Numerical risk analysis of gas freeing process in oil/chemical tanker ships. (15th December 2022)

• Record Type: Journal Article
• Authors: Elidolu, Gizem; Uflaz, Esma; Aydin, Muhammet; Celik, Erkan; Akyuz, Emre; Arslan, Ozcan
• Is Part Of: Ocean engineering. Volume 266(2022)Part 4
• Publication Date: 2022-12-15
• Subjects: Risk assessment -- Intuitionistic fuzzy TODIM -- Gas freeing -- Oil/chemical tankers; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.113082
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Gas freeing is one of the most hazardous and critical operations on oil/chemical tankers. The process aims to remove toxic gases from tanks and bring oxygen to a healthy level (21%) in the tank atmosphere. Significant shipboard operations such as hot work or entry into the tank after tank cleaning require a successful gas-freeing process; otherwise, the consequences may be devastating for human life, cargo, ship, and the marine environment. Therefore, proactive planning and comprehensive risk assessment are essential to enhance operational safety onboard tanker ships. In this study, the potential hazards of the gas-freeing process are evaluated under the Fine–Kinney based intuitionistic fuzzy TODIM (Tomada de Decisão Interativa e Multicritério) approach. While the Fine Kinney and TODIM methods are used for calculating the risk score with the probability, exposure, and consequence parameters and determining the risk priority, intuitionistic fuzzy sets (IF) help to overcome uncertainty in human decision-making. The research findings are anticipated to guide maritime professionals, safety inspectors, and shipboard personnel in enhancing the gas-freeing process's safety and potential mitigating risks on oil/chemical tanker ships. Highlights: Numerical risk assessment under Fine-Kinney and TODIM for gas freeing process is performed. Intuitionistic fuzzy sets are modified to overcome uncertainty. The paper recommends preventive measures according to highest risk factors.