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Modular distributed models of production systems: a Petri nets based approach

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Języki publikacji
EN
Abstrakty
EN
Modeling and simulation are key performance analysis and control techniques to optimize decision-making as well as design and operate complex production systems. They are also indicated as one of the technological pillars of modern industry and IT solutions supporting the implementation of the roadmap toward Industry 4.0 in the areas of digital transformation and automation. In the context of the required rapid transformation of today’s enterprises, it becomes extremely important to look for solutions that allow the use of the existing infrastructure, information, and energy, so as to minimize the negative impact of new technologies and the transformation process itself on the environment. The article presents an approach to modeling large and complex production systems with the use of distributed Petri net models allowing the use of the possessed IT infrastructure as consistent with the idea of sustainable development in the activities of enterprises. This eliminates two major problems that render traditional models unusable. The first is related to the difficulties in analyzing and verifying models of enormous size and infinite space of states. The second is related to the required computing power, if such analyzes are to be performed on one computing unit, which would force the producers to replace the IT infrastructure. For this purpose, modular Petri nets are introduced. Other benefits of modularization, such as smaller components that can be independently analyzed, are also presented in the paper. The proposed modular Petri net has been implemented in the proprietary GPenSIM software. The paper is complemented by a practical example of industrial modeling of production systems with automated guided vehicles (AGVs) using the Modular Model with Intelligent Petri Modules.
Rocznik
Strony
art. no. e144621
Opis fizyczny
Bibliogr. 42 poz., rys.
Twórcy
  • University of Stavanger, Stavanger, Norway
  • Silesian University of Technology, Gliwice, Poland
  • Silesian University of Technology, Gliwice, Poland
Bibliografia
  • [1] A. Shaik, V. Rao, and C. Rao, “Development of modular manufacturing systems – a review,” Int. J. Adv. Manuf. Technol., vol. 76, pp. 789–802, 02 2015, doi: 10.1007/s00170-014-6289-2.
  • [2] A. Kusiak, “Integrated product and process design: A modularity perspective,” J. Eng. Des., vol. 13, no. 3, pp. 223–231, 2002, doi: 10.1080/09544820110108926.
  • [3] S. Singh, “Green computing strategies & challenges,” in 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), 2015, pp. 758–760, doi: 10.1109/ICGCIoT.2015.7380564.
  • [4] W. Binder and N. Suri, “Green computing: Energy consumption optimized service hosting,” in SOFSEM 2009: Theory and Practice of Computer Science, M. Nielsen, A. Kučera, P.B. Miltersen, C. Palamidessi, P. Tůma, and F. Valencia, Eds. Springer Berlin Heidelberg, 2009, pp. 117–128.
  • [5] N. Almurisi and S. Tadisetty, “Cloud-based virtualization environment for iot-based wsn: solutions, approaches and challenges,” J. Ambient Intell. Humaniz. Comput., pp. 1–23, 03 2022, doi: 10.1007/s12652-021-03515-z.
  • [6] I. Rojek, M. Macko, D. Mikołajewski, M. Sága, and T. Burczyński, “Modern methods in the field of machine modelling and simulation as a research and practical issue related to industry 4.0,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 69, no. 2, p. e136717, 2021, doi: 10.24425/bpasts.2021.136717.
  • [7] W. de Paula Ferreira, F. Armellini, and L.A. De Santa-Eulalia, “Simulation in industry 4.0: A state-of-the-art review,” Comput. Ind. Eng., vol. 149, p. 106868, 2020, doi: 10.1016/j.cie.2020.106868.
  • [8] D. Wangerin, C. DeCoro, L. Campos, H. Coyote, and I. Scherson, “A modular client-server discrete event simulator for networked computers,” in Proc. 35th Annual Simulation Symposium, 2002, pp. 125–133, doi: 10.1109/SIMSYM.2002.1000138.
  • [9] J. Patalas-Maliszewska, R. Wiśniewski, M. Topczak, and M. Wojnakowski, “Design optimization of the petri net-based production process supported by additive manufacturing technologies,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 70, no. 2, p. e140693, 2022, doi: 10.24425/bpasts.2022.140693.
  • [10] J.L. Peterson, Petri net theory and the modeling of systems. Prentice Hall PTR, 1981.
  • [11] B. Skolud, D. Krenczyk, and R. Davidrajuh, “Solving repetitive production planning problems. an approach based on activityoriented petri nets,” in International Joint Conference SOCO’16- CISIS’16-ICEUTE’16. Springer, 2016, pp. 397–407.
  • [12] R. Davidrajuh, “Design of a new modular petri nets,” in Petri Nets for Modeling of Large Discrete Systems. Springer, 2021, pp. 95–105.
  • [13] R. Davidrajuh, “A new modular petri net for modeling large discrete-event systems: a proposal based on the literature study,” Computers, vol. 8, no. 4, p. 83, 2019.
  • [14] T. Murata, “Petri nets: Properties, analysis and applications,” Proc. IEEE, vol. 77, no. 4, pp. 541–580, 1989.
  • [15] V. M. Savi and X. Xie, “Liveness and boundedness analysis for petri nets with event graph modules,” in International Conference on Application and Theory of Petri Nets. Springer, 1992, pp. 328–347.
  • [16] J. Claver, G. Harhalakis, J. Proth, V. Savi, and X. Xie, “A stepwise specification of a manufacturing system using petri nets,” drum.lib.umd.edu, Tech. Rep., 1992.
  • [17] G.G. De Jong and B. Lin, “A communicating petri net model for the design of concurrent asynchronous modules,” in 31st Design Automation Conference. IEEE, 1994, pp. 49–55.
  • [18] L.-C. Wang, “Object-oriented petri nets for modelling and analysis of automated manufacturing systems,” Comput. Integr. Manuf. Syst., vol. 9, no. 2, pp. 111–125, 1996.
  • [19] L.-C.Wang and S.-Y.Wu, “Modeling with colored timed object-oriented petri nets for automated manufacturing systems,” Comput. Ind. Eng., vol. 34, no. 2, pp. 463–480, 1998.
  • [20] S. Christensen and L. Petrucci, “Modular analysis of petri nets,” Comput. J., vol. 43, no. 3, pp. 224–242, 2000.
  • [21] G.J. Tsinarakis, N. Tsourveloudis, and K.P. Valavanis, “Modular petri net based modeling, analysis, synthesis and performance evaluation of random topology dedicated production systems,” J. Intell. Manuf., vol. 16, no. 1, pp. 67–92, 2005, doi: 10.1007/s10845-005-4825-5.
  • [22] H. Lee and A. Banerjee, “A modular petri net based architecture to model manufacturing systems exhibiting resource and timing uncertainties,” in 2009 IEEE International Conference on Automation Science and Engineering. IEEE, 2009, pp. 525–530.
  • [23] O. Bonnet-Torrès, P. Domenech, C. Lesire, and C. Tessier, “Exhost-pipe: Pipe extended for two classes of monitoring petri nets,” in International Conference on Application and Theory of Petri Nets. Springer, 2006, pp. 391–400.
  • [24] M.A. Blätke, S. Meyer, and W. Marwan, “Pain signaling-a case study of the modular petri net modeling concept with prospect to a protein-oriented modeling platform,” in Proc. of the International Workshop on Biological Processes & Petri Nets (BioPPN), satellite event of Petri Nets. Citeseer, 2011, pp. 117–134.
  • [25] C. Mahulea, J.-M. García-Soriano, and J.-M. Colom, “Modular petri net modeling of the spanish health system,” in Proc. of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012). IEEE, 2012, pp. 1–8.
  • [26] M. dos Santos Soares and J. Vrancken, “A modular petri net to modeling and scenario analysis of a network of road traffic signals,” Control Eng. Practice, vol. 20, no. 11, pp. 1183–1194, 2012.
  • [27] A. Słota, J. Zaja˛c, and M. Uthayakumar, “Synthesis of petri net based model of a discrete event manufacturing system for nonlinear process plan,” Manag. Prod. Eng. Rev., vol. 7, 2016, doi: 10.1515/mper-2016-0018 .
  • [28] R. Davidrajuh, “Distributed workflow based approach for eliminating redundancy in virtual enterprising,” J. Supercomput., vol. 63, no. 1, pp. 107–125, 2013.
  • [29] S. Berger, M. Bogenreuther, B.S. Häckel, and O. Niesel, “Modelling availability risks of it threats in smart factory networks – a modular petri net approach,” in European Conference on Information Systems (ECIS), 2019.
  • [30] R. Davidrajuh, D. Krenczyk, and B. Skolud, “Modeling production systems as modular systems: A petri nets based approach,” in Advances in Manufacturing III. Lecture Notes in Mechanical Engineering, J. Trojanowska, A. Kujawińska, J. Machado, and I. Pavlenko, Eds. Springer International Publishing, 2022, pp. 3–12.
  • [31] R. Davidrajuh, Modeling discrete-event systems with gpensim: An introduction. Springer, 2018.
  • [32] GPenSIM, “General-purpose Petri net simulator,” http://www.davidrajuh.net/gpensim, Tech. Rep., 2019, (accessed: 20 July 2020).
  • [33] B. Hrúz and M. Zhou, Modeling and control of discrete-event dynamic systems: With petri nets and other tools. Springer, 2007, vol. 59.
  • [34] R. Davidrajuh, “Models of real-life systems,” in Petri Nets for Modeling of Large Discrete Systems. Springer, 2021, pp. 29–50.
  • [35] G. Bishop, G.Welch et al., “An introduction to the kalman filter,” Proc of SIGGRAPH, Course, vol. 8, no. 27599–23175, p. 41, 2001.
  • [36] H. Li, D. Yang, H. Cao, W. Ge, E. Chen, X. Wen, and C. Li, “Data-driven hybrid petri-net based energy consumption behaviour modelling for digital twin of energy-efficient manufacturing system,” Energy, vol. 239, p. 122178, 2022.
  • [37] J. Friederich, D.P. Francis, S. Lazarova-Molnar, and N. Mohamed, “A framework for data-driven digital twins for smart manufacturing,” Comput. Ind., vol. 136, p. 103586, 2022.
  • [38] G. Tsinarakis, N. Sarantinoudis, and G. Arampatzis, “A discrete process modelling and simulation methodology for industrial systems within the concept of digital twins,” Appl. Sci., vol. 12, no. 2, p. 870, 2022.
  • [39] Y. Kim and H. Bang, Introduction to Kalman filter and its applications. A-JIN, Korea, 2018.
  • [40] A.M. da Rocha Pinto Rolim Marques, “Modeling and simulation of large discrete-event systems as Petri modules: An approach based on GPenSim,” University of Minho, Portugal, Tech. Rep., 2021, master Thesis.
  • [41] R. Davidrajuh, Petri Nets for Modeling of Large Discrete Systems. Springer, 2021.
  • [42] G. Rogers and L. Bottaci, “Modular production systems: a new manufacturing paradigm,” J. Intell. Manuf., vol. 8, no. 2, pp. 147–156, 1997.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-14895651-320e-4570-a756-0c4352fc273e
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