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Reliability, availability, and maintainability analysis of the propulsion system of a fleet

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
New systems are produced and developed to meet specific needs, and their reliability is the most important issue. In the maritime industry, evaluating failures in a ship’s propulsion system results in high costs and the loss of prestige for the company. Land/sea fleet employees need to detect and minimize the failures that may occur in ship propulsion systems in advance to ensure the continuity of the ships’ operations. In this study, the recorded failure data of four different ships belonging to a fleet in the last 10 years are used. Failures were examined as a whole since the ships have similar propulsion systems. The obtained failure data were grouped, and the average time to fix the failures was determined by the chief engineer and made suitable for reliability, availability, and maintainability (RAM) analysis. A suitable model was created for grouped failures by Isograph’s RWB software. As a result of the analysis of the propulsion system and its subsystems, the main engine of the ship was shown to have the best reliability. Furthermore, the most important components were the cylinders of the main engine as subsystems. This study highlights the components that are important to the reliability of a propulsion system. Thanks to the RAM analysis, improvements can be pinpointed on a ship’s propulsion system, which will increase the operations of the maritime industry. Reducing failures will further increase the confidence in maritime transport and strengthen its place among the modes of transportation. This study provides a valuable resource for academicians, experts, as well as companies working on reliability, availability, and maintainability in the future.
Rocznik
Strony
63--70
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
  • Zonguldak Bulent Ecevit University, Maritime Faculty, Adatepe Neighborhood, Doğuş St., No:207/O, Zip Code:35390, Buca, İzmir, Turkey
  • Dokuz Eylül University, Maritime Faculty Adatepe Neighborhood, Doğuş St., No:207/O, Zip Code:35390, Buca, İzmir, Turkey
Bibliografia
  • 1. Alarçin, F., Balin, A. & Demirel, H. (2014) Fuzzy AHP and Fuzzy TOPSIS integrated hybrid method for auxiliary systems of ship main engines. Journal of Marine Engineering & Technology 13(1), pp. 3–11, doi: 10.1080/20464177.2014.11020288.
  • 2. Anantharaman, M., Islam, R., Khan, F., Garaniya, V. & Lewarn, B. (2019) Data analysis to evaluate reliability of a main engine. TransNav 13(2), pp. 403–407, doi: 10.12716/1001.13.02.18.
  • 3. Awal, Z.I. & Hasegawa, K. (2015) Analysis of Ship Accidents due to Marine Engine Failure-Application of Logic Programming Technique (LPT). Marine Engineering 50(6), pp. 744–751, doi: 10.5988/jime.50.744.
  • 4. Balin, A., Demirel, H. & Alarçin, F. (2015) A hierarchical structure for ship diesel engine trouble-shooting problem using fuzzy AHP and fuzzy VIKOR hybrid methods. Brodogradnja 66(1), pp. 54–65.
  • 5. Birolini, A. (2017) Reliability engineering. Berlin, Germany: Springer.
  • 6. Bocchetti, D., Giorgio, M., Guida, M. & Pulcini, G. (2009) A competing risk model for the reliability of cylinder liners in marine Diesel engines. Reliability Engineering & System Safety 94(8), pp. 1299–1307.
  • 7. Cai, G., Wang, Y., Song, Q. & Yang, C. (2018) RAMS Analysis of Train Air Braking System Based on GO-Bayes Method and Big Data Platform. Complexity 2018(2), pp. 1–14, doi: 10.1155/2018/5851491.
  • 8. Choi, I.-H. & Chang, D. (2016) Reliability and availability assessment of seabed storage tanks using fault tree analysis. Ocean Engineering 120, pp. 1–14, doi: 10.1016/ j.oceaneng.2016.04.021.
  • 9. Di Lorenzo, R.A. & Rehg, V. (2008) Reliability, Maintainability, and Availability for Engineers. Kettering, Ohio.
  • 10. Emovon, I., Norman, R.A., Murphy, A.J. & Okwu, M.O. (2018) Application of WASPAS in enhancing reliability centred maintenance for ship system maintenance. Journal of Engineering and Technology 9(1), pp. 35–53
  • 11. Golub Medvešek, I., Šoda, J. & Perić, T. (2014) Fault Tree Analysis in the Reliability of Heavy Fuel Oil Supply. Transactions on Maritime Science 3(2), pp. 131–136, doi: 10.7225/toms.v03.n02.004.
  • 12. Islam, R., Anantharaman, M., Khan, F. & Garaniya, V. (2019) Reliability assessment of a main propulsion engine fuel oil system-what are the failure-prone components? TransNav 13(2), pp. 415–420, doi: 10.12716/1001.13.02.20.
  • 13. Isograph (2021) Reliability Workbench. [Online] Available from: https://www.isograph.com/software/reliability workbench/ [Accessed: March 08, 2021].
  • 14. Knežević, V., Orović, J., Stazić, L. & Čulin, J. (2020) Fault tree analysis and failure diagnosis of marine diesel engine turbocharger system. Journal of Marine Science and Engineering 8(12), 1004, doi: 10.3390/imse8121004.
  • 15. Laskowski, R. (2015) Fault Tree Analysis as a tool for modelling the marine main engine reliability structure. Scientific Journals of the Maritime University of Szczecin, Zeszyty Naukowe Akademii Morskiej w Szczecinie 41(113), pp. 71–77.
  • 16. Lazakis, I., Dikis, K., Michala, A.L. & Theotokatos, G. (2016) Advanced ship systems condition monitoring for enhanced inspection, maintenance and decision making in ship operations. Transportation Research Procedia 14, pp. 1679–1688, doi: 10.1016/j.trpro.2016.05.133.
  • 17. Lazzaroni, M. (2011) Reliability engineering: basic concepts and applications in ICT. Springer Science & Business Media.
  • 18. Levin, M.A. & Kalal, T.T. (2003) Improving product reliability: strategies and implementation (Vol. 1). John Wiley & Sons.
  • 19. Mellal, M.A. & Williams, E.J. (2018) Large-scale reliability-redundancy allocation optimization problem using three soft computing methods. In: Modeling and simulation based analysis in reliability engineering. CRC Press Taylor & Francis Group.
  • 20. Mishra, A. & Mishra, R.P. (2020) RAM modeling for performance analysis of a coal handling system. Materials Today: Proceedings 28, 4, pp. 2149–2155, doi: 10.1016/ j.matpr.2020.04.140.
  • 21. Papadopoulos, Y., Walker, M., Parker, D., Rüde, E., Hamann, R., Uhlig, A., Grätz, U. & Lien, R. (2011) Engineering failure analysis and design optimisation with HiPHOPS. Engineering Failure Analysis 18(2), pp. 590–608, doi: 10.1016/j.engfailanal.2010.09.025.
  • 22. Pham, H. (Ed.) (2006) Springer handbook of engineering statistics. Springer Science & Business Media.
  • 23. Smith, D.J. (2017) Reliability, maintainability and risk: practical methods for engineers. Butterworth-Heinemann.
  • 24. Stapelberg, R.F. (2009) Handbook of reliability, availability, maintainability and safety in engineering design. Springer Science & Business Media.
  • 25. Ta, T.V., Thien, D.M. & Cang, V.T. (2017) Marine Propulsion System Reliability Assesment by Fault Tree Analysis. International Journal of Mechanical Engineering and Applications. Special Issue: Transportation Engineering Technology – Part III 5(4–1), pp. 1–7, doi: 10.11648/ j.ijmea.s.2017050401.11.
  • 26. Tsarouhas, P. (2018) Reliability, availability and maintainability (RAM) analysis for wine packaging production line. International Journal of Quality & Reliability Management 35(3), pp. 821–842, doi: 10.1108/IJQRM-02-2017-0026.
  • 27. Wan, C., Yan, X.P., Zhang, D. & Fu, S. (2013) Reliability analysis of a marine LNG-diesel dual fuel engine. Chemical Engineering Transactions 33, pp. 811–816, doi: 10.3303/ CET1333136.
  • 28. Yang, G. (2007) Life cycle reliability engineering. John Wiley & Sons.
  • 29. Yang, Z. & Wang, J. (2015) Use of fuzzy risk assessment in FMEA of offshore engineering systems. Ocean Engineering 95, pp. 195–204, doi: 10.1016/j.oceaneng.2014.11.037.
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).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-290a3ce8-740c-4329-941a-c23ff02e2d8e
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