Leveraging Industry 4.0 for Sustainable Manufacturing: A Quantitative Analysis Using FI-RST
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe study employs Fuzzy Integration-Rough Set Theory (FI-RST) to quantitatively analyze the impacts of key technologies such as Manufacturing Execution Systems (MES), the Industrial Internet of Things (IIoT), and Additive Manufacturing (AM) on sustainability performance. Data was gathered through a structured survey targeting senior managers and technical experts in manufacturing firms. The survey focused on economic, environmental, and social sustainability aspects.
Research questions addressed:
Which Industry 4.0 technologies exert the most significant influence on the sustainable development performance of manufacturing enterprises?
How can these technologies be effectively integrated to maximize their collective impact on sustainability, spanning economic, environmental, and social dimensions?
What strategies should manufacturing enterprises adopt to successfully implement these technologies in pursuit of sustainable development?
Suggestion to improve the relevance of the document:
1. Increase the sample size in future studies can enhance the accuracy of findings.
2. Implement periodic data gathering over time can provide insights into the long-term impacts of Industry 4.0 technologies on sustainability.
3. Describe the technologies to incorporate to improve worker safety and training.
4. Reduce the gaps in the literature review regarding the application of Industry 4.0 technologies in sustainable development, ensuring a more comprehensive understanding of their potential benefits.
5. Explore studies that analyze the combined effects of multiple Industry 4.0 technologies rather than focusing on them individually.
6. Emphasize the need for more empirical research that quantifies the impact of Industry 4.0 technologies on sustainable development performance, particularly in emerging economies.
7. Investigate literature that specifically addresses the environmental benefits of technologies, include literature that examines the social implications of adopting Industry 4.0 technologies, such as employee well-being and training outcomes, to provide a holistic view of sustainability.
8. Evaluate the inclusion of mathematical backgraound to the document, in specific the formulas related with Fuzzy Integration-Rough Set Theory.
Author Response
Dear Reviewer,
We sincerely appreciate your thorough review and the insightful comments that have been provided. We believe these suggestions have greatly contributed to improving the quality and clarity of our manuscript. Below, we provide detailed responses to each of your comments, as well as the revisions we have made to address them.
Comment 1: Increase the sample size in future studies can enhance the accuracy of findings.
Response:
We agree that increasing the sample size would improve the robustness and accuracy of our findings. In this current study, we were limited by the availability of senior managers and technical experts. However, we have acknowledged this limitation in the revised manuscript and proposed increasing the sample size in future research to further validate our results. Specifically, we have added a section in the "Limitations and Future Research" section to address this.
Comment 2: Implement periodic data gathering over time can provide insights into the long-term impacts of Industry 4.0 technologies on sustainability.
Response:
Thank you for this valuable suggestion. We have revised the "Methodology" section to recommend the importance of longitudinal studies. Additionally, in the conclusion, we highlight that periodic data collection would offer deeper insights into the longterm impacts of Industry 4.0 technologies on economic, environmental, and social sustainability performance.
Comment 3: Describe the technologies to incorporate to improve worker safety and training.
Response:
We have expanded the "Discussion" section to include a detailed description of how Industry 4.0 technologies, such as the Industrial Internet of Things (IIoT) and Additive Manufacturing (AM), can contribute to enhancing worker safety and training. This includes references to existing studies that show how these technologies can be applied to monitor realtime data, predict hazards, and improve training through simulations and virtual environments.
Comment 4: Reduce the gaps in the literature review regarding the application of Industry 4.0 technologies in sustainable development, ensuring a more comprehensive understanding of their potential benefits.
Response:
We have thoroughly revised the "Literature Review" section to provide a more comprehensive analysis of the application of Industry 4.0 technologies in sustainable development. We have integrated additional references that explore the economic, environmental, and social benefits of these technologies, ensuring a more holistic understanding of their potential.
Comment 5: Explore studies that analyze the combined effects of multiple Industry 4.0 technologies rather than focusing on them individually.
Response:
In response to this suggestion, we have expanded the "Results" and "Discussion" sections to focus on the combined effects of MES, IIoT, and AM on sustainability performance. We now explore how the integration of these technologies creates synergies that amplify their impact on sustainability across economic, environmental, and social dimensions.
Comment 6: Emphasize the need for more empirical research that quantifies the impact of Industry 4.0 technologies on sustainable development performance, particularly in emerging economies.
Response:
We fully agree with this comment and have emphasized the need for more empirical research in emerging economies in both the "Conclusion" and "Future Research" sections. We have also included relevant studies that highlight the unique challenges and opportunities faced by these regions in adopting Industry 4.0 technologies.
Comment 7: Investigate literature that specifically addresses the environmental benefits of technologies, include literature that examines the social implications of adopting Industry 4.0 technologies, such as employee wellbeing and training outcomes, to provide a holistic view of sustainability.
Response:
We have significantly expanded the literature cited in the revised "Literature Review" and "Discussion" sections to include studies on both the environmental and social benefits of Industry 4.0 technologies. This includes research on their contribution to reducing energy consumption, improving resource efficiency, as well as their implications for employee wellbeing, safety, and training.
Comment 8: Evaluate the inclusion of mathematical background to the document, in specific the formulas related with Fuzzy Integration Rough Set Theory.
Response:
We appreciate your suggestion and have added a section in the "Methodology" that elaborates on the mathematical foundation of the Fuzzy Integration Rough Set Theory (FIRST). This includes key formulas used in our analysis to ensure clarity and reproducibility for readers with technical expertise in this area.
We hope the revisions we have made successfully address your comments and improve the overall quality of the manuscript. Thank you once again for your valuable feedback, and we look forward to your further evaluation.
Sincerely,
Reviewer 2 Report
Comments and Suggestions for AuthorsThe implementation of Industry 4.0 tools & technologies is currently subjected by many authors, so paper subject is of actuality. Despite this, the paper, in the present form, could hardly be considered as research paper. More specific, the paper only presents some results, without any specification regarding the manner on which they were obtained. The entire paper is a nice story - not a single relation, not a single diagram (except the one from fig. 1, which is trivial, and the ones presenting the results). The invoked questionnaire is not at all introduced. The addressed companies are also not introduced, nothing relevant about them - what are they actually manufacturing, which is their size, how many employies do they have? There are not included any concrete numbers, there is not included any indication about the results in absolute representation. How were calculted, for example, the results from Table 1, how was they assessed the environmental impact and the sustainability score? The FI-RST model application is invoked but there is nothing concrete about the specific conditions. The Introduction is very formal and general, the Literature review is very thin. The conclusion is also too general.
Comments on the Quality of English LanguageThe expression style is sometimes complicated / inappropriate - a single, but relevant example is the phrase from rows 113-117.
What does it mean multi-upran (row 118)?
Author Response
Dear Reviewer,
We sincerely appreciate your detailed and constructive feedback on our manuscript. Your insights have greatly contributed to improving the quality of our work. Below, we provide a point-by-point response to each of your comments and outline the revisions made accordingly.
Comment 1: General relevance and presentation of results
The implementation of Industry 4.0 tools & technologies is currently subjected by many authors, so the paper subject is of actuality. Despite this, the paper, in the present form, could hardly be considered as research paper. More specific, the paper only presents some results, without any specification regarding the manner on which they were obtained.
Response:
We acknowledge this critical observation. To address this, we have significantly expanded the "Methodology" section, explicitly detailing the research design, data collection processes, and the analytical methods applied. We have introduced comprehensive descriptions of the data sources, including the exact nature of the questionnaire used and the statistical methods employed to process the data. Additionally, the FI-RST (Fuzzy Integration-Rough Set Theory) model application has been elaborated with explicit conditions and mathematical formulations, providing a robust framework for understanding how results were derived.
Comment 2: Lack of diagrams and insufficient explanation of results
The entire paper is a nice story - not a single relation, not a single diagram (except the one from fig. 1, which is trivial, and the ones presenting the results).
Response:
In response, we have added several new figures and tables throughout the manuscript, including diagrams that clarify the relationships between the variables, as well as flowcharts that depict the analytical processes used in the FI-RST model. These additions serve to visually represent the methodology and key relationships. The results have been further contextualized by providing not only relative but also absolute figures, accompanied by detailed explanations of their significance.
Comment 3: Introduction of the questionnaire and companies involved
The invoked questionnaire is not at all introduced. The addressed companies are also not introduced, nothing relevant about them - what are they actually manufacturing, which is their size, how many employees do they have?
Response:
We have now included a detailed description of the questionnaire design, including the types of questions posed and the rationale behind each section. Additionally, the profile of the companies participating in the study is now fully elaborated, including information on their industries, product types, company sizes, employee numbers, and their roles within the Industry 4.0 adoption spectrum. This information is presented in a new subsection of the "Methodology" section.
Comment 4: Lack of concrete numbers and details in results
There are not included any concrete numbers, there is not included any indication about the results in absolute representation. How were calculated, for example, the results from Table 1, how was they assessed the environmental impact and the sustainability score?
Response:
We have revised the "Results" section to incorporate concrete numerical data, including absolute values. We have also provided a step-by-step explanation of how the results in Table 1 were derived, including the formulas used to assess environmental impact and sustainability scores. The calculations for each key variable are explained in detail, offering transparency and replicability.
Comment 5: Insufficient description of the FI-RST model
The FI-RST model application is invoked but there is nothing concrete about the specific conditions.
Response:
We have now included a dedicated subsection within the "Methodology" that outlines the specific conditions under which the FI-RST model was applied. This includes a clear explanation of the parameters used, the boundary conditions considered, and the mathematical formulations involved. Additionally, the integration of Fuzzy Set Theory and Rough Set Theory has been elaborated with supporting mathematical equations and justifications for their relevance in evaluating Industry 4.0 technologies.
Comment 6: Generality of Introduction and Literature Review
The Introduction is very formal and general, the Literature review is very thin.
Response:
The "Introduction" has been revised to provide more specific context, particularly regarding the challenges faced by manufacturing enterprises in adopting Industry 4.0 technologies. The "Literature Review" has been significantly expanded to address gaps in the existing research on the intersection of Industry 4.0 and sustainable development. We have incorporated recent studies that focus on the combined effects of multiple Industry 4.0 technologies, as well as empirical research on their impact in emerging economies. This expansion ensures a more comprehensive foundation for our study.
Comment 7: Complexity of language
The expression style is sometimes complicated/inappropriate - a single, but relevant example is the phrase from rows 113-117. What does it mean multi-upran (row 118)?
Response:
We have revised the language throughout the article to ensure clarity and conciseness. The phrases in lines 113-117 have been restructured to improve readability and accuracy. In addition, ‘multi-upran’ in line 118 was a spelling error that has now been corrected. We have scrutinised the entire text and eliminated any other complex or unclear language.
Reviewer Suggestions for Improvement:
- Increase the sample size in future studies: We fully agree and have noted this in the "Limitations and Future Research" section.
- Implement periodic data gathering over time: This suggestion is acknowledged and integrated into the future research section.
- Describe the technologies to incorporate worker safety and training: We have added a discussion of these technologies in the "Discussion" section.
- Reduce literature review gaps: The literature review has been expanded accordingly, as explained above.
- Explore studies on the combined effects of technologies: We have included more studies focusing on the synergies between multiple Industry 4.0 technologies.
- Quantify the impact of Industry 4.0 technologies on sustainability: More emphasis is placed on empirical research, as recommended.
- Include studies on the environmental and social benefits of Industry 4.0: We have incorporated this literature to provide a more holistic view of sustainability.
- Evaluate inclusion of mathematical background on FI-RST model: Mathematical formulas related to the FI-RST model have been added.
We trust that these revisions address your concerns. We greatly appreciate your time and valuable feedback, which have significantly enhanced the quality of our work.
Sincerely,
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThank you for allowing me to participate in this review, I consider that the authors applied the previously proposed recommendations.
For that reason, my recommendation is accept the document for publication.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe paper quality has been improved by considerably reconsidering its content and by including a significant amount of additional information.
