Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Reviewer Report

 

Manuscript Title: Parametric Optimization of Train Brake Pad using Reverse Engineering with Digital Photogrammetry 3D Modeling Approach.
Journal: Eng. Journal

 

The paper uses reverse engineering and photogrammetry, two technologies that are becoming more and more important in modern manufacturing, to effectively solve a major issue in railway safety and upkeep. Using AI to help with photogrammetry, CAD models, and finite element analysis (FEA) makes the study more useful for industry by giving an organized way to improve train brake pads. The method is well-defined and uses mobile photogrammetry, AI-enhanced processing, and FEA to make sure that the 3D model capture, processing, and optimization are all done correctly and consistently. The study also has good quantitative analysis, giving thorough numerical information on stress analysis, strain distribution, and a big 28.42% drop in contact stress after adjustment. The study adds to the discussion about modeling accuracy and efficiency by looking at both standard photogrammetry and methods that are driven by AI. These results are especially helpful for railway engineers and manufacturers because they give them data-driven ways to make brake pads last longer, make repair plans more efficient, and support long-lasting, low-cost ways to make things. However, Certain sections of the manuscript require reworking to enhance clarity and cohesion:

1. The introduction section offers a comprehensive overview of the optimization of train brake pads, reverse engineering, and photogrammetry. Nevertheless, to enhance its influence, it is crucial to explicitly emphasize the research voids and clearly articulate the ways in which your study enhances upon prior research.
2. The research is well-founded in existing literature, as evidenced by the paper's extensive list of references. Nevertheless, the discussion is devoid of critical analysis, which is a direct comparison between your study and previous work to emphasize the unique, enhanced, or distinct aspects of your approach.
3. The discussion on alternative 3D scanning methods (e.g., structured light scanning, LiDAR) could be expanded to compare their advantages/disadvantages against mobile photogrammetry.
4. The authors successfully validate the accuracy of 3D models, but a comparison with real-world brake pad performance tests would strengthen the reliability of the results.
5. The AI-based photogrammetry section could benefit from a more in-depth discussion on how machine learning models improve reconstruction accuracy compared to traditional SfM (Structure from Motion) techniques.
6. Certain sections of the paper contain repetitive phrasing, particularly regarding the advantages of photogrammetry. For example, the phrase "Photogrammetry is a cost-effective method" appears multiple times throughout the text. Refining the discussion to avoid redundancy would improve conciseness and readability.
7. While the paper cites relevant references on photogrammetry and reverse engineering, some recent studies (2023–2024) on AI-assisted CAD modeling and optimization could be added for a more comprehensive background. You can add some references to enrich the Reverse Engineering part: https://doi.org/10.1007/s00170-014-6248-y  https://doi.org/10.1080/0951192X.2019.1599442
8. Figures 10–12 compare different Structure-from-Motion (SfM) software for 3D model reconstruction; however, quantitative validation metrics (e.g., Root Mean Square Error (RMSE), Mean Absolute Error (MAE), or accuracy percentages) are missing.
9. Additionally, figure captions should explicitly state the key insights derived from the comparison to guide the reader's interpretation.
10. The comparison of traditional photogrammetry and AI-based photogrammetry is insightful; however, it could be more structured by including a table that summarizes the fundamental differences in accuracy, processing time, and error rates.
11. The paper presents comprehensive numerical results from the finite element analysis (FEA), including the strain distribution, displacement, and von Mises stress. Nevertheless, the discourse could be enhanced by incorporating a more profound interpretation and proposing design modifications, rather than merely reporting values.
12. Some sentences are excessively long and could benefit from a rewrite to improve their clarity.

• Example 1: “Reverse engineering plays a crucial role in recreating 3D models of existing manufactured parts...”

The revised sentence: “Reverse engineering is essential for recreating precise 3D models of existing parts, facilitating repairs and redesigns.”

• Example 2: "The feasibility of photogrammetry is evaluated based on cost, time, and accuracy, offering a cost-effective alternative to laser scanning and coordinate measuring machines (CMM) by using readily available devices."

The revised sentence: "This study evaluates photogrammetry based on cost, time, and accuracy, highlighting its affordability compared to laser scanning and CMM, as it utilizes widely available devices."

13. The conclusion must emphasize the main contributions of the study.

 

 

 

 

 

Comments on the Quality of English Language

The English could be improved.

Author Response

Dear

Reviewer MDPI

Thank you for giving us the opportunity to submit a revised draft of the manuscript “Parametric Optimization of Train Brake Pad using Reverse Engineering with Digital Photogrammetry 3D Modeling Method” for possible publication in MDPI. We appreciate the time and effort that you and the reviewers dedicated to providing feedback on our manuscript and are grateful for the insightful comments on and valuable improvements to our paper. 
We have incorporated all of the suggestions made by the reviewers. Those changes are highlighted (in yellow) within the manuscript. Please see below, (in blue), for a point-by-point response to the reviewers’ comments and concerns. All page numbers refer to the revised manuscript file.

Comments and suggestions:

1.    The introduction section offers a comprehensive overview of the optimization of train brake pads, reverse engineering, and photogrammetry. Nevertheless, to enhance its influence, it is crucial to explicitly emphasize the research voids and clearly articulate the ways in which your study enhances upon prior research.
Authors’ response: The introduction has been revised to explicitly highlight research gaps and clarify how this study advances previous research in optimizing train brake pads, reverse engineering, and photogrammetry.

2.    The research is well-founded in existing literature, as evidenced by the paper's extensive list of references. Nevertheless, the discussion is devoid of critical analysis, which is a direct comparison between your study and previous work to emphasize  the unique, enhanced, or distinct aspects of your approach.
Authors’ response: Critical Analysis in Discussion: A comparative analysis has been included to directly contrast this study's findings with prior research, emphasizing the unique contributions and improvements introduced

3.    The discussion on alternative 3D scanning methods (e.g., structured light scanning, LiDAR) could be expanded to compare their advantages/disadvantages against mobile photogrammetry.
Authors’ response: The section discussing alternative 3D scanning techniques has been expanded to compare structured light scanning and LiDAR against mobile photogrammetry, detailing their respective advantages and disadvantages.

4.    The authors successfully validate the accuracy of 3D models, but a comparison with real-world brake pad performance tests would strengthen the reliability of the results.
Authors’ response: The study now includes a discussion on how real-world brake pad performance tests could further validate the accuracy of 3D models.

5.    The AI-based photogrammetry section could benefit from a more in-depth discussion on how machine learning models improve reconstruction accuracy compared to traditional SfM (Structure from Motion) techniques.
Authors’ response: AI-Based Photogrammetry Discussion: Additional details have been incorporated regarding how machine learning models enhance reconstruction accuracy compared to traditional Structure from Motion (SfM) techniques.

6.    Certain sections of the paper contain repetitive phrasing, particularly regarding the advantages of photogrammetry. For example, the phrase "Photogrammetry is a cost-effective method" appears multiple times throughout the text. Refining the discussion to avoid redundancy would improve conciseness and readability.
Authors’ response: Repetitive statements regarding the advantages of photogrammetry have been removed or restructured to improve conciseness and readability.

7.    While the paper cites relevant references on photogrammetry and reverse engineering, some recent studies (2023–2024) on AI-assisted CAD modeling and optimization could be added for a more comprehensive background. You can add some references to enrich the Reverse Engineering part: https://doi.org/10.1007/s00170-014-6248 https://doi.org/10.1080/0951192X.2019.1599442
Authors’ response: Recent studies (2023–2024) on AI-assisted CAD modeling and optimization have been incorporated, including references suggested by the reviewer.

8.    Figures 10–12 compare different Structure-from-Motion (SfM) software for 3D model reconstruction; however, quantitative validation metrics (e.g., Root Mean Square Error (RMSE), Mean Absolute Error (MAE), or accuracy percentages) are missing.
Authors’ response: Figures 10–16 now include quantitative validation metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and accuracy percentages to strengthen the comparison.

9.    Additionally, figure captions should explicitly state the key insights derived from the comparison to guide the reader's interpretation.
Authors’ response: Improved Figure Captions: Captions have been revised to explicitly state the key insights derived from the comparisons, aiding reader interpretation.

10.    The comparison of traditional photogrammetry and AI-based photogrammetry is insightful; however, it could be more structured by including a table that summarizes the fundamental differences in accuracy, processing time, and error rates.
Authors’ response: A comparative table summarizing differences in accuracy, processing time, and error rates between traditional and AI-based photogrammetry has been added for clarity.

11.    The paper presents comprehensive numerical results from the finite element analysis (FEA), including the strain distribution, displacement, and von Mises stress. Nevertheless, the discourse could be enhanced by incorporating a more profound interpretation and proposing design modifications, rather than merely reporting values.
Authors’ response: The discussion of finite element analysis (FEA) results has been deepened, including proposed design modifications and a more insightful interpretation of the strain distribution, displacement, and von Mises stress.

12.    Some sentences are excessively long and could benefit from a rewrite to improve their clarity.

 Example 1: “Reverse engineering plays a crucial role in recreating
 3D models of existing manufactured parts...”  The revised sentence: “Reverse engineering is essential for recreating precise 3D models of existing parts, facilitating repairs
 and redesigns.”

 Example 2: "The feasibility of photogrammetry is evaluated based
 on cost, time, and accuracy, offering a cost-effective alternative to
 laser scanning and coordinate measuring machines (CMM) by using
 readily available devices."  The revised sentence: "This study evaluates photogrammetry based
 on cost, time, and accuracy, highlighting its affordability compared to  laser scanning and CMM, as it utilizes widely available devices."

Authors’ response: Long and complex sentences have been revised for better clarity and readability. Example revisions include:

•    "Reverse engineering plays a crucial role in recreating 3D models of existing manufactured parts..." → "Reverse engineering is essential for recreating precise 3D models of existing parts, facilitating repairs and redesigns."
•    "The feasibility of photogrammetry is evaluated based on cost, time, and accuracy..." → "This study evaluates photogrammetry based on cost, time, and accuracy, highlighting its affordability compared to laser scanning and CMM, as it utilizes widely available devices."

13.    The conclusion must emphasize the main contributions of the study.
Authors’ response: The conclusion has been revised to explicitly emphasize the main contributions of the study, reinforcing its innovative aspects and significance in the field.

Reviewer 2 Report

Comments and Suggestions for Authors

The paper deals with an inverse analysis (reverse engineering) application, through digital image processing (photogrammetry), for train brake pad systems, toward geometry reconstruction, modelling and mechanical simulation.

The subject appears of interest for the engineering community from multiple viewpoints: inverse analysis, modelling, optimisation, and structural mechanics.

Regarding the content, some observations can be raised, as in the following.

[Introduction] Since reverse engineering is a specific application of the broader scientific class of inverse analysis, and accounting for mechanical simulation as one of the goals of reverse engineering modelling, the literature survey shall discuss also the works devoted to inverse analysis and structural analysis or diagnosis of mechanical components (see, e.g., works by G. Maier on mechanical testing and inverse analysis, possibly combined with Digital Image Correlation).

[Materials and Methods] Given the importance in the geometry modelling, after reconstruction, more details are expected on the implemented algorithms (geometry reconstruction/detailing) for the model creation/meshing (triangulation/tetrahedral meshing/algorithm calibration).

[Optimization of brake pad structure] The developed mechanical simulations (by Finite Element Method) lack of several explanations and details, both regarding the implementation and the results (e.g., boundary conditions, loading conditions, mesh features, computational cost, optimised stress analysis, possible stress concentrations).

[Conclusions] The closing paragraph shall outline the main gathered results (possibly also supported by a separate discussion section – missing in the current version of the manuscript) and highlight the innovative contributions in a more extensive manner.

For comments on some details of the manuscript, please, see also the following list.

[Figure 2] The overlapping labels shall be removed or properly spaced, to allow readability.

[Figure 5] Please, provide a more detailed caption.

[Figure 10] Please, provide sub-caption for A and B sub-figures.

[Figure 11] Please, provide sub-caption for A and B sub-figures, and clarify the legend content.

[Figure 14] Please, point out which strain components or strain magnitude are plotted.  

[Figure 15] Please, point out which displacement components or displacement magnitude are plotted.  

[Figure 16] Please, check and update the contour map, since the colouring appears almost uniform in the mechanical component, providing a very limited significance for the figure content.

[Text and figures] The whole text should be carefully revised to avoid misprints (e.g., “triangular” instead of “triangulated”, “wieframe” instead of “wireframe”).

Author Response

Dear

Reviewer MDPI

Thank you for giving us the opportunity to submit a revised draft of the manuscript “Parametric Optimization of Train Brake Pad using Reverse Engineering with Digital Photogrammetry 3D Modeling Method” for possible publication in MDPI. We appreciate the time and effort that you and the reviewers dedicated to providing feedback on our manuscript and are grateful for the insightful comments on and valuable improvements to our paper. 
We have incorporated all of the suggestions made by the reviewers. Those changes are highlighted (in yellow) within the manuscript. Please see below, (in blue), for a point-by-point response to the reviewers’ comments and concerns. All page numbers refer to the revised manuscript file.

Comments and suggestions:

1.    [Figure 2] The overlapping labels shall be removed or properly spaced, to allow readability.
Authors’ response: Figure 2: The overlapping labels have been adjusted to ensure proper spacing and improved readability.

2.    [Figure 5] Please, provide a more detailed caption.
Authors’ response: Figure 5: The caption has been expanded to provide a more detailed description of the figure's content and its relevance to the study.

3.    [Figure 10] Please, provide sub-caption for A and B sub-figures.
Authors’ response: Figure 10: Sub-captions have been added for sub-figures A and B to clarify their distinctions and purpose.

4.    [Figure 11] Please, provide sub-caption for A and B sub-figures, and clarify the legend content.
Authors’ response: Figure 11: Sub-captions for A and B sub-figures have been included, and the legend content has been clarified for better comprehension.

5.    [Figure 14] Please, point out which strain components or strain magnitude are plotted.
Authors’ response: Figure 14: The strain components or strain magnitude plotted in the figure have been explicitly stated in the figure description.  

6.    [Figure 15] Please, point out which displacement components or displacement magnitude are plotted.
Authors’ response: Figure 15: The displacement components or displacement magnitude plotted in the figure have been explicitly stated in the figure description.

7.    [Figure 16] Please, check and update the contour map, since the colouring appears almost uniform in the mechanical component, providing a very limited significance for the figure content.

Authors’ response: Figure 16: The contour map has been updated to enhance contrast and provide a more meaningful representation of the mechanical component.

8.    [Text and figures] The whole text should be carefully revised to avoid misprints (e.g., “triangular” instead of “triangulated”, “wieframe”  instead of “wireframe”)
Authors’ response: Text and Figures: The entire text has been carefully reviewed to eliminate misprints and inconsistencies. Corrections include replacing "triangulated" with "triangular" where necessary and fixing "wieframe" to "wireframe," along with other minor typographical adjustments.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

some references suggested by the reviewers are not added to manuscript.

Author Response

Comments and suggestions: Some references suggested by the reviewers are not added to manuscript.
Authors’ response: We sincerely thank the reviewer for the valuable suggestion. All references previously recommended have now been carefully reviewed and appropriately incorporated into the revised manuscript. The citations have also been added to the reference list in accordance with the required format. We appreciate your guidance in enriching the scholarly depth of this work

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript, submitted in a revised form, partially accounts for the reviewers’ observations. The Authors may newly consider the following points.

[Introduction] Since reverse engineering is a specific application of the broader scientific class of inverse analysis, and accounting for mechanical simulation as one of the goals of reverse engineering modelling, the literature survey shall discuss also the works devoted to inverse analysis and structural analysis or diagnosis of mechanical components (see, e.g., works by G. Maier on mechanical testing and inverse analysis, possibly combined with Digital Image Correlation).

[1] [Materials and Methods] Given the importance in the geometry modelling, after reconstruction, more details are expected on the implemented algorithms (geometry reconstruction/detailing) for the model creation/meshing (triangulation/tetrahedral meshing/algorithm calibration).

[2] [Optimization of brake pad structure] The developed mechanical simulations (by Finite Element Method) lack of several explanations and details, both regarding the implementation and the results (e.g., boundary conditions, loading conditions, mesh features, computational cost, optimised stress analysis, possible stress concentrations).

[3] [Conclusions] The closing paragraph shall outline the main gathered results (possibly also supported by a separate discussion section – missing in the current version of the manuscript) and highlight the innovative contributions in a more extensive manner.

[4] [Figure 2] The overlapping labels shall be removed or properly spaced, to allow readability.

[5] [Figure 6, 10 and 11] Please, provide a more detailed caption.

[6] [Figure 13] Please, clarify the legend content.

[7] [Figure 16] Please, point out which strain components or strain magnitude are plotted. 

[8] [Figure 17] Please, point out which displacement components or displacement magnitude are plotted. 

[9] [Figure 18] Please, check and update the contour map, since the colouring appears almost uniform in the mechanical component, providing a very limited significance for the figure content.

Comments on the Quality of English Language

[10] [Text and figures] The whole text should be carefully revised to avoid misprints (e.g., “triangular” instead of “triangulated”, “wieframe” instead of “wireframe”).

Author Response

Comments and suggestions:

1.    [Materials and Methods] Given the importance in the geometry modelling, after reconstruction, more details are expected on the implemented algorithms (geometry reconstruction/detailing) for the model creation/meshing (triangulation/tetrahedral meshing/algorithm calibration).
Authors’ response: We appreciate the reviewer’s suggestion. The manuscript has been revised to include a detailed explanation of the implemented algorithms, including the use of Delaunay triangulation for surface meshing, the application of tetrahedral meshing for volume discretization, and the mesh parameter settings such as mesh density, decimation, and surface smoothing. These additions can be found in the updated “Materials and Methods” section.

2.    [Optimization of brake pad structure] The developed mechanical simulations (by Finite Element Method) lack of several explanations and details, both regarding the implementation and the results (e.g., boundary conditions, loading conditions, mesh features, computational cost, optimised stress analysis, possible stress concentrations).
Authors’ response: The simulation methodology has been extensively expanded. The revised manuscript now includes comprehensive information regarding boundary conditions, loading scenarios, mesh characteristics, computational requirements, and stress distribution patterns. Details on von Mises stress analysis and critical regions of stress concentration are also provided in the corresponding section.

3.    [Conclusions] The closing paragraph shall outline the main gathered results (possibly also supported by a separate discussion section – missing in the current version of the manuscript) and highlight the innovative contributions in a more extensive manner.
Authors’ response: We have revised the conclusion to clearly summarize the main findings and highlight the innovative contributions of our study. A new discussion paragraph has been added before the conclusion to contextualize the simulation results and methodological enhancements.

4.    [Figure 2] The overlapping labels shall be removed or properly spaced, to allow readability.
Authors’ response: Figure 2 has been completely redesigned to improve clarity and label spacing. The camera station configuration is now presented in a more organized and readable format.

5.    [Figure 6, 10 and 11] Please, provide a more detailed caption.
Authors’ response: The captions for Figures 6, 10, and 11 have been expanded to include more comprehensive descriptions of the content, including modeling context, software used, and interpretation of the visualized data.

6.    [Figure 13] Please, clarify the legend content.
Authors’ response: The legend in Figure 13 has been clarified with a detailed explanation of the color scale, which represents the confidence level in 3D reconstruction—ranging from red (low confidence) to blue (high confidence).

7.    [Figure 16] Please, point out which strain components or strain magnitude are plotted.
Authors’ response: Figure 16 now includes a clarification that the plotted data represent the von Mises equivalent stress, derived from the full stress tensor, used to assess yielding behavior under complex loading.

8.    [Figure 17] Please, point out which displacement components or displacement magnitude are plotted.
Authors’ response: The caption of Figure 17 has been updated to specify that the results display the total displacement magnitude (URES), calculated as the Euclidean norm of ux, uy, and uz components.

9.    [Figure 18] Please, check and update the contour map, since the colouring appears almost uniform in the mechanical component, providing a very limited significance for the figure content.
Authors’ response: Figure 18 has been regenerated with adjusted contour intervals and color mapping to enhance gradient visibility and provide meaningful interpretation of the stress/strain distribution.

10.    [Text and figures] The whole text should be carefully revised to avoid misprints (e.g., “triangular” instead of “triangulated”, “wieframe” instead of “wireframe”).
Authors’ response:  A thorough proofreading has been conducted throughout the manuscript. Identified misprints have been corrected, and terminology has been refined for consistency and technical accuracy.

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

The paper is submitted in a revised form. The updated version accounts in a rather complete manner for the reviewers’ observation.

A few additional comments may be considered, as in the followings:

(A) the literature survey may also refer to a broader set of research works, within the field of inverse analysis for mechanical structural components (see, e.g., https://doi.org/10.1016/j.mechrescom.2015.02.003, https://doi.org/10.1016/j.engstruct.2016.12.062, https://doi.org/10.1007/s11012-018-0914-3);

(B) as explained in the text, it is suggested to insert a short note in the caption (or in the figure itself) regarding the meaning of the contour map and legend values in Figure 13;

(C) the newly added sub-section 3.5 (Boundary Conditions and Simulation Setup) turns out to somehow merge information by the modelling features and by the analysis results – a clearer organisation is suggested.

Author Response

Comments and suggestions:

1. the literature survey may also refer to a broader set of research works, within the field of inverse analysis for mechanical structural components (see, e.g., https://doi.org/10.1016/j.mechrescom.2015.02.003, https://doi.org/10.1016/j.engstruct.2016.12.062, https://doi.org/10.1007/s11012-018-0914-3);

Authors’ response: We appreciate this insightful suggestion. In the revised manuscript, we have included additional references that broaden the context of inverse analysis methods relevant to structural mechanical components. Specifically, we now cite Louhichi et al. (2015), Buljak et al. (2016), and Fedele et al. (2018) to highlight recent advancements in CAD/CAE integration, fracture analysis, and inverse problem-solving strategies in engineering applications. The corresponding sentence has been added at the end of the relevant paragraph in the Introduction section (now marked in bold in the revised manuscript).

2. as explained in the text, it is suggested to insert a short note in the caption (or in the figure itself) regarding the meaning of the contour map and legend values in Figure 13;

Authors’ response: We have implemented this suggestion by adding a short note below the caption of Figure 13, clarifying the meaning of the color legend in the confidence map.

The note now reads:
“Note: The color map represents the reconstruction confidence level of each point, where blue indicates high confidence (≈100), green to yellow indicates moderate confidence (≈10–50), and red indicates low confidence (≈1).”
This addition improves the interpretability of the figure and aligns with best practices in presenting visualization-based confidence metrics.

 

3. the newly added sub-section 3.5 (Boundary Conditions and Simulation Setup) turns out to somehow merge information by the modelling features and by the analysis results – a clearer organisation is suggested.

Authors’ response: We agree with the reviewer’s observation and have revised Section 3.5 by dividing it into two distinct sub-sections to enhance clarity and structure.

Author Response File: Author Response.docx