## 6 Conclusions  
In the case of repetitive mass production processing, such as in automobile parts, it is difficult to produce NC data that can guarantee quality while having an optimal production time. Although computer-aided design (CAD)/computer-aided manufacturing (CAM) software has evolved, NC codes are generated based on predictions. However, it is difficult to maintain optimized production conditions because chatter and tool wear conditions are different depending on the characteristics of equipment and tools. In particular, the spindle has a very flexible performance in the processing environment. Since the overload section, the no-load section, and the chatter occurrence section can be identified through the initial processing of the part, optimized NC code can be generated by storing and analyzing related data. This is called machining optimization. It is very difficult for an operator to intuitively modify NC codes in the field. The method proposed in this paper can perform NC code optimization based on the processing history using an MDT4 DE. For reference, since the optimization of the cutting curve does not have linearity as shown in Equation (3), it cannot be optimized by accumulating experience.  
Cutting is a process to remove materials in a chip form, using relative material-tool motions. The efficiency of the NC data that decides the tool transfer can be expressed with machining time. When machining time is shorter, NC data are more efficient. However, the quality of the machined surface must be met, considering the lifespan of tools. Chatter, machining quality and tool lifespan are closely related to each other. This study proposed a method to enhance the efficiency of NC machine by storing and analyzing machining data using MDT4 DE.  
The proposed method is applicable to machining or repetitive manufacturing of parts such as mass production. It was optimized using the machining load history. First, to remove chatter, the chatter avoidance RPM equation was applied. After creating an alternative for a new spindle speed, RPM was chosen considering the cutting speed of the material. In terms of feed speed, machining load was optimized, using linear interpolation under maximum-minim ranges in consideration of feed per tooth. When machined using optimized NC data, machining time increased in an overload section during D100 face milling. In contrast, the overall machining time was reduced by 7% by increasing the feed rates in a no-load section. In D25 rough cutting, the machining time decreased by more than 28%. In D16R3 and D16 intermediate cutting, the machining time was reduced by nearly 50% due to an increase in feed rate.  
Conceptualization, E.H. and N.Y.; Methodology, E.H.; Software, N.Y.; Validation, E.H. and N.Y.; Formal analysis, E.H.; Investigation, E.H. and N.Y.; Data curation, E.H. and N.Y.; Writing--original draft preparation, E.H. and N.Y.; Writing--review and editing, N.Y. All authors have read and agreed to the published version of the manuscript.  
This research was supported by Software Convergence Cluster 2.0 funded by the Ministry of Science and ICT, Gyeongsangnam-do, and National IT Industry Promotion Agency.  
Not applicable.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Tool**} & \multicolumn{3}{c}{**Machining Time**} & \multirow{2}{*}{**Rate**} \\ \cline{2-2} \cline{4-4}  & **Original NC Data [min]** & & **Proposed NC Data [min]** & \\ \hline D100 & 5:38 & 5:14 & 0.929 \\ D25 & 32:4 & 22:59 & 0.717 \\ D16R3 & 9:52 & 5:11 & 0.525 \\ D16 & 10:44 & 5:5 & 0.474 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Matching time comparison between original NC and the proposed method.  
**Acknowledgments:** The authors would like to thank the reviewers and editors for their comments and suggestions.  
**Conflicts of Interest:** The authors have no conflicts of interest relevant to this study to disclose.