Journal is indexed in following databases:
- SCOPUS
- Web of Science Core Collection - Journal Citation Reports
- EBSCOhost
- Directory of Open Access Journals
- TRID Database - Transportation Research Board
- Index Copernicus Journals Master List
- BazTech
- Google Scholar
2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
The Overview of Risk Analysis Methods and Discussion on Their Applicability for Power System of Autonomous Ships
1 University of Zagreb, Zagreb, Croatia
ABSTRACT: The aim of system safety, as a sub-discipline of engineering, is to implement scientific, engineering and management knowledge to provide identification, evaluation, prevention, and control of identified hazards throughout the life cycle and within the defined boundaries of operational effectiveness, time, and cost. By utilizing risk analysis, the system safety function can assign expected values to certain hazards and/or failures to determine the likelihood of their occurrence. Autonomous and unmanned shipping are emerging topics, where technologies needed for their successful implementation in global fleet already exists and it is crucial to demonstrate that they are as safe as conventional ships. Through literature it is suggested that by eliminating human error as a cause of 53% of maritime accidents, autonomous and unmanned shipping will increase maritime safety, but it is important to consider that new types of accidents can appear. Considering that autonomous and unmanned ships need to operate with unattended ship machinery for extended time periods and that empirical data is not available, new framework for reliability assessment is needed. The aim of this paper is to provide overview of risk approaches that can be applied for reliability assessment of autonomous and unmanned ship. Within this paper, literature review is performed where reliability methods and their application to autonomous shipping are outlined. Furthermore, Bayesian network is selected as most promising one and further discussed.
KEYWORDS: Risk Analysis, Failure Analysis, Autonomous Ship, Bayesian Networks, Assessment of Risk, Autonomous Merchant Ships, Fault Tree Analysis (FTA), Ship power systems
REFERENCES
Abaei, M. M., Hekkenberg, R., & BahooToroody, A. (2021). A multinomial process tree for reliability assessment of machinery in autonomous ships. Reliability Engineering and System Safety, 210. - doi:10.1016/j.ress.2021.107484
de Vos, J., Hekkenberg, R. G., & Valdez Banda, O. A. (2021). The Impact of Autonomous Ships on Safety at Sea – A Statistical Analysis. Reliability Engineering and System Safety, 210. - doi:10.1016/j.ress.2021.107558
Wróbel, K., Montewka, J., & Kujala, P. (2017). Towards the assessment of potential impact of unmanned vessels on maritime transportation safety. Reliability Engineering and System Safety, 165(March), 155–169. - doi:10.1016/j.ress.2017.03.029
Rozell, D. J. (2018). The ethical foundations of risk analysis. Risk Analysis, 38(8), 1529-1533. - doi:10.1111/risa.12971
Nzengu, W., Faivre, J., Pauwelyn, A. S., Bolbot, V., Lien Wennersberg, L. A., & Theotokatos, G. (2021). Regulatory framework analysis for the unmanned inland waterway vessel. WMU Journal of Maritime Affairs, 20(3), 357-376. - doi:10.1007/s13437-021-00237-z
Bolbot, V., Theotokatos, G., Andreas Wennersberg, L., Faivre, J., Vassalos, D., Boulougouris, E., & Van Coillie, A. (2021). A novel risk assessment process: Application to an autonomous inland waterways ship. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 1748006X211051829. - doi:10.1177/1748006X211051829
Montewka, J., Wróbel, K., Heikkilä, E., Valdez Banda, O., Goerlandt, F., & Haugen, S. (2018, September). Challenges, solution proposals and research directions in safety and risk assessment of autonomous shipping. In PSAM 14th Probabilistic Saf Assess Manag Conf.
Porathe, T., Å. Hoem, Ø. Rødseth, K. Fjørtoft, and S. O. Johnsen (2018). At least as safe as manned shipping? Autonomous shipping, safety and “human error”. Safety and Reliability–Safe Societies in a Changing World (pp. 417-425). CRC Press. - doi:10.1201/9781351174664-52
Zhou, B., Gao, F., Wang, L., Liu, C., & Shen, S. (2019). Robust and efficient quadrotor trajectory generation for fast autonomous flight. IEEE Robotics and Automation Letters, 4(4), 3529-3536. - doi:10.1109/LRA.2019.2927938
van Cappelle, L. E., Chen, L., & Negenborn, R. R. (2018). Survey on short-term technology developments and readiness levels for autonomous shipping. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 11184 LNCS. Springer International Publishing. - doi:10.1007/978-3-030-00898-7_7
Kretschmann, L., Burmeister, H. C., & Jahn, C. (2017). Analyzing the economic benefit of unmanned autonomous ships: An exploratory cost-comparison between an autonomous and a conventional bulk carrier. Research in transportation business & management, 25, 76-86. - doi:10.1016/j.rtbm.2017.06.002
Jovanović, I., Vladimir, N., Perčić, M., & Koričan, M. (2022). The feasibility of autonomous low-emission ro-ro passenger shipping in the Adriatic Sea. Ocean Engineering, 247. - doi:10.1016/j.oceaneng.2022.110712
Peeters, G., M. Kotzé, M. R. Afzal, T Catoor, S. Van Baelen, P. Geenen, M. Vanierschot, R. Boonen, and P. Slaets (2020). An unmanned inland cargo vessel: Design, build, and experiments. Ocean Engineering, 201, p.107056. - doi:10.1016/j.oceaneng.2020.107056
Thieme, C.A., Utne, I.B., Haugen, S., 2018. Assessing ship risk model applicability to Marine Autonomous Surface Ships. Ocean Engineering 165, 140–154. - doi:10.1016/j.oceaneng.2018.07.040
Rødseth, Ø. J. and Å. Tjora (2014). A system architecture for an unmanned ship. Proceedings of the 13th international conference on computer and IT applications in the maritime industries (COMPIT). Verlag Schriftenreihe Schiffbau, 2014 Redworth, UK.
Thieme, C. A., I. B. Utne, and I. Schjølberg (2015). A risk management framework for unmanned underwater vehicles focusing on human and organizational factors. International Conference on Offshore Mechanics and Arctic Engineering, vol. 56499, p. V003T02A075. American Society of Mechanical Engineers. - doi:10.1115/OMAE2015-41627
Thieme, C. A. and I. B. Utne (2017). A risk model for autonomous marine systems and operation focusing on human–autonomy collaboration. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 231(4), 446-464. - doi:10.1177/1748006X17709377
Utne, I. B., A. J. Sørensen, and I. Schjølberg (2017, June). Risk management of autonomous marine systems and operations. International conference on offshore mechanics and arctic engineering (Vol. 57663, p. V03BT02A020). American Society of Mechanical Engineers.
Wróbel, K., J. Montewka, and P. Kujala (2018). System-theoretic approach to safety of remotely-controlled merchant vessel. Ocean Engineering, 152, 334-345. - doi:10.1016/j.oceaneng.2018.01.020
Fan, C., K. Wróbel, J. Montewka, M. Gil, C. Wan, and D. Zhang (2020). A framework to identify factors influencing navigational risk for Maritime Autonomous Surface Ships. Ocean Engineering, 202, 107188. - doi:10.1016/j.oceaneng.2020.107188
Utne, I. B., B. Rokseth, A. J. Sørensen, and J. E. Vinnem (2020). Towards supervisory risk control of autonomous ships. Reliability Engineering & System Safety 196: 106757. - doi:10.1016/j.ress.2019.106757
Johansen, T., and I. B. Utne (2022). Supervisory risk control of autonomous surface ships. Ocean Engineering 251: 111045. - doi:10.1016/j.oceaneng.2022.111045
Yang, R., and I. B. Utne (2022). Towards an online risk model for autonomous marine systems (AMS). Ocean Engineering 251: 111100. - doi:10.1016/j.oceaneng.2022.111100
Barber, D. (2012). Bayesian reasoning and machine learning. Cambridge University Press. - doi:10.1017/CBO9780511804779
Friis-Hansen, A. (2000). Bayesian networks as a decision support tool in marine applications. Denmark: Department of Naval Architecture and Offshore Engineering, Technical University of Denmark.
Abaei, M. M., Hekkenberg, R., BahooToroody, A., Banda, O. V., & van Gelder, P. (2022). A probabilistic model to evaluate the resilience of unattended machinery plants in autonomous ships. Reliability Engineering & System Safety, 219, 108176. - doi:10.1016/j.ress.2021.108176
BahooToroody, A., Abaei, M. M., Banda, O. V., Montewka, J., & Kujala, P. (2022). On reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach. Ocean Engineering, 254, 111252. - doi:10.1016/j.oceaneng.2022.111252
Citation note:
Jovanović I., Vladimir N., Cajner H., Perčić M.: The Overview of Risk Analysis Methods and Discussion on Their Applicability for Power System of Autonomous Ships. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 18, No. 1, doi:10.12716/1001.18.01.09, pp. 109-113, 2024
Authors in other databases:
Hrvoje Cajner:
15123734700
r69FS0YAAAAJ
15123734700
r69FS0YAAAAJ
Maja Perčić:
orcid.org/0000-0002-6558-8939
57211562339
orcid.org/0000-0002-6558-8939
57211562339
File downloaded 98 times
