Challenges and Opportunities in the Implementation of AI in Manufacturing: A Bibliometric Analysis

Round 1

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

This is a good, solid study, although it does have a few shortcomings that severely undermine the quality of the article.

1.      The first of these shortcomings has to do with the time interval chosen. The choice not to consider articles from before 2019, because they are scarce, is not methodologically acceptable. Similarly, the choice to include articles from 2024 published up until August has little methodological support. If the study had been completed in May, for example, would the articles published up to May be considered in the research? If it had been completed in November, would it have included articles published up to November? It seems like a criterion established according to the investigators' availability/agenda.

In studies of this nature, it is important to establish comparable units of analysis, and “articles published up to August” does not establish a unit of analysis that allows comparisons to be made.

2.      The study also inadequately describes the keywords used to select and retrieve the articles for the study.

3.      In figure 3, the top line, in gray, does not make sense in the way it is presented.

4.      There is a case for revising the article, which sometimes uses inappropriate terms, such as «indices».

5.      In the more analytical part, the study establishes comparative patterns that it doesn't justify, for example, it states “This decline is common in rapidly expanding fields” but doesn't provide any references to support this statement.

6.      The results of the G-index are the same as the number of publications, i.e. the different journals behave in the same way as far as the G-index is concerned, depending only on whether many or few articles have been published on the subject in the different journals. In this sense, the G-index does not allow the different journals to be ranked, i.e. the different journals do not differ in terms of G-index, but only in terms of the number of articles published.

7.      The G-index, the M-index and Bradford's Law should be described in a more rigorous way. This aspect is less necessary for the h-index because it is more commonly used.

8.      Figure 6, while an interesting effort, is not supported by the study's evidence and thus looks like a speculative analysis. The same goes for figure 8, figure 10 and figure 13.

9.      The article seems to be excessively long, which could jeopardize its impact.

10.  Lastly, a review of the conclusions is warranted. The study's contributions appear to be underdeveloped in the conclusions. As the study is relatively in-depth and solid, the conclusions should be more ambitious.

Comments on the Quality of English Language

A minor revision is needed~.

Author Response

Reviewer 1

This is a good, solid study, although it does have a few shortcomings that severely undermine the quality of the article.

1. The first of these shortcomings has to do with the time interval chosen. The choice not to consider articles from before 2019, because they are scarce, is not methodologically acceptable. Similarly, the choice to include articles from 2024 published up until August has little methodological support. If the study had been completed in May, for example, would the articles published up to May be considered in the research? If it had been completed in November, would it have included articles published up to November? It seems like a criterion established according to the investigators' availability/agenda.

In studies of this nature, it is important to establish comparable units of analysis, and “articles published up to August” does not establish a unit of analysis that allows comparisons to be made.

RESPONSE: We appreciate your observation regarding the selection of the time interval, and we agree that the choice of period could have been addressed in a more methodologically rigorous manner. We recognize that the decision not to consider articles prior to 2019 due to their scarcity, as well as the inclusion of articles published up to August 2024, may introduce certain limitations in terms of data comparability. While this choice was motivated by the goal of capturing the most recent trends in AI research in manufacturing, we understand that establishing more consistent units of analysis, such as using full or standardized time periods, is essential for improving the methodological robustness of future studies.

In this regard, we will take your recommendation into account for future research, ensuring that time intervals are defined with greater rigor and comparability. Additionally, this point will be explicitly included in the study’s Limitations section, acknowledging the potential impact of this decision on the results obtained and the conclusions drawn (lines 1104-1111).

 

2. The study also inadequately describes the keywords used to select and retrieve the articles for the study.

RESPONSE: This comment was addressed in lines 216-241.

3. In figure 3, the top line, in gray, does not make sense in the way it is presented.

RESPONSE: Figure 3 was rephrased to make the gray line make sense.

4. There is a case for revising the article, which sometimes uses inappropriate terms, such as «indices».

RESPONSE: Changes made to lines 258, 263, and 396.

5. In the more analytical part, the study establishes comparative patterns that it doesn't justify, for example, it states “This decline is common in rapidly expanding fields” but doesn't provide any references to support this statement.

RESPONSE: This comment was addressed on lines 343-348.

6. The results of the G-index are the same as the number of publications, i.e. the different journals behave in the same way as far as the G-index is concerned, depending only on whether many or few articles have been published on the subject in the different journals. In this sense, the G-index does not allow the different journals to be ranked, i.e. the different journals do not differ in terms of G-index, but only in terms of the number of articles published.

RESPONSE: This comment was addressed on lines 405-423.

7. The G-index, the M-index and Bradford's Law should be described in a more rigorous way. This aspect is less necessary for the h-index because it is more commonly used.

RESPONSE: These comments were addressed on lines 416-423, and on lines 446-461.

8. Figure 6, while an interesting effort, is not supported by the study's evidence and thus looks like a speculative analysis. The same goes for figure 8, figure 10 and figure 13.

RESPONSE: All Figures (6, 8, 10, and 13) were supported by the evidence from the study.

9. The article seems to be excessively long, which could jeopardize its impact.

RESPONSE: We appreciate your observation regarding the length of the article. We acknowledge that the study may be longer than usual; however, given that it is a bibliometric analysis, we believe that the depth and level of detail are essential to provide a comprehensive and accurate view of the research on AI in manufacturing. The nature of bibliometric studies involves analyzing multiple metrics, authors, institutions, and topics, which inevitably requires a detailed treatment of the information.

We believe that reducing the length could compromise the integrity of the analysis, as each section of the study provides key information to understand the trends and current state of research. Our intention is for this article to offer a comprehensive perspective that adds value to both the academic community and industry professionals, and for that reason, it is necessary to include all the aspects addressed.

10. Lastly, a review of the conclusions is warranted. The study's contributions appear to be underdeveloped in the conclusions. As the study is relatively in-depth and solid, the conclusions should be more ambitious.

RESPONSE: The Conclusions Section was reformulated in the light of the comments.

Author Response File: Author Response.docx

Reviewer 2 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

The article is devoted to the bibliometric analysis of articles published in Scopus on the topic of "AI in the manufacturing process". In the article, I made a very detailed analysis of the metrics: from the most cited topics to the most popular authors on the topic. The article gives a generalized understanding of the current state of the field of AI research in manufacturing. I only had one question regarding additive manufacturing. In the most cited articles, a topic related to additive manufacturing is highlighted, however, usually this topic is not very closely related to manufacturing processes, but is quite often related to the topic of 3D printing and its application. Perhaps this should be somehow highlighted in the article or explained.

In the conclusions section, you can add numerical results of the study (average cited by topic, etc.) to reflect the current trends numerically.

Despite this, I believe that the article is ready for publication

 

Author Response

Reviewer 2

The article is devoted to the bibliometric analysis of articles published in Scopus on the topic of "AI in the manufacturing process". In the article, I made a very detailed analysis of the metrics: from the most cited topics to the most popular authors on the topic. The article gives a generalized understanding of the current state of the field of AI research in manufacturing. I only had one question regarding additive manufacturing. In the most cited articles, a topic related to additive manufacturing is highlighted, however, usually this topic is not very closely related to manufacturing processes, but is quite often related to the topic of 3D printing and its application. Perhaps this should be somehow highlighted in the article or explained.

RESPONSE: This comment is addressed on lines 1045-1053.

 

In the conclusions section, you can add numerical results of the study (average cited by topic, etc.) to reflect the current trends numerically.

RESPONSE: This comment was addressed in the reformulated Conclusions section.

Author Response File: Author Response.docx

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

The trend of AI research in the manufacturing sector is something that must be kept in mind. It is a very powerful aid with guidance and structure to support decision-making and behavior forecasts. This study is of interest to the sector, which reflects technological maturity in various industrial processes, such as additive manufacturing, with a significant contribution.

because the study focused exclusively on implementing AI in manufacturing in the context of Industry 4.0, this leaves aside other industries or sectors with different economic and technological conditions

Author Response

Reviewer 3

The trend of AI research in the manufacturing sector is something that must be kept in mind. It is a very powerful aid with guidance and structure to support decision-making and behavior forecasts. This study is of interest to the sector, which reflects technological maturity in various industrial processes, such as additive manufacturing, with a significant contribution.

because the study focused exclusively on implementing AI in manufacturing in the context of Industry 4.0, this leaves aside other industries or sectors with different economic and technological conditions

RESPONSE: We appreciate your observation regarding the scope of the study. We recognize that focusing on the implementation of AI in manufacturing within the context of Industry 4.0 has left aside other sectors with different economic and technological conditions. This focus was intentional, as our primary goal was to analyze how AI is transforming advanced manufacturing processes, a key area within Industry 4.0.

However, we agree that it would be highly valuable to explore how AI could be applied in other sectors that face different technological and economic challenges. This is an aspect we plan to address in future research, expanding the analysis to industries with varying levels of technological maturity and economic conditions to offer a broader perspective on AI adoption.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

The authors have done a good job in reviewing the article.

It can go on to be edited.

Congratulations to the authors.

Comments on the Quality of English Language

Good enough for the editing process.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper is devoted to a review of existing articles about industry 4.0. Works from 2018 to August 2023 were considered. A very voluminous analysis has been done, but I have several questions for the authors.

1) Section 3.2 Data sources, I would suggest putting everything in a table, or making it a diagram, but not in the text, otherwise it turns out very blurry.

2) Section 3.4. Make a diagram of which tools were used for which question. You write that for better understanding the results are presented in the figure, but the figure is not presented.

3) in Table 2, for convenience, it is better to place the lines (article, conference paper, book chapter, review, book) after the Documents line, and perhaps mark it in other italics, to highlight that the "documents" include all the listed lines.

4) update data for 2023 if it has already appeared. Since the article will be published in the summer of 2024, it would be nice to have data for at least the whole of 2023

5) Why was the criterion of minimum number of citations = 0 chosen when analyzing the most influential sources in the 4.0 field? It seems logical to choose a non-zero value.

6) Table 3 lists the ten most interesting publications. Perhaps you mean "sources".

7) in Fig. 5. the authors Müller et al are mentioned three times. Are these two different articles written by the same author or are they namesakes?

8) table 6. Conclusion to the first question RK1. "However, there was a decline in document production in 2023." Since the article considers work only until August 2023, it cannot be stated that in 2023 the number of documents began to decline.

9) The authors examine the global distribution of documents and highlight the most cited countries. It makes sense to note countries where this topic is not studied at all.

I believe that this article will be an excellent contribution to MDPI after major revision

Reviewer 2 Report

Comments and Suggestions for Authors

A large body of research has been carried out on Industry 4.0. The idea of a new industrial revolution should be seen in the context of explaining industrial revolutions. There is a 4th because there was a 1st, 2nd, and 3rd before that. A good explanation of the dynamics of industrial revolutions is the work of Carlota Perez, Chris Freeman, Giovanni Dosi, Teece, etc. For them, industrial revolutions correspond to changes in techno-economic paradigms, characterized by penetrations in all sectors of activity, and are therefore a profound revolution.

Implementing production and other systems based on a set of currently available technologies - Technologies 4.0 - is a paradigm shift and assessing how its application in the different sectors is progressing, apparently, the research subject makes sense.

Nothing in the article makes sense from here on in.

1.      Are the authors convinced that producing a research study that states "the application of 4.0 technologies in tourism is something new" is significantly different from producing a research study that states "the application of 4.0 technologies in the tourism sector is something new"?

For the authors it is, because the former is not considered in the study, and the latter is.

The sample of articles cannot be considered consistent.

2.      The relationship between Industry 4.0 and sectoral aspects is not discussed in the literature review, so it is not clear what the study was supposed to clarify.

3.      Table 1 makes no sense, considering that Disaster Risk Management is similar, for the purposes of the study, to the Internet of Things (IoT) or Tourism and hospitality, which has no rational support.

4.      It's not clear why the study includes the years 2018, 2019, 2020, 2021, 2022, and part of 2023 (??). The inclusion of only part of the year 2023 is incomprehensible. Studying five recent years (2018-2022 or 2019-2019) could make sense, but the criteria applied, and their significance should be explained.

5.      The assumed objectives of the study are

O1. Analyze the evolution of scientific research on Industry 4.0 and related industrial sectors over the years in terms of number of publications and relevant topics.

O2. Identify the most relevant and influential sources in the field of Industry 4.0 and related industrial sectors.

O3. Determine the research trend in Industry 4.0 and related industrial sectors based on the most cited articles.

O4. Identify current trends and prominent areas of study within Industry 4.0, as well as understand how these trends relate to and affect different industry sectors.

O5. Examine how manuscript production is distributed globally and understand what impact this distribution has on mentions and references to Industry 4.0 and other related industry sectors.

The study does not make a single contribution to aligning its findings/ conclusions with these objectives.

6.      The closest contribution to achieving these objectives is when the authors write.

The study demonstrates how the technological revolution significantly impacts operational efficiency and adaptability in diverse industrial sectors.

Regrettably, nothing in the study supports this claim.

 

The idea of the study is very good, and it makes sense to do this research. But unfortunately, that alone is not enough.

 

Authors are invited to extensively review the study and attempt a new submission.

Comments on the Quality of English Language

No coments