Z.: Traffic flow routing and scheduling in a food supply network. Ind. Manag. Data Syst. 117(9), 1972–1994 (2017)CrossRefGoogle Scholar
  7. 7.
    Cameron, A., Stumptner, M., Nandagopal, N., Mayer, W., Mansell, T.: Rule-based peer-to-peer framework for decentralised real-time service oriented architectures. Sci. Comput. Program. 97, 202–234 (2015)CrossRefGoogle Scholar
  8. 8.
    Chang, H.: A method of gameplay analysis by Petri net model simulation. J. Korea Game Soc. 15, 49–56 (2015)CrossRefGoogle Scholar
  9. 9.
    Cheng, A., Christensen, S., Mortensen, K.: Model checking coloured Petri nets – exploiting strongly connected components. DAIMI Rep. Ser. 26, 519 (1997)Google Scholar
  10. 10.
    Davidrajuh, R.: ACtivity-oriented Petri net for scheduling of resources. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Seoul, South Korea, 14–17 October 2012, pp. 1201–1206. IEEE (2012)Google Scholar
  11. 11.
    Davidrajuh, R.: Developing a Petri nets based real-time control simulator. Int. J. Simul. Syst. Sci. Technol. 12(3), 28–36 (2012)Google Scholar
  12. 12.
    Davidrajuh, R.: Outperforming genetic algorithm with a brute force approach based on activity-oriented Petri nets. In: Graña, M., López-Guede, J., Etxaniz, O., Herrero, Á., Quintián, H., Corchado, E. (eds.) International Joint Conference SOCO-16-CISIS-16-ICEUTE-16. SOCO 2016, ICEUTE 2016, CISIS 2016, pp. 454–463 (2017)Google Scholar
  13. 13.
    Davidrajuh, R.: Activity-oriented Petri nets: aligning real-world buffers with virtual places. Int. J. Simul. Syst. Sci. Technol. 18(3), 7.1–7.6 (2017)Google Scholar
  14. 14.
    Davidrajuh, R.: Modeling Discrete-Event Systems with GPenSIM. Springer, Cham (2018)CrossRefGoogle Scholar
  15. 15.
    GPenSIM: a general purpose Petri net simulator. (2019). Accessed 15 Jan 2019
  16. 16.
    Hillion, H.P., Proth, J.M.: Performance evaluation of job-shop systems using timed event graphs. IEEE Trans. Autom. Control 34(1), 3–9 (1989)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Jensen, K., Kristensen, L.M., Wells, L.: Coloured Petri nets and CPN tools for modelling and validation of concurrent systems. Int. J. Softw. Tools Technol. Transf. 9(3–4), 213–254 (2007)CrossRefGoogle Scholar
  18. 18.
    Jones, N.D., Landweber, L., Lien, Y.E.: Complexity of some problems in Petri nets. Theor. Comput. Sci. 4(3), 277–299 (1977)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Jyothi, S.D.: Scheduling flexible manufacturing system using Petri-nets and genetic algorithm. Technical report, Department of Aerospace Engineering, Indian Institute of Space Science and Technology, Thiruvananthapuram, India (2012)Google Scholar
  20. 20.
    Korbaa, O., Camus, H., Gentina, J.C.: FMS cyclic scheduling with overlapping production cycles. In: Proceedings of the International Conference on Application and Theory of Petri Nets, Workshop on Manufacturing and Petri Nets, pp. 35–52 (1997)Google Scholar
  21. 21.
    Korbaa, O., Camus, H., Gentina, J.C.: A new cyclic scheduling algorithm for flexible manufacturing systems. Int. J. Flex. Manuf. Syst. 14(2), 173–187 (2002)CrossRefGoogle Scholar
  22. 22.
    Murata, T.: Petri nets: properties, analysis and applications. Proc. IEEE 77(4), 541–580 (1989)CrossRefGoogle Scholar
  23. 23.
    Mutarraf, U., Barkaoui, K., Li, Z., Wu, N., Qu, T.: Transformation of business process model and notation models onto Petri nets and their analysis. Adv. Mech. Eng. 10(12), 1–21 (2018)CrossRefGoogle Scholar
  24. 24.
    Ohl, H., Camus, H., Castelain, E., Gentina, J.C.: A heuristic algorithm for the computation of cyclic schedules and the necessary WIP to obtain optimum cycle time. In: Proceedings of the Fourth International Conference on Computer Integrated Manufacturing and Automation Technology, Troy, NY, USA, 10–12 October 1994, pp. 339–344. IEEE (1994)Google Scholar
  25. 25.
    Szpyrka, M.: Petri Nets in Modeling and Analysis of Concurrent Systems (in Polish). WNT, Warszawa (2008)zbMATHGoogle Scholar
  26. 26.
    Valentin, C.: Modeling and analysis methods for a class of hybrid dynamic systems. In: Proceedings of ADPM ’94, Brussels, Belgium, pp. 221–226 (1994)Google Scholar
  27. 27.
    Wójcik, R.: Constraint programming approach to designing conflict-free schedules for repetitive manufacturing processes. In: Cunha, P.F., Maropoulos, P.G. (eds.) Digital Enterprise Technology, pp. 267–274. Springer, Boston (2007)CrossRefGoogle Scholar
  28. 28.
    Wójcik, R.: Designing a no-wait cyclic schedule for a class of concurrent repetitive production processes. IFAC-PapersOnLine 51(11), 1305–1310 (2018). Scholar

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Authors and Affiliations

  1. 1.Department of Electrical & Computer EngineeringUniversity of StavangerStavangerNorway
  2. 2.Faculty of Mechanical EngineeringInstitute of Engineering Processes Automation and Integrated Manufacturing Systems, Silesian University of TechnologyGliwicePoland

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