Research on Predicting Welding Deformation in Automated Laser Welding Processes with an Enhanced DEWOA-BP Algorithm

Response to Reviewer 1 Comments

1. Summary

Thank you for your letter and for the reviewer’s comments concerning our manuscript entitled “Research on Predicting Welding Deformation in Automated Laser Welding Processes with an Enhanced DEWOA-BP Algorithm” (ID: machines-2963067). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and made the correction, which we hope will meet with approval. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Questions for General Evaluation

Reviewer’s Evaluation

Response and Revisions

Does the introduction provide sufficient background and include all relevant references?

Yes

Are all the cited references relevant to the research?

Yes

Is the research design appropriate?

Can be improved

We have revised the research methods section of the article

Are the methods adequately described?

Can be improved

We have described the methodology in more detail

Are the results clearly presented?

Can be improved

We have added content to the results section

Are the conclusions supported by the results?

Must be improved

We have added content to the results section

3. Point-by-point response to Comments and Suggestions for Authors

Comments 1: In general, I would see that the ML algorithm is presented here, which can predict the manufacturing result parameter (in this case, surface flatness) in relation to four manufacturing parameters (in this case, laser welding speed, Peak power, Duty Cycle and defocus). There are certainly processes in production where this type of algorithm can be utilized, the laser welding example used here is purely theoretical, as it has no practical meaning in the form presented.

Response 1: Thank you very much for your valuable comment. We have carefully thought about the fact that you have given advice and believe that your comments are absolutely correct. This prediction method is not limited to laser welding application scenarios and is highly generalizable. Therefore, we have added relevant fact sheets in the introduction and conclusion sections of the paper. The changes have been reflected in the PDF at Lines 120-125 and Lines 570-585.

Comments 2: Introduction: The Introduction paragraph adequately describes the state of the latest research in the subject area. The need for research is also justified. OK.

Response 2: Thank you for affirming the content of my work.

Comments 3: DEWOA-BP: The different methods have been presented to a sufficient extent. The advantages of the Whale Optimization Algorithm in relation to BP have been highlighted. The impact of the starting population on the WOA result has been highlighted. OK.

Response 3: Thank you for affirming the content of my work.

Comments 4: Method: The method is clearly described, especially the Block diagram is clear. OK.

Response 4: Thank you for affirming the content of my work.

Comments 5: Experimental settings: OK.

Response 5: Thank you for affirming the content of my work.

Comments 6: Data Acquisition Experiment and Model validation experiment: There are four parameters and apparently four values have been selected for each parameter from the parameter range that gives a good result. Are all possible parameter combinations included or are only four different parameter combinations used?

Response 6: Thank you very much for your valuable comment. We have added a description of the experimental parameterization scheme in the Data Acquisition Experiment chapter. The changes have been reflected in the PDF at Lines 407-419.

Comments 7: Results and discussion: The experimental material could also be examined using statistical methods and the results could be compared with those presented. The discussion part is very narrow. I recommend a separate discussion section.

Response 7: We added an experimental control group based on RBF neural network, GRNN neural network and statistical methods in the Model validation experiment section to illustrate the superiority of DEWOA-BP neural network designed in this paper. And, the analysis of the experimental results is added in the Results and discussion section. The changes have been reflected in the PDF at Lines 433-444 and Lines 453-547

Comments 8: Conclusions: (1) and (2) ok. I would recommend rewriting (3) so that it better summarizes the research done.

Response 8: Thank you very much for your valuable comment. We have rewritten part (3) of the conclusion to better summarize the contributions and implications of the article. The changes have been reflected in the PDF at Lines 275-281.

4. Response to Comments on the Quality of English Language

Point: English language fine. No issues detected.

Response: Thank you for affirming the content of my work.

5. Additional clarifications

We provide a revised manuscript, a PDF copy of the manuscript with revision notes, a copy of the author's response to reviewers' comments, and a revised folder containing all manuscript images.

Response to Reviewer 2 Comments

1. Summary

Thank you for your letter and for the reviewer’s comments concerning our manuscript entitled “Research on Predicting Welding Deformation in Automated Laser Welding Processes with an Enhanced DEWOA-BP Algorithm” (ID: machines-2963067). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and made the correction, which we hope will meet with approval. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Questions for General Evaluation

Reviewer’s Evaluation

Response and Revisions

Does the introduction provide sufficient background and include all relevant references?

Yes

Are all the cited references relevant to the research?

Yes

Is the research design appropriate?

Yes

Are the methods adequately described?

Yes

Are the results clearly presented?

Yes

Are the conclusions supported by the results?

Yes

3. Point-by-point response to Comments and Suggestions for Authors

Comments 1: Paragraph 1 and 2 need to be added and reduced. Too long and dispersive;

Response 1: Thank you very much for your valuable comment. We have revised the content of the first and second paragraphs by refining the content, removing some of the conceptual descriptions, and adding connections and transitions between paragraphs of the article. The changes have been reflected in the PDF at Lines 43-208.

Comments 2: Paragraph 3 and 4 need to be added. Moreover delete the too long theoretical part focusing on your specific application. For theoretical explication one reference is enough.

Response 2: Thank you very much for your valuable comment. We have revised the content of the third and fourth paragraphs by streamlining the content, removing some of the conceptual descriptions and adding descriptions of specific applications. The changes have been reflected in the PDF at Lines 211-362.

Comments 3: Homogenize the style of all the figures: caption and test on the pictures (i.e. comparison between Fig. 3 and Fig. 4.

Response 3: Thank you very much for your valuable comment. We have modified Figure 3 and Figure 4. we have standardized and standardized the style of Figure 3 and Figure 4 in terms of fonts, layout formatting, padding formatting, and so on. The changes have been reflected in the PDF at Line 390 and Line 426.

Comments 4: Error bars are missing in the figures showing experimental results (i.e. Fig. 8).

Response 4: Thank you very much for your valuable comment. Through the analysis, we found that Figure 8 is duplicated with Table 3 and there are some expression loopholes, so we deleted Picture 8, and then adjusted the position of Figure 6, Figure 7 and Table 3 in order to express the comparison of the effect of each prediction model more rigorously. The changes have been reflected in the PDF at Line 463-474.

Comments 5: Highlight the main contribution of your research in the Introduction and Conclusions so that it is clear what the authors added in this field.

Response 5: Thank you very much for your valuable comment. We have added an introduction to the contribution of this paper in both the introduction and conclusion sections to highlight the contribution and significance of this paper to the development of the industry.The changes have been reflected in the PDF at Line 108-130 and 549-591.

4. Response to Comments on the Quality of English Language

Point: Moderate editing of English language required.

Response: Because our university regulations do not allow the use of an off-campus English language editing organization to edit the English language quality of the paper, this paper was quality checked in English through the relevant English major teacher in the School of Foreign Languages of our university.

5. Additional clarifications

We provide a revised manuscript, a PDF copy of the manuscript with revision notes, a copy of the author's response to reviewers' comments, and a revised folder containing all manuscript images.