{"title":"Assessing human reliability in life raft inspection and maintenance to improve onboard ship operational safety","authors":"Muhammet Aydin","doi":"10.1016/j.oceaneng.2025.123048","DOIUrl":null,"url":null,"abstract":"<div><div>Ensuring operational safety is of critical importance for the protection of human life in the maritime industry. One of the most crucial links in this safety chain is the proper execution of periodic maintenance and inspection of emergency equipment, such as life rafts. This study presents a hybrid methodology to assess Human Error Probabilities (HEPs) in life raft inspection and maintenance operations on board ships. The traditional Success Likelihood Index Method (SLIM) is integrated with improved Z-numbers to more effectively model the uncertainties and subjectivity inherent in expert judgments. Through Hierarchical Task Analysis (HTA), the life raft maintenance process was decomposed into fifteen sub-tasks, and Performance Shaping Factors (PSFs) were identified for these tasks. HEP values for each sub-task were calculated based on the evaluations of a panel of nine maritime experts. The analysis results indicate that tasks such as “Log and close-out inspection in maintenance system” (HEP: 1.85E-02) and “Review service expiry dates and PSC remarks” (HEP: 8.21E-03) have the highest error probabilities. The findings of this study identify the weakest links in life raft maintenance operations, providing a concrete basis for measures in training, procedural improvements, and supervision. This methodology represents a significant step towards enhancing ship operational safety by enabling a more precise management of human-related risks in the maritime domain.</div></div>","PeriodicalId":19403,"journal":{"name":"Ocean Engineering","volume":"342 ","pages":"Article 123048"},"PeriodicalIF":5.5000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocean Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0029801825027313","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
Ensuring operational safety is of critical importance for the protection of human life in the maritime industry. One of the most crucial links in this safety chain is the proper execution of periodic maintenance and inspection of emergency equipment, such as life rafts. This study presents a hybrid methodology to assess Human Error Probabilities (HEPs) in life raft inspection and maintenance operations on board ships. The traditional Success Likelihood Index Method (SLIM) is integrated with improved Z-numbers to more effectively model the uncertainties and subjectivity inherent in expert judgments. Through Hierarchical Task Analysis (HTA), the life raft maintenance process was decomposed into fifteen sub-tasks, and Performance Shaping Factors (PSFs) were identified for these tasks. HEP values for each sub-task were calculated based on the evaluations of a panel of nine maritime experts. The analysis results indicate that tasks such as “Log and close-out inspection in maintenance system” (HEP: 1.85E-02) and “Review service expiry dates and PSC remarks” (HEP: 8.21E-03) have the highest error probabilities. The findings of this study identify the weakest links in life raft maintenance operations, providing a concrete basis for measures in training, procedural improvements, and supervision. This methodology represents a significant step towards enhancing ship operational safety by enabling a more precise management of human-related risks in the maritime domain.
期刊介绍:
Ocean Engineering provides a medium for the publication of original research and development work in the field of ocean engineering. Ocean Engineering seeks papers in the following topics.