Evaluation of the efficiency of the delivery process in the technical object of transport infrastructure with the application of a simulation model

• Autorzy: Zabielska Aleksandra , Jacyna Marianna , Lasota Michał , Nehring Karol

Identyfikatory

DOI

10.17531/ein.2023.1.1

• Języki publikacji: EN

Abstrakty

EN

The article presents the issue of assessing the effectiveness of the implementation of a logistics process with the use of a simulation model and queue theory. The process that has been analyzed is the process of goods’ delivery at the technical object. Firstly, a literature review was carried out. Next, the authors described the process using the QT (Queueing Theory). This was possible due to the fact that QT is widely used in the analysis of systems as well as the assessment of their effectiveness, maintenance, and reliability. The description, characteristics and graphic presentation of the system in which the process is carried out have been included in the study too. Then the process was implemented in the computer simulation environment. Simulations were carried out and four variants of the system operation were analyzed. The comparison of the operating parameters of the system for each variant allowed for a detailed analysis of its operation and the influence of selected factors on the implementation of the process as well as it effectiveness or reliability.

Słowa kluczowe

EN

process efficiency; mass service system; technical object reliability; multi-element systems simulation; FlexSim simulation

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 1
• Strony: art. no. 1
• Opis fizyczny: Bibliogr. 37 poz., rys., tab., wykr.

Twórcy

autor

Zabielska Aleksandra

• Warsaw University of Technology Faculty of Transport, 75 Koszykowa str. Warsaw, Poland

• https://orcid.org/0000-0001-5192-4236

autor

Jacyna Marianna

• Warsaw University of Technology Faculty of Transport, 75 Koszykowa str. Warsaw, Poland

• https://orcid.org/0000-0002-7582-4536

autor

Lasota Michał

• Warsaw University of Technology Faculty of Transport, 75 Koszykowa str. Warsaw, Poland

• https://orcid.org/0000-0002-3090-4815

autor

Nehring Karol

• Warsaw University of Technology Faculty of Transport, 75 Koszykowa str. Warsaw, Poland

• https://orcid.org/0000-0002-0682-8795

Bibliografia

• 1. Aziziankohan, A., Jolai, F., Khalilzadeh, M., Soltani, R. Green supply chain management using the queuing theory to handle congestion and reduce energy consumption and emissions from supply chain transportation fleet. Journal of Industrial Engineering and Management 2017, 10(2): http://dx.doi.org/10.3926/jiem.2170.
• 2. Barosz, P., Gołda, G., Kampa, A. Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators. Applied Sciences 2020, 10, 2862. https://doi.org/10.3390/app10082862.
• 3. Bartholdi, J., J., Hackman, S., T. Warehouse & Distribution Science, Atlanta, V. 2016, 0.97.
• 4. Beaverstock, M.,, Greenwood, A., Nordgren, W. Applied Simulation: Modeling and Analysis Using Flexsim. 5th edition. Bookbaby, 2018.
• 5. Borucka, A., Wiśniowski, P., Mazurkiewicz, D., Świderski, A. Laboratory measurements of vehicle exhaust emissions in conditions reproducing real traffic. Measurement 2021; 174: 1-12, https://doi.org/10.1016/j.measurement.2021.108998.
• 6. Bučková, M., Krajčovič, M., Plinta, D. (2019). Use of Dynamic Simulation in Warehouse Designing. In: Burduk, A., Chlebus, E., Nowakowski, T., Tubis, A. (eds) Intelligent Systems in Production Engineering and Maintenance. ISPEM 2018. Advances in Intelligent Systems and Computing, vol 835. Springer, Cham. https://doi.org/10.1007/978-3-319-97490-3_47.
• 7. Ficoń, K., Krasnodębski, G. Suboptimalization of critical railway parametrs in massage systems. Gospodarka Materiałowa i Logistyka, 2019, 5, 31-39; https://doi.org/10.33226/1231-2037.2019.5.5.
• 8. Gołda, P., Zawisza, T., Izdebski,1 M. Evaluation of efficiency and reliability of airport processes using simulation tools. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021, 23(4): 659–669, http://doi.org/10.17531/ein.2021.4.8.
• 9. Harikrishnan, T., Jeganathan, K., Selvakumar, S., Anbazhagan, N., Cho, W., Joshi, G.P., Son, K.C. Analysis of Stochastic M/M/c/N Inventory System with Queue-Dependent Server Activation, Multi-Threshold Stages and Optional Retrial Facility. Mathematics 2022, 10, 2682. https://doi.org/10.3390/ math10152682.
• 10. Huihui, S., Xiaoxia, M., Xiangguo, M. Simulation and Optimization of Warehouse Operation Based on Flexsim. Journal of Applied Science and Engineering Innovation 2016, 3(4), 125-128.
• 11. Jacyna, M., Żak, J., Gołębiowski, P. The Use of the Queueing Theory for the Analysis of Transport Processes. Logistics and Transports 2019¸ 41(1), 101-111.
• 12. Jacyna-Gołda, I., Kłodawski, M., Lewczuk, K., Łajszczak, M., Chojnacki, T., Siedlecka-Wójcikowska, T. Elements of perfect order rate research in logistics chains. Archives of Transport 2019, 49(1), 25-35. DOI: https://doi.org/10.5604/01.3001.0013.2771.
• 13. Karkula, M. Selected aspects of simulation modelling of internal transport processes performed at logistics facilities. Archives of Transport 2014, 30(2), 43-56. https://doi.org/10.5604/08669546.1146976.
• 14. Kliment, M., Trojan, J., Pekarcíková, M., Kronová, J. Creation of simulation models using the FlexSim software module. Advanced Logistic Systems-Theory and Practice, 2022, 16 (1), 41-50. https://doi.org/10.32971/als.2022.004
• 15. Lenort, R., Grakova, E., Karkula, M., Wicher, P., Stas, D. Model for simulation of supply chain resilience, METAL 2014 - 23rd International Conference on Metallurgy and Materials, Conference Proceedings. 1803-1809.
• 16. Leończuk, D. Factors affecting the level of supply chain performance and its dimensions in the context of supply chain adaptability. Scientific Journal of Logistics 2021, 17 (2), 253-269. http://doi.org/10.17270/J.LOG.2021.584.
• 17. Lewczuk, K. The study on the automated storage and retrieval system dependability. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021, 23(4), 709-718. https://doi.org/10.17531/ein.2021.4.13.
• 18. Lewczuk, K., Kłodawski, M., Gepner, P. Energy Consumption in a Distributional Warehouse: A Practical Case Study for Different Warehouse Technologies. Energies 2021, 14, 2709. https://doi.org/10.3390/en14092709.
• 19. Liu, J., Hu, L., Xu, X., Wu, J. A queuing network simulation optimization method for coordination control of passenger flow in urban rail transit stations. Neural Comput & Applic 2021, 33, 10935–10959. https://doi.org/10.1007/s00521-020-05580-5.
• 20. Liu, T., Gong, Y., De Koster, R, B, M. Travel time models for split-platform automated storage and retrieval systems. International Journal of Production Economics, 2018; 197: 197-214, https://doi.org/10.1016/j.ijpe.2017.12.021.
• 21. Michlowicz, E., Wojciechowski, J. A method for evaluating and upgrading systems with parallel structures with forced redundancy. Eksploatacja i Niezawodnosc, 2021; 23(4): 770-6, https://doi.org/10.17531/ein.2021.4.19.
• 22. Nehring, K., Kłodawski, M., Jachimowski, R., Klimek, P., Vašek, R. Simulation analysis of the impact of container wagon pin configuration on the train loading time in the intermodal terminal. Archives of Trasnport, 2021, 60(4), 155-169. https://doi.org/10.5604/01.3001.0015.6928.
• 23. Nooraie, V., S., Parast, M., M. A multi-objective approach to supply chain risk management: Integrating visibility with supply and demand risk, 2015; 161: 192-200, https://doi.org/10.1016/j.ijpe.2014.12.024.
• 24. Pawlewski, P., Hoffa-Dabrowska, P., Golinska-Dawson, P., Werner-Lewandowska K.. FlexSim in Academe: Teaching and Research. Springer 2019.
• 25. Rece, L.; Vlase, S.; Ciuiu, D.; Neculoiu, G.; Mocanu, S.; Modrea, A. Queueing Theory-Based Mathematical Models Applied to Enterprise Organization and Industrial Production Optimization. Mathematics 2022, 10, 2520. https:// doi.org/10.3390/math10142520.
• 26. Rostami, P., Avakh Darestani, S., Movassaghi, M. Modelling Cross-Docking in a Three-Level Supply Chain with Stochastic Service and Queuing System: MOWFA Algorithm. Algorithms 2022, 15, 265. https://doi.org/10.3390/a15080265.
• 27. Ruwaida, A., Ainul, A., M. Research Advances in the Application of FlexSim: A Perspective on Machine Reliability, Availability, and Maintainability Optimization. Journal of Hunan University Natural Sciences 2021, 48(9), 517-564.
• 28. Saderova, J., Poplawski, L., Balog, M. Jr., Michalkova, S., Cvoliga, M. Layout design options for warehouse management. Polish Journal Of Management Studies 2020, DOI: 10.17512/pjms.2020.22.2.29.
• 29. Saderova, J., Rosova, A., Behunova, A., Behun, M., Sofranko, M., Khouri. S. Case study: the simulation modelling of selected activity in a warehouse operations. Wireless Networks 2022, 28: 431–440, https://doi.org/10.1007/s11276-021-02574-6.
• 30. Semenov, I, Jacyna, M. The synthesis model as a planning tool for effective supply chains resistant to adverse events. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2022, 24 (1): 140–152, http://doi.org/10.17531/ein.2022.1.16.
• 31. Szaciłło, L., Jacyna, M., Szczepański, E., Izdebski, M. Risk assessment for rail freight transport operations. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021, 23(3). 476–488, http://doi.org/10.17531/ein.2021.3.8.
• 32. Sztrik, J. Basic Queueing Theory, University of Debrecen, Faculty of Informatics 2012.
• 33. Wachnik, B.; Kłodawski, M.; Kardas-Cinal, E. Reduction of the Information Gap Problem in Industry 4.0 Projects as a Way to Reduce Energy Consumption by the Industrial Sector. Energies 2022, 15, 1108. https://doi.org/10.3390/ en15031108.
• 34. Wasiak, M., Jacyna-Gołda, I., Markowska, K., Jachimowski, R., Kłodawski, M., Izdebski, M. The use of a supply chain configuration model to assess the reliability of logistics processes. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019, 21 (3): 367–374, http://dx.doi.org/10.17531/ein.2019.3.2.
• 35. Yand, D., Wu, Y., Ma, W. Optimization of storage location assignment in automated warehouse. Microprocessors and Microsystems, 2021, 80;103356, https://doi.org/10.1016/j.micropro.2020.103356.
• 36. Zhou, Z., Dou, Y., Sun, J, Jiang, J., Tan. ,Y. Sustainable Production Line Evaluation Based on Evidential Reasoning. Sustainability 2017, 9(10), 1811. https://doi.org/10.3390/su9101811.
• 37. Żak, J., Jacyna-Gołda I. Using Queue Theory to Analysis and Evaluation of the Logistics Centre Workload. Archives of Transport, 2013, 25(1), 118-135.

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).