## 5 Case Study  
### Fault Classification Statistics  
Through an investigation of the construction site, the author obtained the concrete production logs of several concrete dams during the construction period and collected and classified the faults in three production systems. In this paper, S1, S2, and S3 are used to represent these three CPSs, respectively, as shown in Figure 7. The mechanical structure characteristics and operating characteristics of these three CPSs are similar, but there are differences in their production capacity. The production capacities of these three CPSs are 200 m\({}^{3}\)/h, 330 m\({}^{3}\)/h, and 350 m\({}^{3}\)/h, respectively. There are 839 cases of CPS faults. Among them, there are 298 fault cases in the statistical sample S1, and there are 154 material delivery system faults, 28 batch metering system faults, 50 pneumatic system faults, and 66 mixer faults. The numbers of faults caused by human factors, environmental factors, mechanical component life factors, and other factors are 104, 30, 98, and 66. There are 287 fault cases in statistical sample S2, and the numbers of cases of the four types of faults are 66, 75, 116, and 30. The numbers of faults caused by human factors, environmental factors, mechanical component life factors, and other factors are 97, 57, 75, and 58. There are 254 fault cases in statistical sample S3, and the numbers of cases of the four types of faults  
Figure 6: Identification process of the influencing factors of the concrete dam production system fault. are 66, 75, 116, and 30. The numbers of faults caused by human factors, environmental factors, mechanical component life factors, and other factors are 97, 57, 75, and 58. Because each system is affected by its own performance, operating environment, and the technical level of its equipment operators, the proportions of the same types of faults in different production systems are different, and the influences of different factors on the faults of different types of production systems are not the same. The details of the collected faults in the three production systems are shown in Tables 2 and 3. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Fault Category**} & \multirow{2}{*}{\
\begin{tabular}{c} **Fault** \\ **Manifestation** \\ \end{tabular} } & \multicolumn{2}{c}{**Statistical Sample Number S1**} & \multicolumn{2}{c}{**Statistical Sample Number S2**} & \multicolumn{2}{c}{**Statistical Sample Number S3**} \\ \cline{3-8}  & &
\begin{tabular}{c} **Number of** \\ **Faults** \\ \end{tabular} & \multirow{2}{*}{**Proportion**} & \multicolumn{2}{c}{**Number of** **Cases**} & \multirow{2}{*}{**Proportion**} & \multicolumn{2}{c}{**Number of** **Cases**} & \multirow{2}{*}{**Proportion**} \\ \hline \multirow{8}{*}{A} & A\({}_{1}\) & 37 & \multicolumn{2}{c}{8} & \multicolumn{2}{c}{29} \\ \cline{2-8}  & A\({}_{2}\) & 22 & \multicolumn{2}{c}{14} & \multicolumn{2}{c}{14} \\ \cline{2-8}  & A\({}_{3}\) & 6 & \multicolumn{2}{c}{51.68\%} & \multicolumn{2}{c}{11} & \multicolumn{2}{c}{11} & \multicolumn{2}{c}{11} \\ \cline{2-8}  & A\({}_{4}\) & 59 & \multicolumn{2}{c}{14} & \multicolumn{2}{c}{32} & \multicolumn{2}{c}{39.76\%} \\ \cline{2-8}  & A\({}_{5}\) & 18 & \multicolumn{2}{c}{9} & \multicolumn{2}{c}{8} & \multicolumn{2}{c}{} \\ \cline{2-8}  & A\({}_{6}\) & 12 & \multicolumn{2}{c}{10} & \multicolumn{2}{c}{7} & \multicolumn{2}{c}{} \\ \hline \multirow{8}{*}{B} & B\({}_{1}\) & 9 & \multicolumn{2}{c}{19} & \multicolumn{2}{c}{11} \\ \cline{2-8}  & B\({}_{2}\) & 5 & \multicolumn{2}{c}{16} & \multicolumn{2}{c}{8} \\ \cline{2-8}  & B\({}_{3}\) & 3 & \multicolumn{2}{c}{11} & \multicolumn{2}{c}{3} & \multicolumn{2}{c}{7} & \multicolumn{2}{c}{18.11\%} \\ \cline{2-8}  & B\({}_{4}\) & 1 & \multicolumn{2}{c}{3} & \multicolumn{2}{c}{6} & \multicolumn{2}{c}{6} \\ \cline{2-8}  & B\({}_{5}\) & 6 & \multicolumn{2}{c}{19} & \multicolumn{2}{c}{5} \\ \cline{2-8}  & B\({}_{6}\) & 4 & \multicolumn{2}{c}{7} & \multicolumn{2}{c}{9} \\ \hline \hline \end{tabular}
\end{table}