Application of a SPAR-H based framework to assess human reliability during emergency response drill for man overboard on ships

Ahn, Sung Il; Kurt, Rafet Emek; Akyüz, Emre

doi:10.1016/j.oceaneng.2022.111089

Cited by 34 publications

(6 citation statements)

References 37 publications

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“…It was necessary to formulate rules. The study used formulae (6), formulae (7), formulae (8), formulae (9), formulae (10), formulae (11) and formulae (12) presented in Table 16 [ 43 , 47 ]. With reference to Table 16 , a high-pressure reactor operation comprised four sub-tasks, with each sub-task containing elementary actions.…”

Section: Resultsmentioning

confidence: 99%

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An investigation into accidents in laboratories in universities in China caused by human error: A study based on improved CREAM and SPAR-H

He,

Kuai,

Deng

et al. 2024

Heliyon

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Section: Resultsmentioning

confidence: 99%

“…Every PSF level was accorded an HEP multiplier value, as illustrated in Table 6 and Table 7 [ 41 ]. If “Available Time” or “Fitness for Duty” was considered a highly negative instance, following the HEP for the designated task should be set to 1 irrespective of any other multipliers involving other PSFs [ 43 ].…”

Section: Methodsmentioning

confidence: 99%

An investigation into accidents in laboratories in universities in China caused by human error: A study based on improved CREAM and SPAR-H

He,

Kuai,

Deng

et al. 2024

Heliyon

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“…After all, if a ship is sailing on a calm sea without any other factors intervening, it is difficult to directly cause a maritime accident simply through operational errors or poor lookout, which was confirmed by the subsequent analysis of the characteristics' SHAP values in this study. Inadequate training by shipping companies makes crew members more likely to be killed or injured when they fall overboard or fall into cargo storage, as they may not have developed adequate muscle memory [37]. The third item in Figure 8 shows that the more the ship is loaded in an unreasonable way, the more likely it is to cause a capsizing accident.…”

Section: Shap Value Analysis Of the Featuresmentioning

confidence: 99%

Fusing XGBoost and SHAP Models for Maritime Accident Prediction and Causality Interpretability Analysis

Zhang

Xiong

Lin

2022

JMSE

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In order to prevent safety risks, control marine accidents and improve the overall safety of marine navigation, this study established a marine accident prediction model. The influences of management characteristics, environmental characteristics, personnel characteristics, ship characteristics, pilotage characteristics, wharf characteristics and other factors on the safety risk of maritime navigation are discussed. Based on the official data of Zhejiang Maritime Bureau, the extreme gradient boosting (XGBoost) algorithm was used to construct a maritime accident classification prediction model, and the explainable machine learning framework SHAP was used to analyze the causal factors of accident risk and the contribution of each feature to the occurrence of maritime accidents. The results show that the XGBoost algorithm can accurately predict the accident types of maritime accidents with an accuracy, precision and recall rate of 97.14%. The crew factor is an important factor affecting the safety risk of maritime navigation, whereas maintaining the equipment and facilities in good condition and improving the management level of shipping companies have positive effects on improving maritime safety. By explaining the correlation between maritime accident characteristics and maritime accidents, this study can provide scientific guidance for maritime management departments and ship companies regarding the control or management of maritime accident prevention.

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“…On the other hand, human error is very effective in accidents that occur in maritime transportation [8]. For this reason, some studies in the maritime literature have evaluated human performance by adopting techniques such as Standardized Plant Analysis Risk Human Reliability Analysis (SPAR-H) [9], Human Factors Analysis and Classification System (HFACS) [10], Human Error Assessment and Reduction Technique (HEART) [11], Cognitive Reliability and Error Analysis Method (CREAM) [12], Success Likelihood Index Method (SLIM) [13].…”

Section: Introductionmentioning

confidence: 99%

Human error probability prediction for cargo sampling process on chemical tanker ship under extended SLIM Evidential Reasoning approach

Sezer

Akyüz

Arslan

2023

ICSIS

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Cargo sampling, which indicates the condition of the cargo on the ship, is one of the importantchemical tanker shipboard operations where human performance is prominent. Any negligence during thecargo sampling process can result in loss of human life, environmental disasters and financial losses.Therefore, evaluating human performance in the cargo sampling process on chemical tanker ships is vitalto avoid these. This paper aims to evaluate the contribution of human errors to the cargo sampling process.Hence, the Success Probability Index Method (SLIM) is conducted, incorporating Evidential Reasoning(ER) approach. While SLIM systematically predicts human error probabilities (HEP) consideringperformance shaping factors (PSFs), ER deals with the uncertain and subjective judgments of experts inthe step of rating and weighting PSFs. Based on the presented ER-SLIM model, HEP can be estimated byaggregating the belief degree of the experts and human performance for the cargo sampling process can beevaluated. The outputs of the paper provide a practical contribution to chemical tanker ship owners, healthsafety environment and quality (HSEQ) managers, maritime safety professionals and, chemical tankerofficers in order to minimize the probability of human error in the cargo sampling process, as well as thetheoretical background.

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Application of a SPAR-H based framework to assess human reliability during emergency response drill for man overboard on ships

Cited by 34 publications

References 37 publications

An investigation into accidents in laboratories in universities in China caused by human error: A study based on improved CREAM and SPAR-H

An investigation into accidents in laboratories in universities in China caused by human error: A study based on improved CREAM and SPAR-H

Fusing XGBoost and SHAP Models for Maritime Accident Prediction and Causality Interpretability Analysis

Human error probability prediction for cargo sampling process on chemical tanker ship under extended SLIM Evidential Reasoning approach

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