# Estimating the Human Error Probability during Lifeboat Drills
## 3 Results
In addition, the largest weights were assigned to the design and condition of equipment and Crew Competence, which are, according to [35], the most common causes of lifeboat drill accidents worldwide. Hence, it can be concluded that their judgement is validated against the objective criteria. After weighing, experts rated the PSFs, considering each task separately. The arithmetic means were taken and multiplied by the normalised weights to obtain the SLI according to Equation (1) (Table 3). After obtaining the SLI values for each task, it was necessary to determine the HEP. Hence, the experts estimated the HEP for each group of tasks (T1-T5) for the worst- and best-case scenarios (in the best-case scenario, all PSFs are as good as possible, and the opposite is true for the worst case). Equation (2) was used for obtaining constants \(a\) and \(b\), where an SLI value of 0 was taken for the worst case, while an SLI value of 100 was taken for the best case. The obtained values of the \(a\) and \(b\) constants are shown in Table 4.  
After calculating the constants \(a\) and \(b\), the HEP was obtained using Equation (2) (the obtained SLI values from Table 3 were used together with constants a and b from Table 4). The results are presented in Table 5.  
According to the experts' judgement, tasks T4.5--Resuming recovery to the embarkation deck level, testing the manual operation of the limit switches during recovery, and disembarking the lifeboat crew; T4.2--Confirming crew readiness for recovery; and T4.1--Aligning the lifeboat with the forward and aft davit hooks, retrieving the painter, and engaging the hooks, were identified as the ones with the highest probability of human error during the execution, with 4.1%, 4.1%, and 3.4%, respectively (Figure 2). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Task Group**} & **Estimated HEP** & **Estimated HEP** & **Value of \(a\)** & **Value of \(b\)** \\  & **for the Best Case** & **for the Worst Case** & **Constant** & **Constant** \\ \hline T1 & 3.30 \(\times\) 10\({}^{-4}\) & 5.00 \(\times\) 10\({}^{-2}\) & 0.0002213 & \(-\)0.02228 \\ T2 & 5.00 \(\times\) 10\({}^{-4}\) & 5.00 \(\times\) 10\({}^{-2}\) & 0.0002206 & \(-\)0.02228 \\ T3 & 2.85 \(\times\) 10\({}^{-4}\) & 3.30 \(\times\) 10\({}^{-2}\) & 0.0001445 & \(-\)0.01457 \\ T4 & 1.00 \(\times\) 10\({}^{-3}\) & 1.00 \(\times\) 10\({}^{-1}\) & 0.00045323 & \(-\)0.04576 \\ T5 & 2.50 \(\times\) 10\({}^{-4}\) & 2.50 \(\times\) 10\({}^{-2}\) & 0.0001089 & \(-\)0.01100 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The experts’ estimates of HEP for the lifeboat drill. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Product 1** & **Product 2** & **Product 3** & **Product 4** & **Product 5** & **SLI** \\ \hline T1.1 & 18.49 & 15.28 & 14.06 & 8.25 & 7.71 & 63.79 \\ T1.2 & 16.56 & 14.36 & 15.60 & 8.43 & 8.45 & 63.39 \\ T1.3 & 18.63 & 14.82 & 16.38 & 9.43 & 9.65 & 68.91 \\ T2.1 & 18.63 & 15.90 & 14  
In addition, it was necessary to perform an inter-judge consistency analysis to ensure that there was consistency in the judgement of experts used in the study. For that purpose, a two-way ANOVA test was utilised to compare the means of two or more groups. The dependent variable used in the test was log(HEP), and the factors used were experts and tasks. IBM SPSS version 29.0.1.0 (171) was used for the analysis. According to the analysis, the individual log(HEP) values were significantly different for the tasks performed (\(p<0.001\)) but were not significantly different for the experts (\(p=0.792\)) and were consistent with the study's purpose (Table 6). Furthermore, there is a need to calculate the interclass correlation coefficient (r), expressing the mean correlation between experts' judgments, utilising Equation (3) [20,21]:  
\[r=\frac{F-1}{F+(n+1)} \tag{3}\]  
where F is the F value from Table 6 (F = 470.339), and n is the number of experts (n = 8). When these values are inserted into Equation (3), the result obtained is r = 0.979, meaning