## 5 Conclusions  
This paper proposes a method to identify the key components of CNC lathe from the perspective of the influence of fault propagation. Based on the details of the fault information collected in the field, the relevant faults are analyzed, and the fault propagation structure diagram starting from each component of the system is established. The fault  
\begin{table}
\begin{tabular}{c c c} \hline
**Directed Edge** & **Fault Propagation Intensity** & **Fault Propagation Intensity** \\  & **Value (4000 h)** & **Value (6000 h)** \\ \hline E\(\rightarrow\)NC & 0.17773814 & 0.165807 \\ E\(\rightarrow\)H & 0.26106422 & 0.262317 \\ H\(\rightarrow\)A & 0.20396607 & 0.200436 \\ H\(\rightarrow\)F & 0.22417257 & 0.216161 \\ NC\(\rightarrow\)M & 0.12332509 & 0.128086 \\ NC\(\rightarrow\)A & 0.16248011 & 0.168651 \\ A\(\rightarrow\)B & 0.13769959 & 0.141097 \\ A\(\rightarrow\)T & 0.11370514 & 0.117754 \\ F\(\rightarrow\)S & 0.24395299 & 0.246486 \\ S\(\rightarrow\)M & 0.18203743 & 0.18273 \\ S\(\rightarrow\)T & 0.16985866 & 0.170474 \\ \hline \end{tabular}
\end{table}
Table 7: Fault propagation intensity value of each edge of the fault propagation structure model of CNC lathe.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Component Code** & **Fault Probability** & **Fault Propagation Strength (4000 h)** & **Rank** & **Fault Probability** & **Fault Propagation Strength (6000 h)** & **Rank** \\ \hline NC & 0.440846 & 0.285805 & 4 & 0.580568 & 0.296737 & 4 \\ F & 0.290179 & 0.243953 & 6 & 0.398005 & 0.246486 & 6 \\ M & 0.322855 & 0 & 7 & 0.430764 & 0 & 7 \\ E & 0.632003 & 0.438802 & 1 & 0.79164 & 0.428125 & 1 \\ S & 0.494166 & 0.351896 & 3 & 0.644833 & 0.353204 & 3 \\ T & 0.335338 & 0 & 7 & 0.436309 & 0 & 7 \\ H & 0.544449 & 0.428139 & 2 & 0.718822 & 0.416597 & 2 \\ A & 0.385268 & 0.251405 & 5 & 0.493773 & 0.258851 & 5 \\ B & 0.246186 & 0 & 7 & 0.350279 & 0 & 7 \\ \hline \end{tabular}
\end{table}
Table 8: Fault propagation strength and ranking of system components in CNC lathe.  
data is used to calculate dynamic fault rate, dynamic fault probability and dynamic fault influence degree, and then the dynamic fault propagation rate of the system components is calculated. Combined with the fault propagation structure diagram, the improved ASP algorithm is used to evaluate the fault propagation influence value of the components, and finally the dynamic and accurate identification of key components of CNC lathe is realized.  
The results obtained in this paper can be used to formulate maintenance control strategy, provide reference for health maintenance and reliability design, and reduce unnecessary shutdown loss of CNC lathes. In the future, multiple attributes of importance, fault propagation influence and fragility can be considered to identify key components, and the method can be extended to the identification of key components of other complex CNC equipment.  
Conceptualization, L.L. and Y.Z.; methodology, L.L.; software, G.G.; validation, L.L. and G.S.; formal analysis, Y.Z.; investigation, L.L. and G.G.; resources, G.S.; data curation, Y.Z.; writing--original draft preparation, L.L.; writing--review and editing, L.L.; visualization, G.G.; supervision, Y.Z.; project administration, G.S.; funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Jilin Province Science and Technology Development Plan Project (Grant No. 20190302104 GX) and the Jilin Provincial Natural Science Foundation (Grant No. 20170101212 JC).  
Not applicable.  
The authors declare no conflict of interest.