M.N. Belozerov1

1 Federal State Autonomous Educational Institution of Higher Education "National Research Technological University "MISIS" (Moscow, Russia)
1 mnbelozyorov@gmail.com

Simulation modeling is a decision support tool for operational production management and planning of production processes. At the same time, production processes have a formal description in the form of a system of logical rules. The purpose of the study is to develop a method for analyzing a system of logical rules describing production processes using the mathematical formalism of Petri nets. Results.  Each production process is considered at some level of abstraction as a separate nodal element, the structure and functions of which are described using Petri nets. The analysis of the results of modeling production processes based on the construction of a graph of the reachability of the Petri net allows you to make rational decisions taking into account the assessment of possible scenarios.  Thus, verification and analysis of the simulation model makes it possible to identify bottlenecks for making recommendations and correcting the functionality of nodal elements.  Practical significance. The proposed approach allows you to create dynamic models from static rules and obtain effective solutions for creating new and improving existing production processes. As a result of the coordinated adjustment of interconnected nodal elements in the design process of industrial enterprises and productions, it is possible to create complex logistics and production chains. Also, the proposed tools contribute to the organization of new production systems with optimization of their functioning before commissioning.

Belozerov M.N. An integrated approach to the planning of production processes based on the methodology of simulation modeling. Information-measuring and Control Systems. 2025. V. 23. № 1. P. 68−73. DOI: https://doi.org/10.18127/j20700814-202501-08 (in Russian)

1. Zurawski R., Zhou M.C. Petri nets and industrial applications: A tutorial. IEEE Transactions on industrial electronics. 1994. V. 41. № 6. Р. 567–583.
2. Orlov S.P., Susarev S.V., Uchaikin R.A. Application of Hierarchical Colored Petri Nets for Technological Facilities’ Maintenance Process Evaluation. Applied Sciences. 2021. V. 11. № 11. Р. 5100.
3. Van Der Aalst W.M.P. Making work flow: On the application of petri nets to business process management / International conference on application and theory of Petri nets. Berlin, Heidelberg: Springer Berlin Heidelberg. 2002. Р. 1–22.
4. Leemans S.J.J., Maggi F.M., Montali M. Reasoning on labelled petri nets and their dynamics in a stochastic setting / International Conference on Business Process Management. Cham: Springer International Publishing. 2022. Р. 324–342.
5. Han D., Tian Y. Analysis and application of transition systems based on Petri nets and relation matrices to business process management. Mathematical Problems in Engineering. 2020. V. 2020. № 1. Р. 2545413.
6. Ghilardi S. et al. Petri nets with parameterised data: Modelling and verification. Business Process Management: 18th International Conference, BPM 2020, Seville, Spain, September 13–18, 2020, Proceedings 18. Springer International Publishing. 2020. Р. 55–74.
7. Fang H. et al. An approach for identifying the abstraction scopes of business process Petri nets system using binary search tree. International Journal of Services Technology and Management. 2020. V. 26. № 2-3. Р. 149–166.
8. Liu C. et al. Formal modeling and discovery of hierarchical business processes: A petri net-based approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2022. V. 53. № 2. Р. 1003–1014.
9. Zhang M. et al. A new business process verification approach for e-commerce using petri nets. International Journal of Enterprise Information Systems (IJEIS). 2020. V. 16. № 1. Р. 92–107.
10. van der Aalst W.M.P. Using free-choice nets for process mining and business process management / 2021 16th Conference on Computer Science and Intelligence Systems (FedCSIS). IEEE. 2021. Р. 9–15.
11. Zeng Q., Duan H., Liu C. Top-down process mining from multi-source running logs based on refinement of Petri nets. IEEE Access. 2020. V. 8. Р. 61355–61369.
12. Xiang D. et al. Checking missing-data errors in cyber-physical systems based on the merged process of Petri nets. IEEE Transactions on Industrial Informatics. 2022. V. 19. № 3. Р. 3047–3056.
13. Lo Bianco R. et al. Action-evolution petri nets: a framework for modeling and solving dynamic task assignment problems / International Conference on Business Process Management. Cham: Springer Nature Switzerland. 2023. Р. 216–231.
14. Liu C. et al. Petri net based data-flow error detection and correction strategy for business processes. IEEE Access. 2020. V. 8. Р. 43265–43276.
15. Ben Mesmia W., Escheikh M., Barkaoui K. DevOps workflow verification and duration prediction using non‐Markovian stochastic Petri nets. Journal of Software: Evolution and Process. 2021. V. 33. № 3. Р. E2329.
16. Unruh E., Delfmann P., Thimm M. Quantitative deadlock analysis in petri nets using inconsistency measures / 2021 IEEE 23rd Conference on Business Informatics (CBI). IEEE. 2021. V. 1. Р. 42–51.
17. David R. et al. Timed continuous petri nets. Discrete, Continuous, and Hybrid Petri Nets. 2010. Р. 159–229.