Injection Mold Design Technology to Locate Weld Lines Away from Highly Loaded Structural Areas

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript entitled “Injection mold design technology to locate weld lines away from highly loaded structural areas” by Chertykovtseva et al. presents an automated method for weld line placement in injection molding. This defect significantly affects the mechanical strength of molded parts. Since the technique is presented in a modular format and is adaptable to widely used software such as Ansys and Moldflow, it has strong potential to attract a broad audience. The approach is also validated against experimental measurements.

The manuscript is generally well-written, and the experimental design is scientifically sound. I have only a few minor comments:

• The sentence on line 71 is unclear and should be revised for clarity.

• Figure 3 is blurry and not very informative.

• The codes and data used in the study are not provided.

• Screenshots from the data files (Figs. 8, 11, and 13) are not necessary in their current form and could either be moved to the supplementary materials or reformatted into tables for clarity.

Author Response

Comments 1: The sentence on line 71 is unclear and should be revised for clarity.

Response 1:Thank you for your comment, we have expanded the description of scientific novelty in introduction.

“The scientific novelty of this study is the development of technology for the automated design of a gating system based on parametric optimization algorithms, considering technological constraints. It allows the calculation of the optimal melt injection points into the cavity part to increase the load-bearing capacity of products manufactured by molding from thermoplastic material at the design stage. The modular structure of the software, which allows for the flexible connection of CAE solvers convenient for the end user, is a distinctive feature of the technology implementation. An experimental assessment of the strength of material specimens and structures containing a weld line was experimentally assessed. It was experimentally confirmed that the developed technique can be used to manufacture aerospace structures and allowed increasing the strength of the product by 2 times.”

Comments 2: Figure 3 is blurry and not very informative.

Response 2:Thank you for your comment, we have significantly improved the image quality. We've cropped unnecessary information, and highlighted that the weld line influences the location of sample failure. We believe that retaining this figure in the current edition is beneficial, and we hope it's now clearer for the reader. A description has also been added in the text (Section 2.1):

“An assessment of the failure locations of the specimens (Figure 3) shows that specimens without a weld line are of equal strength and fail in different locations, whereas specimens containing a weld line fail at the weld line’s location. ”

Comments 3: The codes and data used in the study are not provided.

Response 3:Thank you for your recommendation. We’ve share the code by GitHub [44]:
https://github.com/Vladislava-Chertykovtseva/GateOptWeld3D

Comments 4: Screenshots from the data files (Figs. 8, 11, and 13) are not necessary in their current form and could either be moved to the supplementary materials or reformatted into tables for clarity.

Response 4: Thank you for your comment. We've significantly revised the images in this article. We've replaced some of the screenshots with more schematic images, and described others with text or reformatted into tables for clarity. We hope the current version is more understandable and academic view.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript provides a clear and structured presentation of an optimization-based method for injection mold design, aiming to minimize weld line effects and improve the strength of fiber-reinforced thermoplastic components. The integration of Moldflow, ANSYS, and a modified genetic algorithm is interesting and practical. I believe the manuscript is strong, but I would like to kindly suggest a few minor improvements to make the work even more informative and appealing.

1. Could the authors kindly consider adding one short paragraph to highlight the wider scientific context of their work? For example, a few lines could mention the growing interest in designing multifunctional materials and structures for energy, environmental, and health applications.
2. Could the authors clarify how the optimization time scales with the complexity of the part geometry?
3. This may help future users understand limitations in more intricate parts.
4. Would it be possible to briefly discuss whether the weld line strength factor varies significantly across different fiber orientations?
5. You may already show this in Figure 15, but a short comment in the discussion could make it clearer.
6. In the Methods section, could you add one sentence clarifying if the interpolation step introduces any error in the stress transfer from ANSYS to Moldflow?
7. This is useful for readers who want to validate this hybrid simulation strategy.
8. Is the optimization approach scalable to multi-gate systems or conformal cooling designs?
9. If yes, a short mention in the conclusion or outlook would be interesting for industrial applications.
10. Could you explain whether the developed method is compatible with other commercial solvers beyond Moldflow and ANSYS (for example: Abaqus, Simulia)?
11. Would it be beneficial to add a small comment in the Conclusion on how this method could support predictive design in aerospace or biomedical mold parts? Especially considering composite implants or lightweight structures.
12. Regarding Figure 23–24, is there any indication of local delamination or matrix cracking observed during testing in brackets with weld lines? Even a short comment would strengthen the mechanical interpretation.
13. These are only humble suggestions and questions intended to slightly improve the clarity and perspective of your promising and well-written work. The core contribution is strong and useful for both academic and industrial readers.

Author Response

Comments 1: Could the authors kindly consider adding one short paragraph to highlight the wider scientific context of their work? For example, a few lines could mention the growing interest in designing multifunctional materials and structures for energy, environmental, and health applications.

Response 1: Thank you for your comment, we have expanded the introduction and added new references based on your recommendations to highlight the wider scientific context of the work:

“Weld line problem occures in many industrial applications, including aerospace [9], microelectronics, micro-injection molding [10] and multifunctional structures in embedded electronic components [11], automotive industries, telecommunication systems and medical engineering [12].”

Comments 2: Could the authors clarify how the optimization time scales with the complexity of the part geometry?

Response 2: Thank you for your comment. We have reviewed the proposed algorithm on model functions such as the Ackley function, which allows us to assume that is robust to a large number of local extrema we suggest that the convergence rate of the proposed algorithm algorithm is weakly dependent on the part’s geometric complexity. A quantitative assessment of this hypothesis requires a comparison of different geometries, which is planned for future studies. We added a paragraph to the Section 2.2.1:

“The proposed algorithm does not require the calculation of the derivatives of the objective function and performs a global search for an extremum. Tests on various multidimensional mathematical functions, such as the Ackley function, demonstrate the reliable detection of optimal solutions, even in the presence of multiple extrema [43]. Since the proposed algorithm is robust to a large number of local extrema we suggest that the convergence rate of the algorithm is weakly dependent on the part’s geometric complexity. The search space’s dimensionality has the most significant influence on the number of iterations. Thus, the proposed algorithm can be directly generalized to multi-gate systems by increasing the number of design variables: three design variables for each melt entry point.”

Comments 3: This may help future users understand limitations in more intricate parts.

Response 3: We've expanded the article to include a hypothesis about the impact of part complexity and the number of gates on the optimization algorithm (more details are provided in the answer to the previous point). We hope that it may help future users understand limitations in more intricate parts.

Comments 4: Would it be possible to briefly discuss whether the weld line strength factor varies significantly across different fiber orientations?

Response 4: Near the weld line, the fibers are located in the plane of the weld line, since their orientation is determined by the injection molding hydrodynamics. We briefly discussed this issue and add several references:

"The orientation of fibers near the weld line is determined by the hydrodynamics of melt front convergence: fibers near the weld line lie in the weld plane, which is one of the reasons for the reduction in material strength [45,46,47]. Accounting for this effect does not require recalculating the equivalent stress field, but can be accomplished by reducing the permissible value of the equivalent stress limit."

Comments 5: You may already show this in Figure 15, but a short comment in the discussion could make it clearer.

Response 5:Thanks for the recommendation, we briefly discuss this question is the figure 14 (ex 15) and provided a quote in response to the previous point.

Comments 6: In the Methods section, could you add one sentence clarifying if the interpolation step introduces any error in the stress transfer from ANSYS to Moldflow?

Response 6:Thank you for your comment. We added text to the Section 2.2.5:

“In this case, the error in stress interpolation is reduced to a minimum due to the fact that the mechanical and hydrodynamic computational meshes have practically the same element size.”

Comments 7: This is useful for readers who want to validate this hybrid simulation strategy.

Response 7: Thank you for your recommendation. We’ve taked it into account by aswering the previous point.

Comments 8: Is the optimization approach scalable to multi-gate systems or conformal cooling designs?

Response 8: Thank you for your comment. We added a paragraph to the Section 2.2.1:

“The search space’s dimensionality has the most significant influence on the number of iterations. Thus, the proposed algorithm can be directly generalized to multi-gate systems by increasing the number of design variables: three design variables for each melt entry point.”

Comments 9: If yes, a short mention in the conclusion or outlook would be interesting for industrial applications.

Response 9:Thanks for the recommendation, we briefly mentioned this in the conclusion:

"The developed technology can be used in multi-gate molding cases by increasing the number of design variables, adding three design variables for each melt entry point."

Comments 10: Could you explain whether the developed method is compatible with other commercial solvers beyond Moldflow and ANSYS (for example: Abaqus, Simulia)?

Response 10:Thank you for your comment. We added a paragraph to the Section 2.2.2:

“The proposed optimization technology can be implemented as a plug-in or add-on based on any commercial CAE solver (including Simulia Abaqus) or open-source solvers (such as Open-Foam). A console interface or API that provides access to the data needed to calculate the objective function is the main requirement.”

Comments 11: Would it be beneficial to add a small comment in the Conclusion on how this method could support predictive design in aerospace or biomedical mold parts? Especially considering composite implants or lightweight structures.

Response 11: Thank you for your comment. Thanks for the recommendation, we briefly mentioned this in the conclusion:

“The obtained results confirm the adequacy and applicability of the methods used to improve the quality of short-reinforced composite materials by injection molding. The use of the proposed technology is particularly relevant in the aerospace and automotive industries, as significant economic benefits from saving the weight of structures in these areas of application.”

While preparing the literature review, we found more examples from aerospace and automotive industries, so we noted this point. Regarding the biomedical industry, we believe this is possible, but we cannot provide specific examples, so we left this point outside the main text of the manuscript.

Comments 12: Regarding Figure 23–24, is there any indication of local delamination or matrix cracking observed during testing in brackets with weld lines? Even a short comment would strengthen the mechanical interpretation.

Response 12: Thank you for your recommendation. We have added a short comment regarding the delamination issue in the figure with fracture site microscopy:

“Electron microscopic examination of the fracture surfaces of the brackets and test specimens revealed no delamination of the material. This is due to the short reinforce-ment of the material and the presence of fibers in various directions.”

Comments 13: These are only humble suggestions and questions intended to slightly improve the clarity and perspective of your promising and well-written work. The core contribution is strong and useful for both academic and industrial readers.

Response 13: Thank you for your review, we have tried to take all the recommendations into account.

Reviewer 3 Report

Comments and Suggestions for Authors

This manuscript investigates the problem of weld line formation in injection molding of short fiber–reinforced composites. The authors propose an automated gate location optimization framework that integrates a modified genetic algorithm with technological constraints into a modular system combining ANSYS and Moldflow. The study is practically relevant and demonstrates industrial applicability. Nevertheless, several issues should be addressed before the manuscript can be considered for publication:

1. The novelty of the proposed method is not sufficiently highlighted. The authors should more clearly articulate how their modifications to the genetic algorithm and integration framework differ from existing approaches in the literature.
2. The description of the methodology is overly detailed in terms of software operations and interface procedures, which makes parts of the paper resemble technical documentation. The presentation should emphasize the scientific rationale and methodological insights rather than procedural steps.
3. Several figures (e.g., 6–8, 9–13) are direct screenshots of software interfaces, file formats, or code outputs. Such figures are not in line with academic standards. The authors are encouraged to replace them with professional schematics, abstracted diagrams, or reformatted plots that highlight the underlying workflow and results more clearly.
4. The convergence analysis of the optimization algorithm is presented, but the discussion of parameter sensitivity and robustness remains limited. Additional analysis of how population size, mutation rates, and constraint handling affect convergence would enhance methodological rigor.
5. The link between computational optimization results and the observed microstructural evidence is underdeveloped. The discussion should more explicitly relate weld line relocation to fiber orientation, fracture mechanisms, and mechanical behavior.
6. The paper would benefit from a clearer comparison with alternative optimization methods (e.g., Taguchi, FEM-based design, or machine learning approaches) to demonstrate the advantages and limitations of the proposed framework.
7. The language and presentation could be further improved for clarity and conciseness. In particular, reducing redundancies in the methodology and ensuring consistent terminology would improve readability and impact.

Author Response

Comments 1: The novelty of the proposed method is not sufficiently highlighted. The authors should more clearly articulate how their modifications to the genetic algorithm and integration framework differ from existing approaches in the literature.

Response 1: Thank you for your comment, we have expanded the description of scientific novelty.

“The scientific novelty of this study is the development of technology for the automated design of a gating system based on parametric optimization algorithms, con-sidering technological constraints. It allows the calculation of the optimal melt injection points into the cavity part to increase the load-bearing capacity of products manufactured by molding from thermoplastic material at the design stage. The modular structure of the software, which allows for the flexible connection of CAE solvers convenient for the end user, is a distinctive feature of the technology implementation. An experimental assessment of the strength of material specimens and structures containing a weld line was experimentally assessed. It was experimentally confirmed that the developed technique can be used to manufacture aerospace struc-tures and allowed increasing the strength of the product by 2 times.”

Comments 2: The description of the methodology is overly detailed in terms of software operations and interface procedures, which makes parts of the paper resemble technical documentation. The presentation should emphasize the scientific rationale and methodological insights rather than procedural steps.

Response 2: Thank you for your recommendation. We have revised the presentation of the article, adding more comparisons and conclusions, and reworked the figures, summarizing them and making them more schematic. We expand Introduction and Conclusion to show more cases of application the proposed technology. We add more descrpition of brackets and samples failure, describe more of convergance analisys and fiber orientation modeling validation.

Comments 3: Several figures (e.g., 6–8, 9–13) are direct screenshots of software interfaces, file formats, or code outputs. Such figures are not in line with academic standards. The authors are encouraged to replace them with professional schematics, abstracted diagrams, or reformatted plots that highlight the underlying workflow and results more clearly.

Response 3: Thank you for your comment. We've significantly revised the figures in this article, convert screenshorts to shematics, tables and algorithms and tell some information in text.

Comments 4: The convergence analysis of the optimization algorithm is presented, but the discussion of parameter sensitivity and robustness remains limited. Additional analysis of how population size, mutation rates, and constraint handling affect convergence would enhance methodological rigor.

Response 4: Thank you for your comment. We have completed additional analys of mutation rates (figure 11), addition to population size and constraint handling affect presented at fig. 10:

“Mutation rates analysis carried out for the considering technological constraints and 12 in-dividuals in population case (figure 11). The relative diameter d of the mutation (as a ra-tio to the part size) and the number Nmut of mutated individuals in population are varied. In the case studied, they showed good results with d=0.4, and Nmut=1. In all cases, convergence is achieved by the 3rd generation, so that the influence of the mutation is limited by the spread of individuals in the second iteration.”

Comments 5: The link between computational optimization results and the observed microstructural evidence is underdeveloped. The discussion should more explicitly relate weld line relocation to fiber orientation, fracture mechanisms, and mechanical behavior.

Response 5: Thank you for your recommendation, we have significantly expanded the description of microscopy by adding sentences that relate weld line relocation to fiber orientation, fracture mechanisms, and mechanical behavior.

“Using a Tescan Vega electron microscope, a comparison was made between the orientation of the fibers at the fracture sites of bracket samples manufactured with dif-ferent gate locations, as well as a comparison of the orientation of the fibers at the frac-ture sites of the witness samples (Figure 21). Tests showed that fracture of brackets molded from the side entrance of the melt occurs along the weld line. The side-molded bracket fracture is located along the weld line, and the fibers lie predominantly in the fracture plane. It is one of the reasons for the reduced strength of the brackets with weld line problem. The front-molded bracket does not contain a weld line at the frac-ture site and the fibers in fracture place are predominantly perpendicular to the fracture plane (along the molding). A similar pattern is observed in witness specimens molded with and without a weld line: in the case of a weld line samples, the fibers are in the plane of the mold front closure, while in the specimen without a weld line, they are aligned with the molding direction.”

Also we add in figure comparison between expimental and computational results and tell about it in text before figure:

"Moldflow calculations of the fiber orientation tensor are consistent with electron microscope data, which validates the modeling methodology.“

Comments 6: The paper would benefit from a clearer comparison with alternative optimization methods (e.g., Taguchi, FEM-based design, or machine learning approaches) to demonstrate the advantages and limitations of the proposed framework.

Response 6: Thank you for your recommendation, we add comparison with alternative optimization method in Conclusion.

“The technology develops standard FEM-based design methods for optimizing process parameters [48] by using geometric operations to search gate locations nodes on the computational mesh in the crossover and mutation operators of the proposed metaheuristic algorithm.”

Comments 7: The language and presentation could be further improved for clarity and conciseness. In particular, reducing redundancies in the methodology and ensuring consistent terminology would improve readability and impact.

Response 7: Thank you for your comment, we have tried to improve the quality of the language.

Reviewer 4 Report

Comments and Suggestions for Authors

• Injection mold design technology to locate weld lines away from 3 highly loaded structural areas: paper is useful, but it must be improved to include more Scientific impact, see that This article introduces an automated injection molding gate placement method using a parametric optimization algorithm with technological constraints. A modified genetic algorithm optimizes gate location by minimizing maximum equivalent stresses on weld lines. The modular software integrates custom optimization modules with Ansys and Moldflow via API, enabling application to complex industrial models. Considering constraints reduces population size and cuts computation time by 1.9×. The approach is demonstrated on an aerospace bracket made of short-fiber composite with a weld line, showing practical effectiveness, was partially in Process planning for reliable high-speed machining of moulds, International Journal of Production Research 40 (12), 2789-2809 or when stamping dies are working in Prediction of press/die deformation for an accurate manufacturing of drawing dies, The International Journal of Advanced Manufacturing Technology 37 (7), 649-656 because the press deformation affects welding joints, so please update.
• Errors are typical when a die or a mould is closed, so discuss: uncertainty of the results:
  • Moulds shape
  • Deformations
• Why this testpiece?? It is too simple
• There are too many coloured figures; take care because ANSYS is only for research, so Figure 18 can be eliminated. 4-5 figures less would be good.
• Conclusions: weak, give 4-5 as points.
• References are OK, However update with recent works in Results in Engineering, JESTECH, Alexandria, etc…I see many journals missed.
• Figure 23. Eliminate, we see this is conventional testing procedure.
• Figures 14-15 can be merged into 1.
• The paper is OK, sueful for people working on casting.
• GateOptWeld3D, a MATLAB-based modification of the genetic algorithm, optimizes melt entry points for any product shape. Technological constraints limit candidate locations to feasible regions, reducing search space, population size, and computation time. With constraints, 12 individuals suffice (28 function calls), while unconstrained problems require 30 individuals (54 calls).
• Is Negri-Bossi a regular plastic injector machine?

Author Response

Comments 1: The approach is demonstrated on an aerospace bracket made of short-fiber composite with a weld line, showing practical effectiveness, was partially in Process planning for reliable high-speed machining of moulds, International Journal of Production Research 40 (12), 2789-2809 or when stamping dies are working in Prediction of press/die deformation for an accurate manufacturing of drawing dies, The International Journal of Advanced Manufacturing Technology 37 (7), 649-656 because the press deformation affects welding joints, so please update.

Response 1: Thank you for your recommendations. We've added these articles to the list of references and included them in the introduction:

"Speeding up the time to market requires reducing mold design and manufacturing time [4], including using modern CAE systems [5,6]"

Comments 2: Errors are typical when a die or a mould is closed, so discuss: uncertainty of the results: Moulds shape, Deformations.

Response 2:Thank you for your comment. We've added a paragraph on this issue to Section 2.2.6.

«The possible runner geomerty and gate location depends on complexity of mold shape, and technological features of the injection molding process, including limitations on gate diameter, issues of mold deformation and organization of part ejection. »

Comments 3: Why this testpiece?? It is too simple

Response 3: Thank you for your question, we have provided a detailed answer in paragraph 3.1:

«This testpiece was chosen because it reflects the key features of aerospace components. It contains tension/compression flanges and shear web, relief openings, and the resulting weld line. The advantage of its simple form is its focus on the weld line issue under investigation, with minimal influence from other factors, which facilitates the validation process. The testpiece can also be manufactured in flat molds without slides. »

Comments 4: There are too many coloured figures; take care because ANSYS is only for research, so Figure 18 can be eliminated. 4-5 figures less would be good.

Response 4:Thank you for your comment. We've significantly revised the figures in this article, convert screenshorts to shematics, tables and algorithms and tell some information in text. As a result, after all the edits, there were 5 fewer figures.

Comments 5: References are OK, However update with recent works in Results in Engineering, JESTECH, Alexandria, etc…I see many journals missed.

Response 5:Thank you for your comment, we have added several articles to introduction from the journals you suggested, they have been very useful for us. We have added references to Results in Engineering and Alexandria journals. The total number of references increased from 33 to 48.

Comments 6: Figure 23. Eliminate, we see this is conventional testing procedure.

Response 6:Thank you, this figure has been corrected.

Comments 7: Figures 14-15 can be merged into 1.

Response 7:Thank you for your comment, we have combined these figures.

Comments 8: Is Negri-Bossi a regular plastic injector machine?

Response 8: Yes, a regular electric injection molding machine. Its peculiarity is electric injection unit, which allows for precise control of injection speed. We reflect this peculiarity in the manuscript in words «electric injection molding machine».

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

I don't have additional questions.