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RESEARCH PAPER
Reliability and risk in the safe operation of a rail vehicle subsystem
 
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1
Department of Machine Design and Maintenance, AGH University of Krakow, Poland
 
2
Department of Rail Vehicles and Transport, Cracow University of Technology al. Jana Pawła II 37, 31-864 Kraków, Poland
 
3
Department of Electronics, Telecommunications and Mechatronics, University of Applied Sciences in Tarnow, Poland
 
 
Submission date: 2025-06-23
 
 
Final revision date: 2026-01-04
 
 
Acceptance date: 2026-01-30
 
 
Online publication date: 2026-03-01
 
 
Corresponding author
Stanisław Młynarski   

Department of Rail Vehicles and Transport, Cracow University of Technology al. Jana Pawła II 37, 31-864 Kraków, al. Jana Pawła II 37, 31-864, Kraków, Poland
 
 
 
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ABSTRACT
This study highlights the problem of modernisation using a practical example of a rail vehicle pivot and constitutes an analysis of the impact of preventive renewals on the reliability of the upgraded structural node. The damage that occurs to the rubber vibration damper and, as a consequence, to the pivot itself, is a dependent failure. The developed model takes into account the random nature of the values of the operating times to failure of the pivot and the vibration damper cooperating with it, as well as the damage relationship between them. The model also includes preventive renewals of the vibration damper performed at fixed intervals of the vehicle's mileage, as well as information on its technical condition derived from inspections performed at shorter mileage intervals. As the analysis of the risk of damage to the pivot system has shown, changing the preventive renewal period of the vibration damper makes it possible to seek an acceptable risk value for the operator and to achieve the required safety integrity level (SIL).
REFERENCES (24)
1.
Beugin J, Renaux D, Cauffriez L. A SIL quantification approach based on an operating situation model for safety evaluation in complex guided transportation systems. Reliability Engineering & System Safety 2007; 92(12): 1686–1700, https://doi.org/10.1016/j.ress....
 
2.
Braga J A P, Costa J N, Ambrósio J, Frey D, Andrade A R. Robust assessment of railway vehicle safety risks in operation using a proposed data-driven wheel profile generation approach: Design of computer experiments and surrogate models. Reliability Engineering & System Safety 2024; 249. As Published: 10.1016/j.ress.2024.110220, https://hdl.handle.net/1721.1/....
 
3.
Chen C, Wang C, Lu N, Jiang B, Xing Y. A data-driven predictive maintenance strategy based on accurate failure prognostics. Eksploatacja i Niezawodność – Maintenance and Reliability 2021; 23(2): 387–394, https://doi.org/10.17531/ein.2....
 
4.
Chen Y, Yang L, Ye C, Kang R. Failure mechanism dependence and reliability evaluation of non-repairable system. Reliability Engineering & System Safety 2015; 138: 273–283, https://doi.org/10.1016/j.ress....
 
5.
de Jonge B, Scarf P A. A review on maintenance optimization. European Journal of Operational Research 2020; 285(3): 805–824, https://doi.org/10.1016/j.ejor....
 
6.
Fang G, Pan R, Hong Y. Copula-based reliability analysis of degrading systems with dependent failures. Reliability Engineering & System Safety 2020; 193, 106618, https://doi.org/10.1016/j.ress....
 
7.
Gac P Y L, Celina M, Roux G, Verdu J, Davies P, Fayolle B. Predictive ageing of elastomers: Oxidation driven modulus changes for polychloroprene. Polymer Degradation and Stability 2016; 130: 348–355, DOI: 10.1016/j.polymdegradstab.2016.06.014.
 
8.
Gong Q, Yang L, Li Y, Xue B. Dynamic Preventive Maintenance Optimization of Subway Vehicle Traction System Considering Stages. Appl. Sci. 2022; 12 (17), doi: 10.3390/app12178617.
 
9.
Kuraś Ł M, Smolnik M. Modernisation of LEMACH 6 Design-Research Method As a Reliability Engineering Tool. Journal of KONBiN 2020; 50(2): 145–164, DOI: 10.2478/jok-2020-0032.
 
10.
Leite M, Costa M A, Alves T, Infante V, Andrade A R. Reliability and availability assessment of railway locomotive bogies under correlated failures. Eng. Fail. Anal. 2022; (135) doi: 10.1016/j.engfailanal.2022.106104.
 
11.
Młynarski S, Pilch R, Smolnik M, Szybka J. Analysis of the Modernised Railway Vehicle Component with Regard to Reliability and Operational Safety. Advances in Science and Technology Research Journal 2024; 18(3): 21–32, https://doi.org/10.12913/22998....
 
12.
Mu L, Zhang Y, Zhang Q. Risk Evaluation Method Based on Fault Propagation and Diffusion. Mathematics 2023; 11, 4083, https://doi.org/10.3390/math11....
 
13.
Piesik E, Śliwiński M, Subramanian N, Zalewski J. Concept of Multifactor Method and Non-Functional Requirements Solution to Increase Resilience through Functional Safety with Cybersecurity Analysis. Eksploatacja i Niezawodność – Maintenance and Reliability 2024; 26(3), https://doi.org/10.17531/ein/1....
 
14.
PN EN 61508 Functional safety of electrical/electronic/programmable electronic safety-related systems.
 
15.
Sakurahara T, Reihani S, Kee E, Mohaghegh Z. Global importance measure methodology for integrated probabilistic risk assessment. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 2020; 234(2): 377–396, doi:10.1177/1748006X19879316.
 
16.
Shang L, Wang H, Wu C, Cai Z. The post-warranty random maintenance policies for the product with random working cycles. Eksploatacja i Niezawodność – Maintenance and Reliability 2021; 23(4): 726–735, https://doi.org/10.17531/ein.2....
 
17.
Śliwiński M. Bezpieczeństwo funkcjonalne i ochrona informacji w obiektach i systemach infrastruktury krytycznej. Wydawnictwo Politechniki Gdańskiej, Gdańsk: 2018.
 
18.
Tayefi M, Eesaee M, Hassanipour M, Elkoun S, David E, Nguyen-Tri P. Recent progress in the accelerated aging and lifetime prediction of elastomers: A review. Polymer Degradation and Stability 2023; 214: 110379, https://doi.org/10.1016/j.poly....
 
19.
Virág L, Egedy A, Varga C, Erdős G, Berezvai S, Kovács L, Ulbert Z. Determination of the most significant rubber components influencing the hardness of natural rubber (NR) using various statistical methods. Heliyon 2024; 10 (3): e25170. doi:10.1016/j.heliyon.2024.e25170.
 
20.
Wang J. Maintenance scheduling at high-speed train depots: An optimization approach, Reliability Engineering & System Safety 2024; 243: 109809, https://doi.org/10.1016/j.ress....
 
21.
Werbińska-Wojciechowska S. Technical System Maintenance Delay-Time-Based Modelling. Springer: 2019.
 
22.
Zeng Z, Barros A, Coit D. Dependent failure behavior modeling for risk and reliability: A systematic and critical literature review, Reliability Engineering & System Safety 2023; 239, 109515, https://doi.org/10.1016/j.ress....
 
23.
Zhang Q, Fang Z, Cai J. Preventive replacement policies with multiple missions and maintenance triggering approaches. Reliability Engineering & System Safety 2021; 213, 107691, DOI: 10.1016/j.ress.2021.10769.
 
24.
Zhu H L, Liu S S, Qu Y Y, Han X X, He W, Cao Y. A new risk assessment method based on belief rule base and fault tree analysis. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 2022; 236(3): 420–438, doi:10.1177/1748006X211011457.
 
eISSN:2956-3860
ISSN:1507-2711
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