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Tytuł artykułu

Simulation tests of fleet vehicles periodic inspections timeliness: a case study

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study analyzed the case of a medium-sized workshop and the income from servicing individual customers. The management of the company observed some unused potential in the garage and plans to sign contracts with fleet customers for comprehensive maintenance of their vehicles. The key question was how many fleet vehicles could be additionally serviced without losing individual customers? In this work, a simulation model of a workshop was developed, treated as a system for queuing orders and vehicles. The model includes a subsystem of random generation of fleet vehicle mileage during the simulation. The idea of event-driven simulation and the Matlab/Simulink SimEvent environment library was used.
Rocznik
Tom
Strony
75--91
Opis fizyczny
Bibliogr. 25 poz.
Twórcy
  • Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
  • Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
Bibliografia
  • 1. Aliyu Aliyu Isah, Tukur Abdulkadir Sulaiman, Abdullahi Yusuf. 2015. “Modeling and simulation analysis of health care appointment system using ARENA”. International Journal 4(1): 1-7.
  • 2. Block Christian, Dominik Lins, Bernd Kuhlenkötter. 2018. “Approach for a simulation-based and event-driven production planning and control in decentralized manufacturing execution systems”. Procedia CIRP 72: 1351-1356.
  • 3. Buchmann Alejandro, et al. 2010. “Event-Driven services: Integrating production, logistics and transportation”. In: International Conference on Service-Oriented Computing. Springer, Berlin, Heidelberg. P. 237-241.
  • 4. Choi Byoung Kyu, Donghun Kang. 2013. Modeling and simulation of discrete event systems. John Wiley & Sons.
  • 5. Czech Piotr. 2011. „An intelligent approach to wear of piston-cylinder assembly diagnosis based on entropy of wavelet packet and probabilistic neural networks”. Communications in Computer and Information Science 239: 102-109. DOI: https://doi.org/10.1007/978-3-642-24660-9_12. Springer, Berlin, Heidelberg. ISBN: 978-3-642-24659-3. ISSN: 1865-0929. In: Mikulski Jerzy (eds), Modern transport telematics, 11th International Conference on Transport Systems Telematics, Katowice Ustron, Poland, October 19-22, 2011.
  • 6. Czech Piotr. 2013. „Diagnose car engine exhaust system damage using bispectral analysis and radial basic function”. Advances in Intelligent Systems Research 30: 312-315. DOI: https://doi.org/10.2991/iccnce.2013.78. Atlantis Press. ISBN: 978-90-78677-67-3. ISSN: 1951-6851. In: Zheng D., Shi J., Zhang L. (eds), Proceedings of the International Conference on Computer, Networks and Communication Engineering (ICCNCE), Beijing, China, May 23-24, 2013.
  • 7. Figlus T. 2019. “A method for diagnosing gearboxes of means of transport using multi-stage filtering and entropy”. Entropy 21(5): 1-13.
  • 8. Figlus T., J. Gnap, T. Skrúcaný, B. Šarkan, J. Stoklosa. 2016. „The use of denoising and analysis of the acoustic signal entropy in diagnosing engine valve clearance”. Entropy 18(7): 1-11.
  • 9. Fornasiero Rosanna, Andrea Zangiacomi, Marzio Sorlini. 2012. „A cost evaluation approach for trucks maintenance planning”. Production Planning & Control 23(2-3): 171-182.
  • 10. García Juan Martín. 2020. Theory and practical exercises of system dynamics: modeling and simulation with Vensim PLE. Preface John Sterman. System Dynamic Group. MIT Sloan School Management.
  • 11. Goyal Suresh K., A. Gunasekaran. 1992. “Determining economic maintenance frequency of a transport fleet”. International Journal of Systems Science 23(4): 655-659.
  • 12. Jalel Ben Othman, et al. 2021. “Queuing theory based simulation model for vehicular mobility”. In: ICC 2021-IEEE International Conference on Communications. IEEE. P. 1-6.
  • 13. Jilcha Kassu, Esheitie Berhan, Hannan Sherif. 2015. “Workers and Machine Performance Modeling in Manufacturing System Using Arena Simulation”. Journal of Computer Science & Systems Biology 8(4): 185.
  • 14. Kozłowski E., K. Antosz, D. Mazurkiewicz, J. Sęp, T. Żabiński. 2021. „Integrating advanced measurement and signal processing for reliability decision-making”. Eksploatacja i Niezawodnosc – Maintenance and Reliability 23(4): 777-787.
  • 15. Małopolski Waldemar, et al. 2012. “Modeling and optimization of manufacturing systems using Arena software”. Czasopismo Techniczne. Mechanika 8-M(22): 91-108.
  • 16. Marseguerra Marzio, Enrico Zio. 2000. “Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation”. Reliability Engineering & System Safety 68(1): 69-83.
  • 17. Michalski R., S. Wierzbicki. 2008. „An analysis of degradation of vehicles in operation”. Eksploatacja i Niezawodnosc – Maintenance and Reliability 1: 30-32.
  • 18. Mickūnaitis V., S. Nagurnas. 2002. „The improvement of the technical exploitation of automobiles”. Transport 17(4): 143-146. DOI: ttps://doi.org/10.3846/16483840.2002.10414031.
  • 19. Raposo Hugo, et al. 2021. “An Integrated Model for Dimensioning the Reserve Fleet based on the Maintenance Policy”. WSEAS transactions on systems and control 16: 43-65.
  • 20. Rudyk Tomasz, Emilian Szczepański, Marianna Jacyna. 2019. „Safety factor in the sustainable fleet management model”. Archives of Transport 49: 103-114.
  • 21. Shamsuddoha Mohammad, Alexandru Mircea Nedelea. 2013. “A Vensim based analysis for supply chain model”. Ecoforum Journal 2(2): 8.
  • 22. Valigura K., M. Foltin, M. Blaho. 2009. “Transport system realization in simevents tool”. Technical Computing Prague.
  • 23. Wainer Gabriel A., Pieter J. Mosterman (ed.). 2018. Discrete-event modeling and simulation: theory and applications. CRC press,
  • 24. Wang Yali, et al. 2019. “Vehicle fleet maintenance scheduling optimization by multi-objective evolutionary algorithms”. In: 2019 IEEE congress on evolutionary computation (cec). IEEE. P. 442-449.
  • 25. Zhang Yue, et al. 2017. “A simevents model for hybrid traffic simulation”. In: 2017 Winter Simulation Conference (WSC). IEEE. P. 1455-1466.
Uwagi
PL
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-29d08930-d45e-4334-aa82-f2516d4a3591
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