Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors
Round 1
Reviewer 1 Report
Review Report
1) There are repetitions in writing of this manuscript:
- In Introduction part,
In Line 27, 32-33, 36, 39, 45 and 46
The group of words “agricultural machinery and vehicles” is used many times, it should be corrected.
2) In this manuscript there are some methods used and mentioned in it for simulation and correlation processes such as Monte Carlo (MC), Latin hypercube sampling (LHS), Imam-Conovor (I-C) and (LHS-IC) etc. Also, it is mentioned to use several statistical methods as Statistica computer program. Trying to get the connection between all the methods is not easy. Therefore, the explicit and sufficient explanation of this connection is important.
3) The other important thing is about applying the procedure in the study. The work of study mainly depending on the topic of randomly generating number seems to be valuable and it includes general results but it cannot be understood well for which of the farm tractors components are applied specifically it is not mentioned in the manuscript.
Our final decision is that if the above recommendations are satisfied exactly, it can be accepted for publication in Applied Sciences of MDPI.
Dr. Metin AKTAŞ - Reviewer 27 October, 2022
Author Response
Dr. Metin AKTAŞ - Reviewer
1) I will delete the repetitions.
2) Only the pseudorandom number generation methods available in Statistica were used for the simulation. The choice was therefore limited. I also did not go into the methodology of their functioning, but showed their practical application.
3) Table 1 shows only the times of failure of specific tractors. The causes of these lesions vary (they belong to up to 22 groups). However, for the sake of readability of the table, they have been omitted. Now I will add.
Author Response File: 
Author Response.docx
Reviewer 2 Report
This paper presents a measure of the reliability of the farm tractors using one public dataset. The novelty of the paper is not clear. I’d suggest rejecting the paper in current form. The inadequacy of the paper is described with the comments listed below for reference.
Abstract is not well-written, in which the contribution of the paper is not precisely and concisely pointed out. All the methods mentioned, such as MC, LHS are well-established. Authors need to explicitly state how they tackle the current challenge to evaluate the reliability.
It seems that in this work, authors just used a software, called Statistica which is embedded with some normal functions/methods, i.e., MC and LHS to analyze one public dataset. This seems like a routine analysis.
The results and relevant discussions are very weak. As an audience, it is difficult to find the key take-away from the results. Is there any benchmark that can help to verify how excellent the algorithm is. Again, MC and LHS are not new methods. Authors just used them instead of conducting secondary development in terms of algorithmic aspect.
The figures (figure 1,2) with non-white background look weird.
Author Response
Thank you very much for your review. Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
- Overall, the paper is well conceived and written. It is based on a highly theoretical approach, trying to alleviate the disadvantage of lacking relevant data on failures of farm tractors and different mechanical equipment that is used in different operations. As is known, when trying to establish the reliability of a certain type of equipment, most of the information collected needs lots of time to be produced. The process of estimating the reliability function via simulation runs into the difficulty of having a real random number generator with a certain type of distribution. From this point of view, the authors of the article are trying to obtain a solution that is satisfactory for the specific case of farm tractor reliability analysis.
- The organization of the paper is according to MDPI specifications regarding formatting and contents of the paperwork.
- There were no major English grammar or syntax errors encountered during the read of the article.
- I recommend improving either the introduction and the conclusions sections by showing specificities of the domain in analysis: typical cases where malfunctions of tractors are due to flaws in design, exploitation, and/or too long maintenance intervals - if available. And also how can be the proposed solution improved in the future.
Author Response
Thank you very much for this opinion. I will try to correct the manuscript taking into account your comments.
autor
Author Response File: Author Response.docx
Reviewer 4 Report
In this paper, the authors used the Statistica computer tool to analyse failure times of technological devices, including agricultural machinery and vehicles. An attempt was made to select the best statistical method (Monte Carlo, Latin hypercube sampling or Iman-Conover) to analyze the topic, which unfortunately was not achieved. In my opinion, the topic of the article does not exactly reflect its content.
Because the authors have attempted to select a random number generator to measure the reliability of agricultural tractors, and as a result do not point to any method as the best, perhaps the title should be changed.
In addition, an attempt was made to analyze the failure times of process equipment for various agricultural machinery and vehicles, and the data analyzed was only for 4 Zetor models.
In the paper does not show from which years these data were taken. Referring the reader to the literature on this issue is not serious.
I think, the paper needs to be revised, as it is only an engineering study in its current form.
Weak
In my opinion, a weakness of this paper is the insufficient description of the state of the issue with only 28 references to the literature even though 35 percent of the bibliographic items are publications no older than 3 years. Supplementation in this regard would certainly increase the value of the paper. There is also a lack of more in-depth analysis of the issue at hand.
The cursory analysis of the issue presented does not provide a clear summary, and no research gap is apparent from reading it.
The way the results are presented (only 3 Figures and 1 Table) and its analysis deviates from the common standards. It should be more insightful.
The combination of the 4th Discussion and Conclusions is uncommon. In my opinion, this chapter should be divided into two:
4. Discussion
5. Conclusions
The number of self-citations in the paper is dangerously approaching the limit of decency and reached 25%. This is not correct practice.
Noticed errors/remarks
• Lines 17, 71: The two terms random number and pseudorandom number cannot be equated, as the authors clearly describe later in the article. Random number generator and pseudorandom number generator are not the same thing, and these names cannot be used interchangeably. Please correct these sentences.
• Lines 71, 109 and 120 contain "wholesale" numbers of literature references without any, even a brief, characterization of each. This is not correct practice for more than 2 to 3 references.
• Line 108: Optimization has a broader meaning than minimization. The minimum value can be one of the criteria for optimization. I propose to correct the wording: optimization (minimization) to: optimization (minimization in this case).
Small errors
I hope a typographic type only. They do not diminish the value of work, but they must be corrected.
· Line 130. Where did the acronym SMCC (Fast Monte Carlo Methods) come from? Shouldn't it be FMCM?
· Line 318. What is “Conlusions”?
Author Response
Thank you for a very honest review. It turns out that each manuscript can still be refined, all you need is the right expert. Lots of comments, but accurate. I will try to correct the next version of the manuscript according to these suggestions.
Let me start with the title. I don't know why so many linguistic errors (Conclusions, of course), because the manuscript was checked by our university translator before sending it.
autor
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
It is recommended to note that this study can be improved by applying also some other physical approaches such as quantum generators as well.
Reviewer 2 Report
N/A
