# Estimating the Human Error Probability during Lifeboat Drills
## 3 Results
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{6}{c}{**Tests of between-Subject Effects**} \\ \hline \multicolumn{6}{c}{**Dependent Variable: Ratings**} \\ \hline \multirow{2}{*}{**Source**} & **Type III Sum of Squares** & \multirow{2}{*}{**Df**} & **Mean Square** & \multirow{2}{*}{**F**} & \multirow{2}{*}{**_p_**} \\  & **Type III Sum of Squares** & & & & \\ \hline Corrected model & 8269.243  & 22 & 375.875 & 8.744 & \textless{}0.001 \\ Intercept & 404,044.424 & 1 & 404,044.424 & 9399.165 & \textless{}0.001 \\ PSF & 5418.167 & 4 & 1354.542 & 31.510 & \textless{}0.001 \\ Tasks & 2851.076 & 18 & 158.393 & 3.685 & \textless{}0.001 \\ Error & 3095.083 & 72 & 42.987 & & \\ Total & 415,408.750 & 95 & & & \\ Corrected total & 11,364.326 & 94 & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Results of two-way ANOVA for rating analysis. The mean of PSF ratings can be considered a measure of the overall quality of the lifeboat drill performance, considering the evaluated tasks during the drill performance. After obtaining results using the SLIM, Task 4--Recovery of the lifeboat was recognised as the one with the highest probability of human error. In order to reduce the shortcomings of the SLIM, the BN was utilised to estimate the probability of human error with respect to the selected tasks and the Performance-Shaping Factors according to the experts' opinions. The BN was developed with five PSF nodes as root nodes, five SLI nodes, five HEP nodes, and overall HEP (Figure 3). The BN was modelled using the GeNle Modeler tool [36]. The normalised weights from Table 2 were taken to calculate SLI values according to Equation (1) (as stated in the Section 2, values of 1 and 100 were taken as ratings). Therefore, 32 possible states (25) were calculated for each SLI according to Equation (4). \[\text{SLI}=0.237\times\{1,100\}+0.247\times\{1,100\}+0.223\times\{1,100\}+0.145 \times\{1,100\}+0.149\times\{1,100\} \tag{4}\]  
Each SLI value can be represented as a possible state of the SLI node. Furthermore, according to Equation (2), the SLI node should be the only parent of the HEP node. This node has two states, i.e., human error occurs (HEP) and no human error (PoS). When completing the Bayesian network structure, conditional probability tables (CCTs) should be assigned to the SLI and HEP nodes to quantify the effects of the PSF node. In order to determine the state values of the SLI factors (SLI T4.1-SLI T4.5), CPTs were used (Figure A1 in Appendix A). After filling in CPTs for the SLI T4.1-SLI T4.5 nodes, it was necessary to fill in the CPTs for the HEP T4.1-HEP T4.5 nodes. In order to achieve this, Equation (2) was used, whereby it was necessary to estimate the probability of human error in the best and worst case for each identified task during lifeboat recovery and, based on that, to calculate the individual values of the constants \(a\) and \(b\) for each individual HEP, that is, for each task identified. The estimated values of the HEP and the calculated constants \(a\) and \(b\) for each individual task are presented in Table 9, where the experts estimated the values of the HEP for the worst- and best-case scenarios (the probabilities were estimated by consensus during a meeting with experts). Then, utilising Equation (2), the values of all states of the nodes HEP T4.1-HEP T4.5 were calculated. After quantifying the values of all nodes, the quantitative BN-SLIM model  
Figure 3: Qualitative BN-SLIM model for Task 4—Recovery of the lifeboat. was obtained and is presented in Figure A2. As shown in Figure A2, the overall task HEP is estimated to be 4%, given the PSF probabilities as estimated by the experts. Also, there is a difference between the SLIM and BN-SLIM results (Table 10). As can be seen from Table 10, the largest difference between the HEPs is for task T4.4--Confirming the release lever is properly rested and hooks locked, and it is higher when using the BN-SLIM.