Modeling and Predicting the Machined Surface Roughness and Milling Power in Scot’s Pine Helical Milling Process

Round 1

Reviewer 1 Report

Dear author

this article is very interesting, but for the further possibility of publication, it is necessary to realize the changes above mentioned:

1. provide better analysis of state of the art in the research area
2. reference for equation No. 1 is missing
3. provide better graphical interpretation of experimental setup in graphical abstract, figure 1 is not necessary to add to this article; information about experimental setup should be present clearly in the text
4. why do not use the DOE (design of experiment) in your study?
5. provide information about the selection of the variables in your study
6. provide a better quality of figure no. 2
7. what kind of software do you use for model prediction described in Equations 2-4?
8. the conclusion part is very short, please provide a better explanation of obtained results and the contribution to the practice or research area

Author Response

this article is very interesting, but for the further possibility of publication, it is necessary to realize the changes above mentioned:

1. provide better analysis of state of the art in the research area

Dear reviewer, thanks for your professional and valuable suggestions. We have revised the manuscript carefully. The introduction of this manuscript was improved.

2. reference for equation No. 1 is missing

We have added two references for RSM and equation 1.

Li, R.; Yao, Q.; Xu, W.; Li, J.; Wang, X. Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards. Materials 2022, 15, 879, doi:10.3390/ma15030879.

Wu, Z.; Buck, D.; Jin, D.; Guo, X.; Cao, P.; Zhu, Z. Investigation on Milling Quality of Stone–Plastic Composite Using Response Surface Methodology. JOM 2022, 74, 2063–2070, doi:10.1007/s11837-021-05024-y.

3. provide better graphical interpretation of experimental setup in graphical abstract, figure 1 is not necessary to add to this article; information about experimental setup should be present clearly in the text

We have moved the figure 1 and check the information about experimental setup. The experimental setup and process are clearly described.

4. why do not use the DOE (design of experiment) in your study?

Experimental design is a branch of mathematical statistics. It is a mathematical principle and implementation method about how to make appropriate experimental scheme according to the predetermined goal, so as to facilitate the effective statistical analysis of experimental results. RSM can establish a continuous variable surface model, to evaluate the factors and their interactions that affect the machining process, and to determine the optimal level range.

It is widely applied for revealing the effects of processing parameters on response parameters, and optimize the input parameters. Such as the follow references.

Zhu, Z.; Buck, D.; Cao, P.; Guo, X.; Wang, J. Assessment of Cutting Forces and Temperature in Tapered Milling of Stone–Plastic Composite Using Response Surface Methodology. JOM 2020, 72, 3917-3925, doi:10.1007/s11837-020-04368-1.

Li, R.; Yao, Q.; Xu, W.; Li, J.; Wang, X. Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards. Materials 2022, 15, 879, doi:10.3390/ma15030879.

5. provide information about the selection of the variables in your study

The input parameters and their ranges were selected by preliminary test, previous studies and actual processing requirement. The selected parameters are important variables of the helical milling, and they had significant influences on cutting force, cutting energy during some other materials processing. The parameters were applied in the Dehua TB New Decoration Material Co., Ltd. to manufacture the wooden flooring. The detailed ranges of the selected variables are also proved by the following references, which have been listed in the references.

Zhu, Z.; Buck, D.; Guo, X.; Cao, P.; Wang, J. Cutting performance in the helical milling of stone-plastic composite with diamond tools. CIRP Journal of Manufacturing Science and Technology 2020, 31, 119-129, doi:10.1016/j.cirpj.2020.10.005.

Li, R.; Yao, Q.; Xu, W.; Li, J.; Wang, X. Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards. Materials 2022, 15, 879, doi:10.3390/ma15030879.

6. provide a better quality of figure no. 2

We have revised the figure 2. The figure 2 was improved with the resolution of 1212 pixel × 458 pixel. We hope it could be accepted for the readers.

7. what kind of software do you use for model prediction described in Equations 2-4?

Design Expert software was applied to modelling and data analysis.

8. the conclusion part is very short, please provide a better explanation of obtained results and the contribution to the practice or research area

We have improved the conclusions.

Reviewer 2 Report

This paper is mainly reporting the Modeling and predicting the machined surface roughness and milling power in Scot’s pine helical milling process. The experimental and statistical results are obtained in this context. Some interesting results are obtained. However, the following revisions should be made.

The Quality of some Figures must be improved. Ex. Please, see Figure 3. Also, font size of Figure 2 is very small. The remaining figures must be revised.

All text must be well formatted. Ex. In page 3 of 13, above and below table 1 must have a space. The same situation bellow Figure 2, Figure 5, etc. The remaining paragraph must be verified.

Author Response

Dear reviewer, thanks for your professional and valuable suggestions. We have revised the manuscript carefully. The figures and formation of the text were revised.

Reviewer 3 Report

The article focuses on the regression modeling and optimization of machined surface roughness and milling power in Scot’s pine helical milling operation using ANOVA and RSM. The intention of the work is good although to enhance the quality of the manuscript, I have some comments, questions, and suggestions.

 

1. The abstract is general. It should refer more to the results obtained, and specific values.
2. In the introduction section, references should be discussed instead of being cited successively.
3. In order to increase the quality of the literature review, you need to add some recently published papers on regression modeling and optimization of surface roughness parameters induced by machining processes. I recommend authors to add the following paper to the introduction section:

• Effect of turning environments and parameters on surface integrity of AA6061-T6: experimental analysis, predictive modeling, and multi-criteria optimization. Int J Adv Manuf Technol110, 2669–2683 (2020).

4. Please explain why you have chosen these input variables including the helical angle of milling cutter, rotation speed of main shaft, and depth of milling for your design of experiment.
5. Please correct the dictation of “angle” in Table 2.
6. Please provide more detail about experimental processes for the measurement of surface roughness.
7. Please indicate the equations of the quadratic model, the coefficient of determination (R²), and optimization.
8. Please add lack of fit and adequate precision to the ANOVA tables (4, 5, and 6).
9. Please explain more about your optimization. Is it single-optimization or multi-criteria-optimization considering both surface roughness and milling power?
10. A deeper discussion of the results obtained is necessary. In the discussion of the results, it is very important to emphasize points of agreement or disagreement between results in this work and others cited in the references part of the manuscript.

 

In conclusion, If the authors apply the corrections to the manuscript within due time, the manuscript will be suitable for publication in "Machines".

Author Response

The article focuses on the regression modeling and optimization of machined surface roughness and milling power in Scot’s pine helical milling operation using ANOVA and RSM. The intention of the work is good although to enhance the quality of the manuscript, I have some comments, questions, and suggestions.

Dear reviewer, thanks for your professional and valuable suggestions. We have revised the manuscript carefully.

1. The abstract is general. It should refer more to the results obtained, and specific values.

We have revised the abstract. The purposes and achievements were presented, the text of abstract was also improved. Now, the methods, results, some conclusions, and research significance were presented in the new abstract.

2. In the introduction section, references should be discussed instead of being cited successively.

We have revised the introduction. The literature review in the “Introduction” was revised and improved. Some discussions about the references were added in the introductions.

3. In order to increase the quality of the literature review, you need to add some recently published papers on regression modeling and optimization of surface roughness parameters induced by machining processes. I recommend authors to add the following paper to the introduction section:

• Effect of turning environments and parameters on surface integrity of AA6061-T6: experimental analysis, predictive modeling, and multi-criteria optimization. Int J Adv Manuf Technol110, 2669–2683 (2020).

The above reference is valuable and it is related to the research content of our research. We have cited the above reference in this manuscript. The addition of new references will improve the literature review. And some other new references were also added.

4. Please explain why you have chosen these input variables including the helical angle of milling cutter, rotation speed of main shaft, and depth of milling for your design of experiment.

The input parameters and their ranges were selected by preliminary test, previous studies and actual processing requirement. The selected parameters are important variables of the helical milling, and they had significant influences on cutting force, cutting energy during some other materials processing. The parameters are applied in the Dehua TB New Decoration Material Co., Ltd. to manufacture the wooden flooring. The detailed ranges of the selected variables are also proved by the following references, which have been listed in the references.

Zhu, Z.; Buck, D.; Guo, X.; Cao, P.; Wang, J. Cutting performance in the helical milling of stone-plastic composite with diamond tools. CIRP Journal of Manufacturing Science and Technology 2020, 31, 119-129, doi:10.1016/j.cirpj.2020.10.005.

Li, R.; Yao, Q.; Xu, W.; Li, J.; Wang, X. Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards. Materials 2022, 15, 879, doi:10.3390/ma15030879.

5. Please correct the dictation of “angle” in Table 2.

The word was misspelt. We have revised all the word of “angle” in the text and figures.

6. Please provide more detail about experimental processes for the measurement of surface roughness.

The test area is located in the middle of milled surface, with a sampling length of 10 mm. The test direction is parallel to the wood fiber direction and also parallel to the milling feed direction. Each surface roughness test was repeated five times in different position, the meaning value of these five results was chosen to estimate the surface roughness. All these texts were put in the section of “Materials and Methods”.

7. Please indicate the equations of the quadratic model, the coefficient of determination (R²), and optimization.

The coefficient of determination for the created quadratic models were shown in Table 7. The optimization was accomplished in section of “3.5 Optimization of processing parameters”. The higher correlation coefficient, the better the fitting effect of the model is. Hence, the quadratic models were selected to create the relationship between input parameters and response parameters.

8. Please add lack of fit and adequate precision to the ANOVA tables (4, 5, and 6).

This information was added in the tables 4-6. Hope this information could be explain the ANOVA results of response parameters.

9. Please explain more about your optimization. Is it single-optimization or multi-criteria-optimization considering both surface roughness and milling power?

It is a multi-criteria-optimization considering both surface roughness and milling power in this study. The condition for the input parameters is “in range”. And the goals of these two response parameters were all set to “minimize”, to achieve the purpose of better surface quality and low power consumption. This information was written in the section of “3.5 Optimization of processing parameters”.

10. A deeper discussion of the results obtained is necessary. In the discussion of the results, it is very important to emphasize points of agreement or disagreement between results in this work and others cited in the references part of the manuscript.

We have revised the discussions. The results of this study have good agreement with the present results of wood-based composites and SPC materials helical milling. The achievements of this research and some research significances were added.

 

In conclusion, If the authors apply the corrections to the manuscript within due time, the manuscript will be suitable for publication in "Machines".

Round 2

Reviewer 1 Report

Dear authors,

 

thank you very much for revision of your paper. Now, this article is possible to publish in present form.

Author Response

Thank you for your reviewing