Application of fuzzy logic to fault tree and event tree analysis of the risk for cargo liquefaction on board ship

Abstract Risk analysis is of paramount importance in maritime transportation due to the nature of work. The IMO (International Maritime Organization) adopted FSA (Formal Safety Assessment) as guidance to address risk analysis on-board ship. However, it does not suggest a specific approach on how to assess the risks. Therefore, safety researchers are seeking robust risk analysis approaches in maritime transportation. This paper performs comprehensive risk analysis by using bow-tie method within a fuzzy logic environment. While the bow-tie method is analysing potential causes and consequences of failures, the fuzzy logic deals with vagueness and imprecision of expert judgements. The case of cargo liquefaction on-board ship is selected as a case study since the consequences of cargo liquefaction are extremely dangerous for crew, ship and environment. Besides its theoretical insight, the paper supports maritime professionals to enhance safety awareness about the cargo liquefaction phenomenon.

[1]  Solomon Tesfamariam,et al.  Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis , 2012 .

[2]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[3]  Emre Akyuz,et al.  Quantitative Human Error Assessment during Abandon Ship Procedures in Maritime Transportation , 2016 .

[4]  Mariarosa Giardina,et al.  Analysis of operator human errors in hydrogen refuelling stations: Comparison between human rate assessment techniques , 2013 .

[5]  Branislav M Corovic,et al.  Research of marine accidents through the prism of human factors , 2013 .

[6]  Abbas Mohajerani,et al.  Bulk cargo liquefaction incidents during marine transportation and possible causes , 2017 .

[7]  Jakub Montewka,et al.  A framework for risk assessment for maritime transportation systems - A case study for open sea collisions involving RoPax vessels , 2014, Reliab. Eng. Syst. Saf..

[8]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[9]  Emre Akyuz,et al.  Utilisation of Fuzzy Fault Tree Analysis (FFTA) for quantified risk analysis of leakage in abandoned oil and natural-gas wells , 2015 .

[10]  Emre Akyuz.  Quantification of human error probability towards the gas inerting process on-board crude oil tankers , 2015 .

[11]  Abbas Mohajerani,et al.  Liquefaction Incidents of Mineral Cargoes on Board Bulk Carriers , 2016 .

[12]  C. Guedes Soares,et al.  Incorporating evidential reasoning and TOPSIS into group decision-making under uncertainty for handling ship without command , 2018, Ocean Engineering.

[13]  Dracos Vassalos,et al.  Numerical assessment of cargo liquefaction potential , 2016 .

[14]  Tian Chai,et al.  Investigation of occurrence likelihood of human errors in shipping operations , 2019, Ocean Engineering.

[15]  Josef Horák.  Recenze: Center for Cemical Process Safety (American Institute of Chemical Engineers) Guidelines for Developing Quantitative Safety Risk Criteria , 2010 .

[16]  Saeed Givehchi,et al.  Cost-based fire risk assessment in natural gas industry by means of fuzzy FTA and ETA , 2020 .

[17]  Yang Liu,et al.  Numerical investigation of solid bulk cargo liquefaction , 2018, Ocean Engineering.

[18]  Faisal Khan,et al.  Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network , 2013 .

[19]  Jin Wang,et al.  Modified failure mode and effects analysis using approximate reasoning , 2003, Reliab. Eng. Syst. Saf..

[20]  J. P. Visser,et al.  Developments in HSE Management in Oil and Gas Exploration and Production , 1998 .

[21]  Sung-Ho Shin,et al.  Half-century research developments in maritime accidents: Future directions. , 2016, Accident; analysis and prevention.

[22]  Chen-Tung Chen,et al.  Aggregation of fuzzy opinions under group decision making , 1996, Fuzzy Sets Syst..

[23]  Bekir Sahin,et al.  Fault Tree Analysis of chemical cargo contamination by using fuzzy approach , 2015, Expert Syst. Appl..

[24]  Bekir Sahin,et al.  Consistency control and expert consistency prioritization for FFTA by using extent analysis method of trapezoidal FAHP , 2017, Appl. Soft Comput..

[25]  Jakub Montewka,et al.  A Risk-Informed Ship Collision Alert System: Framework and Application , 2015 .

[26]  Imo.  INTERNATIONAL MARITIME SOLID BULK CARGOES CODE , 2016 .

[27]  Emre Akyuz,et al.  Application of Fuzzy Fault Tree Analysis (FFTA) to maritime industry: A risk analysing of ship mooring operation , 2019, Ocean Engineering.

[28]  C. Guedes Soares,et al.  Fuzzy logic based approach for ship-bridge collision alert system , 2019, Ocean Engineering.

[29]  A. D. Swain,et al.  Handbook of human-reliability analysis with emphasis on nuclear power plant applications. Final report , 1983 .

[30]  Jin Wang,et al.  Application of a generic bow-tie based risk analysis framework on risk management of sea ports and offshore terminals. , 2011, Journal of hazardous materials.

[31]  Kayvan Pazouki,et al.  Investigation on the impact of human-automation interaction in maritime operations , 2018 .

[32]  Erkan Celik,et al.  A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers , 2015 .

[33]  John Andrews,et al.  Reliability and Risk Assessment , 1994 .

[34]  Muhammet Gul,et al.  A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry , 2016 .

[35]  M Pickthorne.  INTERNATIONAL SAFETY MANAGEMENT CODE , 1994 .

[36]  Tsz Leung Yip,et al.  Shipping technology selection for dynamic capability based on improved Gaussian fuzzy AHP model , 2017 .

[37]  T. Onisawa.  An approach to human reliability on man-machine systems using error possibility , 1988 .