## 4 Results
### Calculating Weight of FMEA Items  
The levels of influence of the RPN elements (O, S, D, and EC) usually differ for many practical applications. Thus, the different weighted elements will affect subsequent risk evaluation. The purpose of this research article is to evaluate the risks of picking and material-handling accidents in warehouse facilities; therefore, an empirical case focused on Taiwan's Logistics Center is selected by this paper. Then the proposed BWM model [19] is used to calculate the proper weights of RPN elements for offering risk evaluation in the next stage, the calculation steps of which are explained in Section 2.1, and Equations (1)-(3) are used for calculating weights.  
The information of the data collected from eight specialists is shown in Tables 5 and 6. The interviewees, whose work experiences in the involved professions are all over 10 years, are working in relative logistics or the PX Mart Guanyin Logistics Center. Their background information is detailed in Table A1. In the logistics industry, the experts evaluated the impact scores given in each case on the basis of Table 2 and considered the information uncertainty to ensure that the analysis reflected the real-world situation.  
The calculation process of the mathematical steps is described in detail in Table A2. In addition, the results of the various weighted RPN elements (O, S, D, and EC) are shown in Table 7. The results of the interval weights are shown as follows:  
\[\widehat{w}_{O} =[0.087,\ 0.114],\ \widehat{w}_{S} =[0.205,\ 0.257],\ \widehat{w}_{D} =[0.249,\ 0.356],\ \widehat{w}_{EC} =[0.324,\ 0.408]\]  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Exp. 1** & **Exp. 2** & **Exp. 3** & **Exp. 4** & **Exp. 5** & **Exp. 6** & **Exp. 7** & **Exp. 8** \\ \hline Worst & Sev. & Sev. & Sev. & Occu. & Occu. & Occu. & Sev. & Occu. \\ \hline Occurrence & M & M & E & E & E & M & E \\ Severity & E & E & M & M & VS & VS & E & S \\ Detection & M & S & VS & S & M & S & VS \\ Expected cost & S & VS & S & VS & S & M & VS & M \\ \hline \hline \end{tabular}
\end{table}
Table 6: Importance of the worst criterion over all the criteria.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Expert 1**} & \multicolumn{2}{c}{**Expert 2**} & \multicolumn{2}{c}{**Expert 3**} & \multicolumn{2}{c}{**Expert 4**} & \multicolumn{2}{c}{**Expert 5**} \\ \cline{2-10}  & **L** & **U** & **L** & **U** & **L** & **U** & **L** & **U** & **L** & **U** \\ \hline \(\widehat{w}_{O}\) & 0.148 & 0.261 & 0.117 & 0.153 & 0.063 & 0.069 & 0.063 & 0.069 & 0.063 & 0.069 \\ \(\widehat{w}_{S}\) & 0.080 & 0.102 & 0.063 & 0.069 & 0.117 & 0.153 & 0.117 & 0.153 & 0.512 & 0.604 \\ \(\widehat{w}_{D}\) & 0.148 & 0.261 & 0.176 & 0.306 & 0.512 & 0.604 & 0.176 & 0.306 & 0.117 & 0.153 \\ \(\widehat{w}_{EC}\) & 0.466 & 0.534 & 0.512 & 0.604 & 0.176 & 0.306 & 0.512 & 0.604 & 0.176 & 0.306 \\ \hline \multicolumn{10}{c}{**Expert 6**} & \multicolumn{2}{c}{**Expert 7**} & \multicolumn{2}{c}{**Expert 8**} & \multicolumn{2}{c}{**Interval Weight**} \\ \cline{2-10}  & **L** & **U** & **L** & **U** & **L** & **U** & **L** & **U** & **Average** & **Rank** \\ \hline \(\widehat{w}_{O}\) & 0.063 & 0.069 & 0.117 & 0.153 & 0.063 & 0.069 & 0.087 & 0.114 & 0.101 & 4 \\ \(\widehat{w}_{S}\) & 0.512 & 0.604 & 0.063 & 0.069 & 0.176 & 0.306 & 0.205 & 0.257 & 0.231 & 3 \\ \(\widehat{w}_{D}\) & 0.1 The result shows that the expected cost is the most important element, as well as the expected cost > detection > severity > occurrence, according to the average value of the experts' comprehensive consideration of importance.