Influence of Crushed Rock Properties on the Productivity of a Hydraulic Excavator

Round 1

Reviewer 1 Report

The reviewer thanks the authors and editors for the opportunity to review the manuscript.

The authors generally identify the determinants of hydraulic excavator productivity. However, a more detailed literature review is missing here.

The paper seems interesting; however, there is a lack of clear emphasis on what is new in this article. Determining the productivity of hydraulic excavators has been the object of research of many scientists and this issue is quite well recognized. The research methods used in the paper seem interesting. The paper needs to be extended and take a wider look at the aspects affecting the productivity of the excavator.

Author Response

Part A (Response to Reviewer 1)

Question# The authors generally identify the determinants of hydraulic excavator productivity. However, a more detailed literature review is missing here.

Answer: Thank you for the instructive suggestion which has greatly helped us to improve our article. We have add more comments on related literature in Introduction. It can be seen at lines: 37 to 60 and 78 to 88, and at the end of the article in list of references, numbers: 4 – 17 and 26 and 27.

Question# The paper seems interesting; however, there is a lack of clear emphasis on what is new in this article. Determining the productivity of hydraulic excavators has been the object of research of many scientists and this issue is quite well recognized.

Answer: Thank you for suggestion that attribute to the highlighting contributions of our research. We have highlighted our aims of research in Introduction (lines: 96 to 109) where we emphasize our aims at analysing influence of the angle of repose of material on the productivity of the excavator and to investigate connections between bucket fill factor and swell factor of material being manipulated. These two properties are relatively sparsely represented in the relevant literature. Also, the accent has been given on simultaneous effect of multiple properties of crushed stone on the productivity of excavator in the conditions prevailing at examined quarries. At the end of the article, in Conclusion, we stressed the main achievements of research.

Statement: The research methods used in the paper seem interesting.

Answer: We are grateful that you find our research methods interesting.

 Question# The paper needs to be extended and take a wider look at the aspects affecting the productivity of the excavator.

Answer: Thank you for suggestion that wider the perspective of our review of factors influencing productivity of the excavator to which we have appointed at the Introduction, see lines 37 to 95.

Author Response File: Author Response.docx

Reviewer 2 Report

Authors of this manuscript entitled "Influence of crushed rock properties on productivity of a hydraulic excavator" have set themselves the goal of their research the influence analysis of independent variables with respect to hydraulic excavator’s productivity.

The following comments will help the authors to improve the quality of the manuscript. Please see the comments below:

• The aims of this study in the “Introduction” need to be modified for clarification in the paper.
• Chapter 2. To increase the reliability of this paper, detailed information is required about field research such as data collection method, field test date/duration, number of samples and etc. It is difficult to trust the data because the detailed information is missing.
• Chapter 4. Before regression analysis, it is necessary to analyze the selection of the independent variables and the correlation between variables.
• In regression model (10), it is necessary to confirm why Adjusted R2(0.995984) is analyzed as an extremely high value. Also, there is no verification process for the final regression model.
• Above all, in the regression model, the number of samples is not enough (n=7). Because it cannot be assumed that the samples are normally distributed, the reliability of the regression model is very poor. Regression analysis is not considered an appropriate research methodology for this study.
• Another separate section is needed to discuss the “limitations and future directions” before writing the “conclusions”.
• Throughout the paper (even in figures), when expressing the decimal point, (,) and (.) are mixed, so form unification is necessary.

Author Response

Part B (Response to Reviewer 2)

Question# The aims of this study in the “Introduction” need to be modified for clarification in the paper.

Answer: Thank you for suggestion that helps us to clarify our aims of research which have been better described in “Introduction”, see lines: 96 to 109. Furthermore, the abstract was also rewritten, and objectives of research are more clearly presented.

Question# Chapter 2. To increase the reliability of this paper, detailed information is required about field research such as data collection method, field test date/duration, number of samples and etc. It is difficult to trust the data because the detailed information is missing.

Answer: Thank You for the suggestions. Chapter 2 was rewritten and rearranged to be more comprehensible and details on performed measurement were appended. Major changes being paragraph 3:

“The measurement procedure at every location composed of loading the bucket and taking photographs of the top material for measurement of angle of repose. Next step was taking photographs of the empty ground in the marked area. After unloading the bucket to the same area, heap was photographed which served for volume of bucket load determination as well as particle size distribution. Afterwards, video recording was started and minimum of 100 excavator cycles were recorded. The procedure was repeated three times and given results represent average values.”

and paragraph 5:

“Granulometric analysis of each relevant rock material was performed by taking digital images of a heap, simultaneously with volume measurement (Figure 2a). Two images from opposite angles were selected for the analysis to give representative parameters of a material. Digital images (Figure 3a) were processed by Wipfrag computer software for granulometric analysis and parameters of rock particle size distribution was obtained (Figure 3b).”

Question# In regression model (10), it is necessary to confirm why Adjusted R²(0.995984) is analyzed as an extremely high value. Also, there is no verification process for the final regression model.

Answer: The authors are aware of the very high value Adj. R², an explanation for this is given in the accompanying text (lines 332 - 338) as follow:

“However, due to the extremely large values of performance parameters, e.g. Adj. R² is 0.995984 there is a reasonable suspicion that overfitting has occurred in this model. So the estimation equation will very well approximate the initial data on which it is made. Therefore, it is likely that it would not be as good as the general model by which Q_vm could be estimated. Besides, the cross-correlation of the independent variables shown in Table 5 allows the rejection of independent variables.”

The authors are aware that, unfortunately, the complexity of the research has conditioned that they have not yet managed to collect enough data for the full validation of the model, but they will certainly do further research on this topic. This fact also mentioned in the new chapter of “limitations and future directives”.

Question# Above all, in the regression model, the number of samples is not enough (n=7). Because it cannot be assumed that the samples are normally distributed, the reliability of the regression model is very poor. Regression analysis is not considered an appropriate research methodology for this study.

Answer: We are grateful for your professional opinion. We have used it to highlight the shortcomings and limitations of our research in a separate chapter “limitations and future directives”.

Question# Another separate section is needed to discuss the “limitations and future directions” before writing the “conclusions”.

Answer: Thank you for your suggestion that helps to completeness of our paper. We have added separate section “Limitations and future directions” as you requested, see lines 346 to 357.

Question #: Chapter 4. Before regression analysis, it is necessary to analyze the selection of the independent variables and the correlation between variables.

Answer: The accompanying text (lines 292 - 299) and the new table 5 with correlations between the variables are made by the authors as follow:

The independent variables are the results of measurements and granulometric analysis from Table 1. The correlation between these variables is shown in Table 5.

Table 5. correlation between variables.

A_T – slew angle of excavator; A_r – angle of repose; n - coefficient of uniformity of the particle size distribution; X_c – characteristic particle size; d_{50 – 80 %} of particles size are less than this dimension

In general, it can be mentioned that Ar and d80 have the most significant degree of correlation with all other variables, while d50 correlates the least with all other variables.

Question #: Throughout the paper (even in figures), when expressing the decimal point, (,) and (.) are mixed, so form unification is necessary.

Answer: The entire text of the article was checked and the decimal point in the text was unified. This was also done in Figures 5, 6, and 7 also in Tables 1 and 4.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The reviewer thanks for the responses sent and the corrections made to the manuscript. I accept the changes.

Reviewer 2 Report

The manuscript seems to have been appropriately revised according to the comments of this reviewer.