The railway operation process evaluation method in terms of resilience analysis

Authors

  • Franciszek Restel Wroclaw University of Science and Technology, Discipline of Mechanical Engineering, Department of Technical Systems Operation and Maintenance Author

DOI:

https://doi.org/10.5604/01.3001.0014.7485

Keywords:

railway, resilience, performance, Fuzzy Logic, security, occurrence of accidents, unwanted event

Abstract

In complex socio-technical systems there is an influence of safe unwanted events on the occurrence of accidents. It is like domino bricks. Therefore, it is not only the recovery from major events that is important, but also the recovery from disruptions in operation. As the literature review shows, the recovery of operation processes is analysed by single criterions for small disruptions. On the other hand, resilience research is focused on the network and major events, but not on frequent small-consequence events that affect operational processes. The performance of a system is a key parameter when evaluating resilience. As a result of the performed literature survey, the aim of the paper was to propose a new method for evaluating performance in terms of operational processes and resilience analysis. Moreover, it is also important to order the most important terms related to this issue, as well as to introduce new types of qualities, which are not only focused on the system, but also on the implemented operational processes. The paper consists of eight sections. The introduction section describes generally the problem, that leads to formulation of the aim of the paper and description of its structure. It is followed by the second section consisting of a complex literature survey. Section three orders the reliability, robustness and resilience definitions. Section four analyses the performance influencing factors using Fault and Event Tree Analysis, while section five defines the operational layer of the system and shows a formal description of operation processes. Section six presents the operation process evaluation model. It was elaborated using the Fuzzy Logic approach, that allows combining of incoherent system and process qualities: punctuality, probability no further delays, quantitative implementation of scheduled processes, reconfiguration level. Afterwards a case study is shown to present the method application. The performed case study shows the advantages of the proposed approach, which is related to the most common methods. The paper ends with conclusions and further research perspectives.

References

AL KHALED, A., JIN, M., LI, L., 2011. Evaluating Criticality of Railway Links Based on Freight Flow Network Optimization. IIE Annual Conference. Proceedings, 2011, 1-8.

ALIPOUR, A., SHAFEI, B., 2016. Seismic Resilience of Transportation Networks with Deteriorating Components. Journal of Structural Engineering. 142. C4015015.10.1061/(ASCE) ST.1943-541X.0001399.

ANDERSSON ET AL. 2013 ANDERSSON, E.V., PETERSON, A, TÖRNQUIST KRASEMANN, J., 2013. Quantifying railway timetable robustness in critical points. Journal of Rail Transport Planning and Management, 3(3), 95-110; doi.org/10.1016/j.jrtpm.2013.12.002.

ARGYROUDIS, S.A., MITOULIS, S.A., HOFER, L., ZANINI, M.A., TUBALDI, E., FRANGOPOL, D.M., 2020. Resilience assessment framework for critical infrastructure in a multihazard environment: Case study on transport assets. Science of The Total Environment, 714, 136854, ISSN 0048-9697; https://doi.org/10.1016/j.scitotenv.2020.136854.

AZAD, N., HASSINI, E., VERMA, M., 2016. Disruption risk management in railroad networks: An optimization-based methodology and a case study. Transportation Research Part B: Methodological, 85, 70-88, ISSN 0191-2615; https://doi.org/10.1016/j.trb.2016.01.001.

BALAL, E., VALDEZ, G., MIRAMONTES, J., CHEU, R.L., 2019. Comparative evaluation of measures for urban highway network resilience due to traffic incidents. International Journal of Transportation Science and Technology, 8(3), 304-317, ISSN 2046-0430; https://doi.org/10.1016/j.ijtst.2019.05.001.

BIROLINI, A., 2017. Basic Concepts, Quality and Reliability (RAMS) Assurance of Complex Equipment and Systems. Reliability Engineering. Springer, Berlin, Heidelberg; https://doi.org/10.1007/978-3-662-54209-5_1.

BÜCHEL, B., CORMAN, F., 2018. Modelling probability distributions of public transport travel time components. Paper presented at the 18th Swiss Transport Research Conference (STRC 2018), Ascona, Switzerland, May 16-18, 2018.

BUKOWSKI, L., 2016. System of systems dependability - Theoretical models and applications examples. Reliability Engineering and System Safety, 151, 76-92, ISSN 0951-8320; https://doi.org/10.1016/j.ress.2015.10.014.

CASSOTTANA, B., SHEN, L., CHING TANG, L., 2019. Modeling the recovery process: A key dimension of resilience. Reliability Engineering and System Safety, 190, 106528, ISSN 0951-8320; https://doi.org/10.1016/j. ress.2019.106528.

CHRISTODOULOU, S.E., FRAGIADAKIS, M., AGATHOKLEOUS, A., XANTHOS, S., 2018. Urban Water Distribution Networks, Butterworth-Heinemann. ISBN 978012813 6522; https://doi.org/10.1016/B978-0-12-8136 52-2.00020-7.

CORMAN, F., D'ARIANO, A., PACCIARELLI, D., PRANZO, M., 2010. A tabu search algorithm for rerouting trains during rail operations. Transportation Research Part B: Methodological, 44(1), 175-192, ISSN 0191-2615; https://doi.org/10.1016/j.trb .2009.05.004.

COX, A., PRAGER, F., ROSE, A., 2011. Transportation security and the role of resilience: A foundation for operational metrics. Transport Policy, 18(2), 307-317, ISSN 0967-070X; https://doi.org/10.1016/j.tranpol.2010.09.004.

D'ARIANO, A., 2010. Improving real-time train dispatching performance: optimization models and algorithms for re-timing, re-ordering and local re-routing. 4OR-Q J Oper Res 8, 429-432; https://doi.org/10.1007/s10288-010-0131-y.

DESSAVRE, D.G., RAMIREZ-MARQUEZ, J.E., BARKER, K., 2016. Multidimensional approach to complex system resilience analysis. Reliability Engineering and System Safety, 149, 34-43, ISSN 0951-8320; https://doi.org /10.1016/j.ress.2015.12.009.

DEWILDE, T., SELS, P., CATTRYSSE, D., VANSTEENWEGEN, P., 2011. Defining robustness of a railway timetable. In: Proceedings of 4th International Seminar on Railway Operations Modelling and Analysis - Rail-Rome 2011, University of Rome La Sapienza and IAROR, Rome, Italy.

DO, M., JUNG, H., 2018. Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value. Sustainability 2018, 10(11), 4188; https://doi.org/10.3390/ su10114188.

EDJOSSAN-SOSSOU, A.M., GALVEZ, D., DECK, O., AL HEIB, M., VERDEL, T., DUPONT, L., CHERY, O., CAMARGO, M., MOREL, L., 2020. Sustainable risk management strategy selection using a fuzzy multi-criteria decision approach. International Journal of Disaster Risk Reduction, 45, 101474, ISSN 2212-4209; https://doi.org/10.1016/j.ijdrr.2020.101474.

FOSTER, C.J., PLANT, K.L., STANTON, N.A., 2019. Adaptation as a source of safety in complex socio-technical systems: A literature review and model development. Safety Science, 118, 617-631, ISSN 0925-7535; https://doi.org/10.1016/j.ssci.2019.05.035.

FRIEDRICH J., RESTEL F.J., WOLNIEWICZ Ł., 2019. Railway Operation Schedule Evaluation with Respect to the System Robustness. In: Zamojski W., Mazurkiewicz J., Sugier J., Walkowiak T., Kacprzyk J. (eds) Contemporary Complex Systems and their Dependability. DepCoS-RELCOMEX 2018. Advances in Intelligent Systems and Computing, 761. Springer, Cham; https://doi.org/10.1007/978-3-319-91446-6_19.

GOŁĘBIOWSKI, P., 2020. Method of Planning the Work of Conductor Crews Taking into Account the Polish Conditions. ISCT21 2019: Research Methods and Solutions to Current Transport Problems (2020), 154-163; doi: 10.1007/978-3-030-27687-4_16.

GOVERDE, R.M.P, 2008: Timetable stability analysis. Hansen, I., Pachl, J. (Eds.), Railway timetable and traffic. Eurailpress, Hamburg.

GOVERDE, R.M.P., 2007. Railway timetable stability analysis using max-plus system theory. Transportation Research Part B: Methodological, 41(2), 179-201, ISSN 0191-2615; https://doi.org/10.1016/j.trb.2006.02.003.

HONG, L., YE, B., YAN, H., ZHANG, H., OUYANG, M., HE, X., 2019. Spatiotemporal vulnerability analysis of railway systems with heterogeneous train flows. Transportation Research Part A: Policy and Practice, 130, 725-744, ISSN 0965-8564, https://doi.org/10.1016/ j.tra.2019.09.055.

HOSSEINI, S., BARKER, K., RAMIREZ-MARQUEZ, J.E., 2016. A review of definitions and measures of system resilience. Reliability Engineering and System Safety, 145, 47-61, ISSN 0951-8320; https://doi.org/10.1016/ j.ress.2015.08.006.

JACYNA M., 2009. Modelling and evaluation of transportation systems. Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa 2009.

JACYNA, M., Gołębiowski, P., 2015. An approach to optimizing the train timetable on a railway network. Urban Transport XXI, 146, 690-710; doi: 10.2495/UT150571.

JACYNA, M., GOŁĘBIOWSKI, P., URBANIAK, M., 2016. Multi-option Model of Railway Traffic Organization Including the Energy Recuperation. TST 2016: Challenge of Transport Telematics 199-210; doi: 10.1007/ 978-3-319-49646-7_17.

JACYNA, M., WASIAK, M., KŁODAWSKI, M., LEWCZUK, K., 2014. Simulation model of transport system of Poland as a tool for developing sustainable transport. Archives of Transport 31(3), 23-35; doi: 10.5604/086 69546.1146982.

JACYNA, M., ŻAK, J., 2016. Simulation Models in Testing Reliability of Transport Process. Journal of Konbin, 37(1), 203-230; doi: 10.1515/jok-2016-0010.

JACYNA-GOŁDA, I., GOŁĘBIOWSKI, P., IZDEBSKI, M., LEWCZUK, K., KŁODAWSKI, M., JACHIMOWSKI, R., SZCZEPAŃSKI, E., 2017a. Scenario analyses for a sustainable transport system development. Vibroengineering PROCEDIA, 13, 280-284; doi: 10.21595/vp.2017.19092.

JACYNA-GOŁDA, I., GOŁĘBIOWSKI, P., IZDEBSKI, M., LEWCZUK, K., KŁODAWSKI, M., JACHIMOWSKI, R., SZCZEPAŃSKI, E., 2017b. The evaluation of the sustainable transport system development with the scenario analyses procedure. Journal of Vibroengineering, 19(7), 5627-5638; doi: 10.21595/jve.2017.19275.

JAIN, P., DIANGELAKIS, N.A., PISTIKO-POULOS, E.N., MANNAN, M.S., 2019b. Process resilience based upset events prediction analysis: Application to a batch reactor. Journal of Loss Prevention in the Process Industries, 62, 103957, ISSN 0950-4230; https://doi.org/10.1016/j.jlp.2019.103957.

JAIN, P., PASMAN, H.J., WALDRAM, S., PISTIKOPOULOS, E.N., MANNAN, M.S., 2018. Process Resilience Analysis Framework (PRAF): A systems approach for improved risk and safety management. Journal of Loss Prevention in the Process Industries, 53, 61-73, ISSN 0950-4230; https://doi.org/10.1016/j.jlp.2017.08.006.

JAIN, P., PISTIKOPOULOS, E.N., MANNAN, M.S., 2019. Process resilience analysis based data-driven maintenance optimization: Application to cooling tower operations. Computers and Chemical Engineering, 121, 27-45, ISSN 0098-1354; https://doi.org/10.1016/ j.compchemeng.2018.10.019.

JOHANSSON, J., HASSEL, H., 2010. An approach for modelling interdependent infrastructures in the context of vulnerability analysis. Reliability Engineering and System Safety, 95, Issue 12, 1335-1344, ISSN 0951-8320; https://doi.org/10.1016/j.ress.2010.06.010.

KIERZKOWSKI, A., KISIEL, T., 2017. Evaluation of a Security Control Lane with the Application of Fuzzy Logic. Procedia Engineering, 187, 656-663, ISSN 1877-7058; https://doi.org/10.1016/j.proeng.2017.04.427.

KNUDSEN, C., ALBRECHTSEN, E., W?R?, I, WAHL, A.M., 2012. Building resilience into emergency management. Safety Science, 50(10), 1960-1966, ISSN 0925-7535, https://doi.org/10.1016/j.ssci.2012.03.001.

KROON, L., HUISMAN, D., MARÓTI, G., 2008b. Optimisation models for railway time-tabling. In: Hansen, I., Pachl, J. (Eds.), Railway timetable and traffic. Eurailpress, Hamburg.

KROON, L.G., DEKKER, R., VROMANS, M.J.C.M., 2007. Cyclic Railway Timetabling: A Stochastic Optimization Approach. In: Geraets F., Kroon L., Schoebel A., Wagner D., Zaroliagis C.D. (eds) Algorithmic Methods for Railway Optimization. Lecture Notes in Com-puter Science, 4359. Springer, Berlin, Heidelberg; https://doi.org/10.1007/978-3-540-74247-0_2.

LIU, W., SONG, Z., 2020. Review of studies on the resilience of urban critical infrastructure 88 Restel, F.J., Archives of Transport networks. Reliability Engineering and System Safety, 193, 106617, ISSN 0951-8320; https://doi.org/10.1016/j.ress.2019.106617.

LOUWERSE, I., HUISMAN, D., 2014. Adjust-ing a railway timetable in case of partial or complete blockades. European Journal of Operational Research, 235(3), 583-593, ISSN 0377-2217; https://doi.org/10.1016/j.ejor.2013.12.020.

LU, C., TANG, J., ZHOU, L., YUE, Y., HUANG, Z., 2017. Improving recovery-to-optimality robustness through efficiency-balanced design of timetable structure. Transportation Research Part C: Emerging Technologies, 85, 184-210, ISSN 0968-090X; https://doi.org/10.1016/j.trc.2017.09.015.

LU, C., TANG, J., ZHOU, L., YUE, Y., HUANG, Z., 2017. Improving recovery-to-optimality robustness through efficiency-balanced design of timetable structure. Transportation Research Part C: Emerging Technologies, 85, 184-210, ISSN 0968-090X; https://doi.org/10.1016/j.trc.2017.09.015.

MAMDANI, E.H., ASSILIAN, S., 1975. An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), 1-13.

OUYANG, M., LIU, C., XU, M., 2019. Value of resilience-based solutions on critical infrastructure protection: Comparing with robustness-based solutions. Reliability Engineering and System Safety, 190, 2019, 106506, ISSN 0951-8320; https://doi.org/10.1016/j.ress.2019.106506.

OUYANG, M., PAN, Z., HONG, L., HE, Y., 2015. Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China. Reliability Engineering and System Safety, 142, 248-257, ISSN 0951-8320; https://doi.org/10.1016/ j.ress.2015.05.013.

PACHL, J., 2016. Systemtechnik des Schienenverkehrs. Bahnbetrieb planen, steuern und sichern. Springer Vieweg, 8.

PATRIARCA, R., BERGSTRÖM, J., DI GRAVIO, G., COSTANTINO, F., 2018. Resilience engineering: Current status of the research and future challenges. Safety Science, 102, 79-100, ISSN 0925-7535; https://doi.org/10.1016/ j.ssci.2017.10.005.

PITILAKIS, K., ARGYROUDIS, S., KAKDERI, K., SELVA, J., 2016. Systemic Vulnerability and Risk Assessment of Transportation Systems Under Natural Hazards Towards More Resilient and Robust Infrastructures. Transportation Research Procedia, 14, 1335-1344, ISSN 2352-1465; https://doi.org/ 10.1016/j.trpro.2016.05.206.

POLICELLA, N., 2005. Scheduling with uncertainty: A proactive approach using partial order schedules. PhD Thesis, Universita delgi Studi di Roma: La Sapienza, Italy. 88.

RAMIREZ-MARQUEZ, J.E., ROCCO, C.M., BARKER, K., MORONTA, J., 2018. Quantifying the resilience of community structures in networks. Reliability Engineering and System Safety, 169, 466-474, ISSN 0951-8320; https://doi.org/10.1016/j.ress.2017.09.019.

RESTEL F.J., TUBIS A., WOLNIEWICZ Ł., 2019. Investigation of Small-Consequence Undesirable Events in Terms of Railway Risk Assessment. In: Zamojski W., Mazurkiewicz J., Sugier J., Walkowiak T., Kacprzyk J. (eds) Contemporary Complex Systems and Their Dependability. DepCoS-RELCOMEX 2018. Advances in Intelligent Systems and Computing, 761. Springer, Cham; https://doi.org/ 10.1007/978-3-319-91446-6_36.

RESTEL, F.J., 2014. Reliability and safety models of transportation systems - a literature review. Probabilistic Safety Assessment and Management, PSAM 12, 1-12.

RUS, K., KILAR, V., KOREN, D., 2018. Resilience assessment of complex urban systems to natural disasters: A new literature review. International Journal of Disaster Risk Reduction, 31, 311-330, ISSN 2212-4209; https://doi.org/10.1016/j.ijdrr.2018.05.015.

SALIDO, M.A., BARBER F., INGOLOTTI, L., 2008. Robustness in railway transportation scheduling. 2008 7th World Congress on Intelligent Control and Automation, Chongqing, 2880-2885; doi: 10.1109/WCICA.2008.4594481.

SCHÖBEL, A., KRATZ, A., 2009. A Bicriteria Approach for Robust Timetabling. In: Ahuja R.K., Möhring R.H., Zaroliagis C.D. (eds) Robust and Online Large-Scale Optimization. Lecture Notes in Computer Science, 5868; Springer, Berlin, Heidelberg; https://doi.org/10.1007/978-3-642-05465-5_5.

SKORUPSKI, J., 2016. The simulation-fuzzy method of assessing the risk of air traffic accidents using the fuzzy risk matrix. Safety Science, 88, 76-87, ISSN 0925-7535; https://doi.org/10.1016/j.ssci.2016.04.025.

SOLINEN, E., NICHOLSON, G., PETERSON, A., 2017. A microscopic evaluation of railway timetable robustness and critical points. Journal of Rail Transport Planning and Management, 7(4), 207-223, ISSN 2210-9706; https://doi.org/10.1016/j.jrtpm.2017.08.005.

TAKEUCHI, Y., TOMII, N., 2005. Robustness indices for train rescheduling. CDROM Proceedings of the 1st International Seminar on Railway Operations Modelling and Analysis. Delft, the Netherlands.

TANG, J., HEINIMANN, H.R., 2018. A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads. PLOS ONE 13(1): e0190616; https://doi.org/10.1371/journal.pone.0190616.

URBANIAK, M., KARDAS-CINAL, E., JACYNA, M., 2019. Optimization of Energetic Train Cooperation. Symmetry, 11(9), 1175; doi: 10.3390/sym11091175.

WANG, Y., NING, B., TANG, T., VAN DEN BOOM, T. J. J., DE SCHUTTER, B., 2015. Efficient Real-Time Train Scheduling for Urban Rail Transit Systems Using Iterative Convex Programming. IEEE Transactions on Intelligent Transportation Systems, 16(6), 3337-3352; doi: 10.1109/TITS.2015.2445920.

XU, Z., RAMIREZ-MARQUEZ, J.E., LIU, Y., XIAHOU, T., 2020. A new resilience-based component importance measure for multi-state networks. Reliability Engineering and System Safety, 193, 106591, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2019.106591.

YANG, L., LI, K., GAO, Z., LI, X., 2012. Optimizing trains movement on a railway network. Omega, 40(5), 619-633, ISSN 0305-0483; https://doi.org/10.1016/j.omega.2011.12.001.

YANG, X., LI, X., NING B., TANG, T. 2016. A Survey on Energy-Efficient Train Operation for Urban Rail Transit. IEEE Transactions on Intelligent Transportation Systems, 17(1), 2-13; doi: 10.1109/TITS.2015.2447507.

YANG, X., NING, B., LI, X., TANG, T., 2014. A Two-Objective Timetable Optimization Model in Subway Systems. IEEE Transactions on Intelligent Transportation Systems, 15(5), 1913-1921; doi: 10.1109/TITS.2014.2303146.

ZADEH, L.A., 1973. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man, and Cybernetics, 3(1), 28-44.

ZHANG, C., KONG, J., SIMONOVIC, J., 2018. Restoration resource allocation model for enhancing resilience of interdependent infrastructure system. Safety Science, 102, 169-177; https://doi.org/10.1016/j.ssci.2017.10.014.

ZHANG, D., DU, F., HUANG, H., ZHANG, F., AYYUB, B.M., BEER, M., 2018. Resiliency assessment of urban rail transit networks: Shanghai metro as an example. Safety Science, 106, 230-243, ISSN 0925-7535; https://doi.org/10.1016/j.ssci.2018.03.023.

ZOU, Q., CHEN, S., 2019. Enhancing resilience of interdependent traffic-electric power system. Reliability Engineering and System Safety, 191, 106557, ISSN 0951-8320; https://doi.org/10.1016/j.ress.2019.106557.

Downloads

Published

2021-03-31

Issue

Section

Original articles

How to Cite

Restel, F. (2021). The railway operation process evaluation method in terms of resilience analysis. Archives of Transport, 57(1), 73-89. https://doi.org/10.5604/01.3001.0014.7485

Share

Most read articles by the same author(s)

Similar Articles

31-40 of 202

You may also start an advanced similarity search for this article.