Comparative reliability analysis and enhancement of marine dual-fuel engines

References

• Alkan, A. D., 2018. Maritime Industry Developments Related to Alternative Fuels. Istanbul, Turkey, 3rd International Naval Architecture and Maritime Symposium.
   Google Scholar
• Andrews, J., and S. Beeson. 2003. “Birnbaum’s Measure of Component Importance for Noncoherent Systems.” IEEE Transactions on Reliability 52 (2): 213–219. doi:10.1109/TR.2003.809656.
   Web of Science ®Google Scholar
• Basurko, O. C., and Z. Uriondo. 2015. “Condition-Based Maintenance for Medium Speed Diesel Engines Used in Vessels in Operation.” Applied Thermal Engineering 80: 404–412.
   Web of Science ®Google Scholar
• Bedford, T., and R. Cooke. 2001. Probabilistic Risk Analysis: Foundations and Methods. Cambridge: Cambridge University Press.
   Google Scholar
• Birnbaum, Z. 1969. “On the Importance of Different Components in a Multi-component System.” In Multivariate Analysis, edited by P. Krishnaiah, 581–592. New York: New York Academic Press.
   Google Scholar
• Bolbota, V., Trivyzab, N., Theotokatosa, G., Boulougourisa, E., Rentizelasb, A., & Vassalosa, D. (2019). Cruise ship optimal power plants design identification and quantitative safety assessment. Environmental Pollution, 9: 11.
   Google Scholar
• Čepin, M., and B. Mavko. 2002. “A Dynamic Fault Tree.” Reliability Engineering & System Safety 75 (1): 83–91.
   Web of Science ®Google Scholar
• Corbett, J., and P. Fischbeck. 1997. “Emissions from Ships.” AMERICAN ASSOCIATION FOR THE ADVANCEMENT OF SCIENCE 278 (5339): 823–824.
   PubMed Web of Science ®Google Scholar
• Dekker, R. 1996. “Applications of Maintenance Optimization Models: A Review and Analysis.” Reliability Engineering & System Safety 51 (3): 229–240.
   Web of Science ®Google Scholar
• Dikis, K. 2016. “Dynamic Risk and Reliability Assessment for Ship Machinery Decision Making.” In Risk, Reliability and Safety. London: CRC Press in Risk, Reliability and Safety: Innovating Theory and Practice: Proceedings of ESREL, edited by C., F. Group et al., 685–692. Glasgow, Scotland: CRC Press.
   Google Scholar
• DNV-GL, 2014. Annual Report 2014, Hovik: DNV–GL.
   Google Scholar
• DNV-GL. 2018. LNG Regulatory Update. Oslo: DNV-GL.
   Google Scholar
• Dong, C., C. Yuan, Z. Liu, and X. Yan. 2013. “Marine Propulsion System Reliability Research Based on Fault Tree Analysis.” Advanced Shipping and Ocean Engineering 2 (1): 27–33.
   Google Scholar
• Espiritu, J. F., D. W. Coit, and U. Prakash. 2007. “Component Criticality Importance Measures for the Power Industry.” Electric Power Systems Research 77 (5–6): 407–420.
   Web of Science ®Google Scholar
• Foss, M. M. 2014. “Chapter 9 - LNG Safety and Security Aspects.” In Handbook of Liquefied Natural Gas, 359–435. Houston: ELSEVIER.
   Google Scholar
• Fussell, J. 1975. “How to Hand-Calculate System Reliability and Safety Characteristics.” IEEE Transactions on Reliability R-24 (3): 169–174.
   Web of Science ®Google Scholar
• Giannakopoulou, E. N., E. I. Thalassinos, and T. V. Stamatopoulos. 2016. “Corporate Governance in Shipping: An Overview.” Maritime Policy & Management 43 (1): 19–38.
   Web of Science ®Google Scholar
• Guan, Y., J. Zhao, T. Shi, and P. Zhu. 2016. “Fault Tree Analysis of Fire and Explosion Accidents for Dual Fuel (Diesel/natural Gas) Ship Engine Rooms.” Journal of Marine Science and Application 15 (3): 331–335.
   Google Scholar
• Hoyland, A., & Rausand, M. 2009. System reliability theory: models and statistical methods (Vol. 420). John Wiley & Sons
   Google Scholar
• IACS. 2015. Classification Societies – What, Why and How? London: IACS.
   Google Scholar
• ICOF. 2020. Compliance with the 2020 ‘Global Sulphur Cap’. London: International Chamber of Shipping.
   Google Scholar
• IEC 61025. 2006. Fault Tree Analysis (Fta). Geneva: International Electrotechnical Commission.
   Google Scholar
• IMO. 2014. Implications of the United Nations Convention on the Law of the Sea for the International Maritime Organization. London: IMO.
   Google Scholar
• IMO. 2018. Revised Guidelines for Formal Safety Assessment (Fsa) for Use in the Imo Rule-making Process. London: IMO.
   Google Scholar
• Kadam, M. N. P. K. S., & Kulkarni, D. K. D. 2017. “Fault Diagnosis and Experimental Analysis of 4-stroke,4-cylinder Petrol Engine Using Fault Tree Analysis.” International Journal of Engineering Trends and Technology 46 (8): 445–453
   Google Scholar
• Komal, C. D., and S.-Y. Lee. 2015. “Fuzzy Reliability Analysis of Dual-fuel Steam Turbine Propulsion System in LNG Carriers considering Data Uncertainty.” Journal of Natural Gas Science and Engineering 23: 148–164.
   Web of Science ®Google Scholar
• Kowalski, J., B. Krawczyk, and M. Woźniak. 2017. “Fault Diagnosis of Marine 4-stroke Diesel Engines Using a One-vs-one Extreme Learning Ensemble.” Engineering Applications of Artificial Intelligence 57: 134–141.
   Web of Science ®Google Scholar
• Kwang Pil, C., M. Rausand, and J. Vatn. 2008. “Reliability Assessment of Reliquefaction Systems on LNG Carriers.” Reliability Engineering & System Safety 93 (9): 1345–1353.
   Web of Science ®Google Scholar
• 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 41 (113): 71–77.
   Google Scholar
• Lazakis, I. 2011. Establishing an Innovative and Integrated Reliability and Criticality Based Maintenance Strategy for the Maritime Industry. Glasgow: University of Strathclyde.
   Google Scholar
• Lazakis, I., O. Turan, and S. Aksu. 2010. “Increasing Ship Operational Reliability through the Implementation of a Holistic Maintenance Management Strategy.” Ships and Offshore Structures 5 (4): 337–357.
   Web of Science ®Google Scholar
• Lazakis, I., O. Turan, S. Alkaner, and A. Olcer. 2009. Effective Ship Maintenance Strategy Using a Risk and Criticality Based Approach. Instanbul, Turkey, 13th Congress of IMAM.
   Google Scholar
• Lazakis, I., Y. Raptodimos, and T. Varelas. 2018. “Predicting Ship Machinery System Condition through Analytical Reliability Tools and Artificial Neural Networks.” Ocean Engineering 152: 404–415.
   Web of Science ®Google Scholar
• Lois, P., J. Wang, A. Wall, and T. Ruxton. 2004. “Formal Safety Assessment of Cruise Ships.” Tourism Management 25 (1): 93–109.
   Web of Science ®Google Scholar
• MAN. 2017. Guiding Overhaul Intervals. Augsburg: MAN Diesel & Turbo.
   Google Scholar
• MARPOL. 2009. International Convention for the Prevention of Pollution from Ships. London: Lloyd’s Register.
   Google Scholar
• MARPOL. 2018. International Convention for the Prevention of Pollution from Ships. London: MARPOL.
   Google Scholar
• MARPOL. 2019. International Convention for the Prevention of Pollution from Ships. London: MARPOL.
   Google Scholar
• Merk, O. 2014. “Shipping Emissions in Ports.” In International Transport Forum. OCED iLibrary. https://www.oecd-ilibrary.org/content/paper/5jrw1ktc83r1-en
   Google Scholar
• NASA. 2002. Fault Tree Handbook with Aerospace Applications. Washington: NASA Office of Safety and Mission Assurance.
   Google Scholar
• NUREG-0492. 1981. Fault Tree Handbook. Washington: U.S. Nuclear Regulatory Commission.
   Google Scholar
• Raptodimos, Y., and I. Lazakis, 2017. Fault Tree Analysis and Artificial Neural Network Modelling for Establishing a Predictive Ship Machinery Maintenance Methodology. London, International Conference on Smart Ship Technology.
   Google Scholar
• Rasoulzadeh Khorasani, V. 2015. Risk Assessment of Diesel Engine Failure in a Dynamic Positioning System. Norway, Stavanger: University of Stavanger.
   Google Scholar
• Schieldrop, B. 2018. IMO2020 Report. London: IMO.
   Google Scholar
• Sharples, J. 2019. “LNG Supply Chains and the Development of LNG as a Shipping Fuel in Northern Europe.” In The Oxford Institute for Energy Studies.
   Google Scholar
• SINTEF Industrial Management. 2015. “Offshore and Onshore Reliability Data.” In 6 Ed. Trondheim: DNV-GL.
   Google Scholar
• Soto, J. F., Seijo, R. G., Formoso, J. F., Iglesias, G. G., & Couce, L. C. 2010. Alternative sources of energy in shipping. The Journal of Navigation, 63(3): 435–448.
   Web of Science ®Google Scholar
• Ta, T. V., D. M. Thien, and V. T. Cang. 2016. “Marine Propulsion System Reliability Assesment by Fault Tree Analysis.” International Journal of Mechanical Engineering and Applications 5 (4–1): 1–7.
   Google Scholar
• Taher, A., I. Lazakis, and O. Turan, 2014. Integration of Business and Technical Aspects of Reliability and Maintenance. Glasgow, International Conference on. Mathematics Textbook Research and Development.
   Google Scholar
• Turan, O., I. Lazakis, S. Judah, and A. Incecik. 2011. “Investigating the Reliability and Criticality of the Maintenance Characteristics of a Diving Support Vessel.” Quality and Reliability Engineering International 27 (7): 931–946.
   Web of Science ®Google Scholar
• UNCTAD. 2018. Review of Maritime Transport. Geneva: UNITED NATIONS CONFERENCE ON TRADE AND DEVELOPMENT.
   Google Scholar
• Vedachalam, N., and G. Ramadass. 2017. “Reliability Assessment of Multi-megawatt Capacity Offshore Dynamic Positioning Systems.” Applied Ocean Research 63: 251–261.
   Web of Science ®Google Scholar
• Wang, J. 2001. “The Current Status and Future Aspects in Formal Ship Safety Assessment.” Safety Science 38 (1): 19–30.
   Web of Science ®Google Scholar
• Wärtsilä®. 2018. Wärtsilä 20 Product Guide. Vaasa: Wärtsilä®
   Google Scholar
• WINGD. 2017. WINGDX72 Operation Manual. Winterthur: Winterthur Gas & Diesel .
   Google Scholar
• WINGD. 2018a. WINGDX72 Maintenance Manual. Winterthur: Winterthur Gas & Diesel .
   Google Scholar
• WINGD. 2018b. WINGDX72DF Maintenance Manual. Winterthur: Winterthur Gas & Diesel .
   Google Scholar
• WINGD. 2019. WINGDX72 Operation Manual. Winterthur: Winterthur Gas & Diesel .
   Google Scholar