Application of expert evaluation methods in determining the significance of criteria for usability of railway traction rolling stock
Abstract
Railway rolling stock must meet the requirements related to its use in the transportation process. The significance of these requirements can be determined using expert testing methods. The current research offers a framework of 9 criteria, which have been developed by the authors of the study, and which contribute to a comprehensive assessment of their importance and priority in relation to each other using expert evaluation methods. The normalised weights of the criteria were determined using Average Rank Transformation Into Weight Linear (ARTIW-L), Average Rank Transformation Into Weight Non-linear (ARTIW-N) and Direct Percentage Weight (DPW) methods. The criteria were given ranks and percentage weights by 18 experts with consistent opinions, which made it reasonable to consider the average of the experts’ opinions as the outcome of the task. The normalised weights of the criteria have shown that the most important issues for the experts included passenger and crew safety (0.1619), passenger and train staff ride comfort (0.1330) and environmental protection (0.1201). The least important criteria for the experts cover the range per one electric charge or full tank of fuel (0.0776), the dynamic performance of the traction rolling stock (0.0849), and the purchase price, the rebate system, the duration of the warranty period (0.0911). The other 3 criteria are of medium importance. The outcomes of this study can be used in deciding on the best alternative for rail traction rolling stock.
Keyword : rail transport, traction rolling stock, serviceability criteria, weights, experts, priority
How to Cite
Maskeliūnaitė, L., Meilus, L., & Sivilevičius, H. (2023). Application of expert evaluation methods in determining the significance of criteria for usability of railway traction rolling stock. Transport, 38(2), 77–86. https://doi.org/10.3846/transport.2023.19407
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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García-Garre, A.; Gabaldón, A. 2019. Analysis, evaluation and simulation of railway diesel-electric and hybrid units as distributed energy resources, Applied Sciences 9(17): 3605. https://doi.org/10.3390/app9173605
Hamurcu, M.; Eren, T. 2022. Applications of the MOORA and TOPSIS methods for decision of electric vehicles in public transportation technology, Transport 37(4): 251–263. https://doi.org/10.3846/transport.2022.17783
Hoffrichter, A. 2013. Hydrogen as an Energy Carrier for Railway Traction. PhD Thesis. University of Birmingham, UK. 364 p. Available from Internet: https://etheses.bham.ac.uk/id/eprint/4345/9/Hoffrichter13PhD1.pdf
Hoffrichter, A.; Miller, A. R.; Hillmanser, S.; Roberts, C. 2012. Well-to-wheel analysis for electric, diesel and hydrogen traction for railways, Transportation Research Part D: Transport and Environment 17(1): 28–34. https://doi.org/10.1016/j.trd.2011.09.002
Kendall, M.; Gibbons, J. D. 1990. Rank Correlation Methods. 5th Edition. Oxford University Press. 272 p.
Li, C.; Xu, C.; Li, X. 2020. A multi-criteria decision-making framework for site selection of distributed PV power stations along high-speed railway, Journal of Cleaner Production 277: 124086. https://doi.org/10.1016/j.jclepro.2020.124086
Logan, K. G.; Nelson, J. D.; McLellan, B. C.; Hastings, A. 2020. Electric and hydrogen rail: potential contribution to net zero in the UK, Transportation Research Part D: Transport and Environment 87: 102523. https://doi.org/10.1016/j.trd.2020.102523
Madovi, O.; Hoffrichter, A.; Little, N.; Foster, S. N. Isaac, R. 2021. Feasibility of hydrogen fuel cell technology for railway intercity services: a case study for the Piedmont in North Carolina, Railway Engineering Science 29(3): 258–270. https://doi.org/10.1007/s40534-021-00249-8
Maskeliūnaitė, L. 2021. Railways in Lithuania: from tsarist Russia to Rail Baltica, Transport 36(4): 364–375. https://doi.org/10.3846/transport.2021.16086
Maskeliūnaitė, L.; Sivilevičius, H. 2021. Identifying the Importance of criteria for passenger choice of sustainable travel by train using ARTIW and IHAMCI methods, Applied Sciences 11(23): 11503. https://doi.org/10.3390/app112311503
Mastrocinque, E.; Ramírez, F. J.; Honrubia-Escribano, A.; Pham, D. T. 2020. An AHP-based multi-criteria model for sustainable supply chain development in the renewable energy sector, Expert Systems with Applications 150: 113321. https://doi.org/10.1016/j.eswa.2020.113321
Montgomery, D. C. 2012. Introduction to Statistical Quality Control. 7th Edition. Wiley. 768 p.
Peniwati, K. 2007. Criteria for evaluating group decision-making methods, Mathematical and Computer Modelling 46(7–8): 935–947. https://doi.org/10.1016/j.mcm.2007.03.005
Polater, N., Tricoli, P. 2022. Technical review of traction drive systems for light railways, Energies 15(9): 3187. https://doi.org/10.3390/en15093187
Rostamzadeh, R.; Esmaeili, A.; Sivilevičius, H.; Nobard, H. B. K. 2020. A fuzzy decision-making approach for evaluation and selection of third party reverse logistics provider using fuzzy ARAS, Transport 35(6): 635–657. https://doi.org/10.3846/transport.2020.14226
Ruf, Y.; Zorn, T.; Akcayoz De Neve, P.; Andrae, P.; Erofeeva, S.; Garisson, F. 2019. Study on the Use of Fuel Cells & Hydrogen in the Railway Environment. Report 3: Overcoming Technological and Non-Technological Barriers to Widespread Use of FCH in Rail Applications: Recommendations on Future R & I. Shift2Rail Joint Undertaking and Fuel Cells and Hydrogen Joint Undertaking. 50 p. Available from Internet: https://rail-research.europa.eu/wp-content/uploads/2019/04/Report-3.pdf
Şahin, M. 2021. Location selection by multi-criteria decision-making methods based on objective and subjective weightings, Knowledge and Information Systems 63(8): 1991–2021. https://doi.org/10.1007/s10115-021-01588-y
Shirres, D. 2020. Hydrogen trains coming soon?, Rail Engineer, 16 December 2020. Available from Internet: https://www.railengineer.co.uk/hydrogen-trains-coming-soon
Sivilevičius, H. 2011. Application of expert evaluation method to determine the importance of operating asphalt mixing plant quality criteria and rank correlation, The Baltic Journal of Road and Bridge Engineering 6(1): 48–58. https://doi.org/10.3846/bjrbe.2011.07
Sivilevičius, H.; Maskeliūnaitė, L. 2018. Multiple criteria evaluation and the inverse hierarchy model for justifying the choice of rail transport mode, Promet – Traffic & Transportation 30(1): 57–69. https://doi.org/10.7307/ptt.v30i1.2417
Sivilevičius, H.; Maskeliūnaitė, L. 2014. The numerical example for evaluating the criteria describing the quality of the trip by international train, E+M Ekonomie a Management 17(2): 73–86. https://doi.org/10.15240/tul/001/2014-2-006
Smith, K. 2020. Do hydrogen and battery trains mean the end for diesel traction?, IRJ: International Railway Journal, 2 April 2020. Available from Internet: https://www.railjournal.com/in_depth/hydrogen-and-battery-trains-end-for-diesel-traction
Sun, Y.; Anwar, M.; Hassan, N. M. S.; Spiryagin, M.; Cole, C. 2021. A review of hydrogen technologies and engineering solutions for railway vehicle design and operations, Railway Engineering Science 29(3): 212–232. https://doi.org/10.1007/s40534-021-00257-8
Šakalys, R., Sivilevičius, H., Miliauskaitė, L., Šakalys, A. 2019. Investigation and evaluation of main indicators impacting synchromodality using ARTIW and AHP methods, Transport 34(3): 300–311. https://doi.org/10.3846/transport.2019.9718