**4. Conclusions**

In this study, we proposed the DNN-based quality assessment method based on a spectrometer in the LBW process, conducted the relevant experiments to analyze the features of the measured data, and verified the developed method. Notable developments and outcomes from this study are as follows.

• We designed and developed a spectrometer that can measure and analyze the light reflected from the welding area in an LBW process. The spectral response range of the developed spectrometer was 225–975 nm, and its sampling frequency was 5 kHz.


The results of this study substantially contribute to the state-of-the-art, regarding the automation of the welding process and monitoring technology, for LBW processes. Despite our study's contributions, some limitations are worth noting. Although our quality prediction model, based on the spectrometer, effectively estimates the weld quality of laser welding, the application of the model is limited to the scope of this study. Future work will focus on the generalization of the quality assessment method proposed in this study. For this purpose, we will collect sufficient data on various materials and welding conditions, and then further improve the data processing techniques and quality assessment algorithms using advanced ML algorithms. In parallel, we will also improve our spectrometer and its software developed in this study.

**Author Contributions:** The research presented here was carried out in collaboration between all authors. Conceptualization, M.K., I.H. and H.L.; data curation, D.-Y.K. and J.Y.; formal analysis, J.Y. and D.-Y.K.; investigation, J.Y. and D.-Y.K.; methodology, J.Y.; software, H.L. and J.Y.; validation, J.Y. and D.-Y.K.; writing—original draft, J.Y.; writing—review and editing, M.K. and J.Y.; funding acquisition, I.H.; supervision, I.H. and H.L.; project administration, M.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by funding from the Korea Institute of Industrial Technology.

**Acknowledgments:** This study has been conducted with the support of the Korea Institute of Industrial Technology as "Development of intelligent root technology with add-on modules (kitech EO-20-0017)".

**Conflicts of Interest:** The authors declare no conflict of interest.
