Towards Zero Defect and Zero Waste Manufacturing by Implementing Non-Destructive Inspection Technologies

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents an extensive review of non-destructive inspection technologies (NDITs), with a focus on their application in achieving zero-defect and zero-waste manufacturing. This is a timely and relevant topic in sustainable manufacturing, particularly in industries where resource optimization and defect minimization are critical. The paper highlights advances in acoustic emission, electromagnetic acoustic transducers, infrared thermography, and AI-driven visual inspection. While the manuscript provides a strong foundation, significant revisions are needed to enhance clarity, depth, and scientific rigor. These improvements are essential to ensure the paper effectively serves as a comprehensive resource for researchers and practitioners.

1-      There is a similar study available on SSRN with the same context. What are the differences between these two investigations? Please refer to the following for details.https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4876982.

2-      Revise for better clarity and focus. Clearly state the objective of the review, highlight key NDIT technologies discussed, and summarize the main conclusions or insights derived from the comparative analysis. "

3-      Figure 1: The diagram summarizing the benefits of NDIT is overly general. Add specific metrics or examples (e.g., percentage reduction in material waste) to contextualize the benefits. Also, more figures should be used to illustrate this revised paper better. Table 2 and Table 3: While these provide comparisons of NDIT techniques, include a consistent set of criteria (e.g., accuracy, cost-effectiveness, and industrial scalability) across all technologies for a more meaningful comparison.

4-      Literature Incorporation: The manuscript would benefit greatly from referencing some relevant papers such as "A Survey on Non-Destructive Smart Inspection of Wind Turbine Blades Based on Industry 4.0 Strategy" - This article provides valuable insights into NDIT integration within Industry 4.0 frameworks and can enrich your discussion on smart manufacturing ecosystems. Moreover, "Non-Contact Inspection Methods for Wind Turbine Blade Maintenance: Techno-Economic Review of Techniques for Integration with Industry 4.0" – And "Advancing zero defect manufacturing: A state-of-the-art perspective and future research directions". Also, "On Smart Geometric Non-Destructive Evaluation: Inspection Methods, Overview, and Challenges" - This paper discusses AI-enhanced inspection systems and could significantly strengthen your discussion on AI integration. Incorporating these references will provide a broader context and strengthen the scientific foundation of your review.

5-      Methodology: The methodology for literature synthesis is unclear. Specify the databases searched, the inclusion/exclusion criteria for studies, and whether a systematic review framework (e.g., PRISMA) was used.

-          Include a structured framework for benchmarking the discussed technologies. This could involve metrics like inspection speed, resolution, cost, and compatibility with Industry 4.0 environments.

-          Add a flowchart summarizing the scope and structure of the review, showing how technologies are categorized and analyzed.

-          Acoustic Emission: Expand on how this method compares to traditional techniques like ultrasound in terms of detection depth and resolution for specific defect types.

-          Infrared Thermography: Discuss limitations such as susceptibility to ambient temperature variations and challenges in inspecting reflective surfaces.

-          AI-Driven Inspection: This section provides a deeper discussion on state-of-the-art machine learning algorithms and datasets used in visual inspection systems. It highlights key challenges like overfitting and bias in defect classification.

6-     Results: Discuss the broader industrial implications of adopting NDIT. For example:

-          How does implementing these technologies affect lead times and production costs in real-world settings?

-          What are the environmental impacts (e.g., carbon footprint reduction) of integrating NDIT into production lines?

-          Address the limitations of NDIT technologies more explicitly. For instance:

-          Certain methods are unable to detect subsurface defects in specific materials.

-          Challenges in deploying AI-driven inspection systems in SMEs due to high computational requirements.

 

 

Comments for author File: Comments.pdf

Comments on the Quality of English Language

The English could be improved.

Author Response

Reviewer 1 comments:

The manuscript presents an extensive review of non-destructive inspection technologies (NDITs), with a focus on their application in achieving zero-defect and zero-waste manufacturing. This is a timely and relevant topic in sustainable manufacturing, particularly in industries where resource optimisation and defect minimisation are critical. The paper highlights advances in acoustic emission, electromagnetic acoustic transducers, infrared thermography, and AI-driven visual inspection. While the manuscript provides a strong foundation, significant revisions are needed to enhance clarity, depth, and scientific rigour. These improvements are essential to ensure that the paper effectively serves as a comprehensive resource for researchers and practitioners.

• There is a similar study available on SSRN with the same context. What are the differences between these two investigations? Please refer to the following for details.https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4876982.

 

We appreciate the reviewer bringing this to our attention. To clarify, the study available on SSRN is a preprint version of our work that was previously submitted for publication in the Journal of Sustainable Futures. While the SSRN preprint shares a similar context, it is an earlier iteration of our investigation. In this current manuscript, we have significantly expanded the analysis to include a more comprehensive discussion of the findings. Furthermore, we have addressed limitations and incorporated feedback received from earlier submissions to improve the rigour and relevance of the research.

 

• Revise for better clarity and focus. Clearly state the objective of the review, highlight key NDIT technologies discussed, and summarise the main conclusions or insights derived from the comparative analysis. "

 

Thank you for your observation. The main conclusions derived from the comparative analysis highlight the distinct advantages of NDITs technology over traditional inspection methods.

Per the reviewer's comment, the following text has been included in the section “3.1 Acoustic Emission” on page 6:

“AE’s non-destructive, non-contact nature allows real-time and automated inspections to detect cracks, porosity, microstructural changes, and fibre breakages. Compared to traditional methods like ultrasound or liquid penetrants, AE significantly enhances quality assurance processes thanks to automatisation capabilities to deploy in-process inspections across various industries and materials”.

Per the reviewer's comment, the following text has been included in the section “3.2 Electromagnetic Acoustic Transducer” on page 7:

“EMAT is a non-destructive, coupling-free, non-contact inspection technology ideal for automatic metal structure analysis. It outperforms conventional methods by enabling earlier defect detection, tolerating variable industrial conditions, and reducing costs associated with post-process techniques like X-ray or radiography”.

Per the reviewer's comment, the following text has been included in the section “3.4. Artificial Intelligent Visual Inspection” on page 8:

“Automatic artificial visual inspection enhances in-process quality assurance with superior accuracy and reliability compared to manual methods. It enables 100% inspection, eliminating operator fatigue from repetitive tasks, and significantly improves quality assurance in industrial production environments”.

 

• Figure 1: The diagram summarising the benefits of NDIT is overly general. Add specific metrics or examples (e.g., percentage reduction in material waste) to contextualize the benefits. Also, more figures should be used to illustrate this revised paper better. Table 2 and Table 3: While these provide comparisons of NDIT techniques, include a consistent set of criteria (e.g., accuracy, cost-effectiveness, and industrial scalability) across all technologies for a more meaningful comparison.

We sincerely thank the reviewer for their valuable feedback. In response:

Figure 1: While the diagram summarising the benefits of NDIT has not been revised, we have added a new paragraph in the manuscript directing readers to a review article that defines specific metrics and examples, such as reductions in material waste and process efficiency improvements, to provide additional context to the diagram.

Per the reviewer's comment, the following text has been included in the section “2. Recent Advances in Non-Destructive Inspection Approaches” on page 4:

“Psarommantis et al. (2020) presented a review highlighting the key factors and advantages of adopting new quality improvement strategies to address manufacturing defects, focusing on specific metrics and examples from various industrial scenarios [4]”.

Tables 2, 3, and 4: These tables have been updated to include consistent criteria—accuracy, cost-effectiveness, and industrial scalability—when comparing various technologies with the proposed NDIT techniques. This revision provides a more meaningful and comprehensive comparison.

We believe these changes enhance the manuscript by addressing the reviewer's concerns about specific metrics and the consistency of the comparisons, while maintaining the integrity of the original diagram. Thank you for your insightful suggestions.

 

• Literature Incorporation: The manuscript would benefit greatly from referencing some relevant papers such as "A Survey on Non-Destructive Smart Inspection of Wind Turbine Blades Based on Industry 4.0 Strategy" -This article provides valuable insights into NDIT integration within Industry 4.0 frameworks and can enrich your discussion on smart manufacturing ecosystems. Moreover, "Non-Contact Inspection Methods for Wind Turbine Blade Maintenance: Techno-Economic Review of Techniques for Integration with Industry 4.0" –And "Advancing zero defect manufacturing: A state-of-the-art perspective and future research directions". Also, "On Smart Geometric Non-Destructive Evaluation: Inspection Methods, Overview, and Challenges" -This paper discusses AI-enhanced inspection systems and could significantly strengthen your discussion on AI integration. Incorporating these references will provide a broader context and strengthen the scientific foundation of your review.

To address the importance of NDIT integration and the Industry 4.0 framework in wind energy production the following articles have been added:

“It is on this energy transition framework that our research focuses, which aims to meet the demand for faster, more efficient and accurate quality inspection services in the wind energy industry to achieve resources [15], [77], [84], [85].”.

 

[84]      M. Dimitrova, A. Aminzadeh, M. S. Meiabadi, S. Sattarpanah Karganroudi, H. Taheri, and H. Ibrahim, “A Survey on Non-Destructive Smart Inspection of Wind Turbine Blades Based on Industry 4.0 Strategy,” Applied Mechanics, vol. 3, no. 4, pp. 1299–1326, 2022, doi: 10.3390/applmech3040075.

[85]      A. Aminzadeh et al., “Non-Contact Inspection Methods for Wind Turbine Blade Maintenance: Techno–Economic Review of Techniques for Integration with Industry 4.0,” J Nondestr Eval, vol. 42, no. 2, pp. 1–20, 2023, doi: 10.1007/s10921-023-00967-5.

 

We have incorporated an additional article focusing on AI-enhanced inspection systems to emphasise the importance of NDIT integration within the Industry 4.0 framework for industrial production. These references enrich the discussion on AI integration, providing a broader context and reinforcing the scientific foundation of this review.

“These AI algorithms can extract and predict features by statistical methods, reducing the burning in preprocessing and fine-tuning tasks[73] [74], [75], [76][15], [77], [78], [79]”.

 

[79]      A. Jaber et al., “On Smart Geometric Non-Destructive Evaluation: Inspection Methods, Overview, and Challenges,” Materials, vol. 15, no. 20, 2022, doi: 10.3390/ma15207187.

 

5- Methodology: The methodology for literature synthesis is unclear. Specify the databases searched, the inclusion/exclusion criteria for studies, and whether a systematic review framework (e.g., PRISMA) was used.

• Include a structured framework for benchmarking the discussed technologies. This could involve metrics like inspection speed, resolution, cost, and compatibility with Industry 4.0 environments.
• Add a flowchart summarizing the scope and structure of the review, showing how technologies are categorized and analyzed.
• Acoustic Emission: Expand on how this method compares to traditional techniques like ultrasound in terms of detection depth and resolution for specific defect types.
• Infrared Thermography: Discuss limitations such as susceptibility to ambient temperature variations and challenges in inspecting reflective surfaces.
• AI-Driven Inspection: This section provides a deeper discussion on state-of-the-art machine learning algorithms and datasets used in visual inspection systems. It highlights key challenges like overfitting and bias in defect classification.

 

We appreciate the reviewer’s feedback regarding the methodology for literature synthesis. To clarify, the synthesis involved a structured process, including searches across key databases and applying inclusion/exclusion criteria to ensure relevance and quality. We followed a rigorous approach to curate the most relevant studies for the article.

However, after careful consideration, we decided not to include a detailed description of the synthesis methodology in the manuscript, as this may introduce unnecessary complexity or detract from the core concepts and discussions. Instead, we focused on the work's conceptual and analytical contributions. If needed, further details regarding the methodology can be provided upon request.

 

1.1           State-of-the-art analysis

1.1.1     Methodology

To determine the state-of-the-art non-destructive inspection technologies and services for quality control in smart manufacturing for advancing zero-defect manufacturing, a systematic literature review (SLR) was conducted. The SLR process begins with a planning phase, where the reviewers clearly identify the purpose and intended goals of the literature review. Next is the selection phase, where the literature search and screening processes are carried out to select the core literature. Then comes the extraction phase, where articles are excluded based on specific quality criteria before the remaining articles are studied to extract the useful data and applicable information. Finally, in the execution phase, the data extracted from the literature is synthesised and analysed – before the results can be documented and presented.

Accordingly, the following section presents the procedure for searching and selecting significant literature on NDIT.

1.1.2     Literature Search

The literature search was conducted in November 2023 using the two databases 'Web of Science' and 'Science Direct'. Three different search queries consisting of different combinations of keywords were selected and applied in each database. These search terms are shown in Table 1, and their specific syntax was adapted to the default settings of the databases. In addition, only articles in English were included. To ensure current research results, articles published before 2008 were not included. Thus, the analysis is limited to open access journals. Similarly, the search was limited to matching hits in the title, abstract, or keywords of the literature. Wherever possible, available categories and topics were selected to individualize the results.

 

After identifying potentially relevant literature, the results of this initial search were refined through a multi-stage selection process described as follows, with an output of 1734 potentially relevant articles. Figure 1 visualises the procedure, the utilised criteria, and the remaining articles per step.

 

First, the 1787 papers were preselected by rejecting doublings, where the number of articles was reduced till 1527. The second preselection was carried out removing the research areas that do not consider the industrial sector, reducing the potential articles to 795. On the next selection criteria, the titles were reviewed to eliminate the articles not aligned with ZDZW objectives, and the remaining articles decreased to 192. The fourth selection criteria applied for the literature search, the abstract and conclusion, were reviewed to confirm that the articles were relevant to zero defects and zero waste, as well as the implementation of NDIT in quality control in the manufacturing industry. In the last step, the number of citations was selected, and finally, 52 of the most relevant articles were selected. These articles were reviewed to extract the main topics or ideas required to develop the article, and some new articles were included based on the bibliographic analysis or by reviewer recommendations.

 

6-Results:Discuss the broader industrial implications of adopting NDIT. For example:

• How does implementing these technologies affect lead times and production costs in real-world settings?

We sincerely thank the reviewer for their insightful feedback. To address the broader industrial implications of adopting NDIT and its impact on lead times and production costs, we have elaborated on the following points:

“The adoption of NDIT significantly impacts lead times and production costs by enabling automatic in-process inspections that replace manual methods (Bose and Guha 2021; Psarommatis et al. 2024).  This reduces cycle times, increases first-time-right rates, and minimises defect probabilities, improving production efficiency and sustainability (J. Lario et al., 2024). These advancements optimise manufacturing processes, ensuring cost-effective and reliable industrial operations”.

 

Psarommatis, F., G. May, V. Azamfirei, and F. Konstantinidis. 2024. “Optimizing Efficiency and Zero-Defect Manufacturing with in-Process Inspection: Challenges, Benefits, and Aerospace Application.” Procedia Computer Science 232 (2023): 2857–2866. https://doi.org/10.1016/j.procs.2024.02.102.

 

Bose, Dipankar, and Apratim Guha. 2021. “Economic Production Lot Sizing Under Imperfect Quality, on-Line Inspection, and Inspection Errors: Full vs. Sampling Inspection.” Computers & Industrial Engineering 160 (August 2020): 107565. https://doi.org/10.1016/j.cie.2021.107565.

 

10. Lario, J. Mateos, F. Psarommatis, and Á. Ortiz, “A cost model for the investment feasibility of quality inspection technologies in the Zero Defect Manufacturing era,” Int J Prod Res, 2024, doi: 10.1080/00207543.2024.2383780.

 

• What are the environmental impacts (e.g., carbon footprint reduction) of integrating NDIT into production lines?

We sincerely thank the reviewer for their insightful feedback. To address the environmental impacts of integrating NDIT into production lines, we have highlighted the following:

“Integrating NDIT minimises material waste, energy consumption, and scrap rates by ensuring efficient, defect-free production. These advancements reduce the carbon footprint, promote sustainable manufacturing, and align with zero-defect manufacturing strategies focused on prevention and efficiency (J.Lario et al. 2024). The potential of integrating Non-Destructive Inspection Technologies (NDITs) with advanced Product Lifecycle Management (PLM) systems to provide real-time feedback and predictive analytics. This integration could enhance the decision-making processes across the lifecycle stages, aligning more closely with Zero Defect and Zero Waste (ZDZW) objectives (Psarommatis et al., 2024; Psarommatis and Azamfirei).

 

2024. Lario, J. Mateos, and Á. Ortiz, Non-destructive Inspection Solutions in the EU Industrial Sector for Sustainable Manufacturing. Springer Nature Switzerland, 2024. doi: 10.1007/978-3-031-57996-7_3.

 

Psarommatis, F.; May, G.; Azamfirei, V. Zero Defect Manufacturing in 2024: A Holistic Literature Review for Bridging the Gaps and Forward Outlook. Int J Prod Res 2024, doi:10.1080/00207543.2024.2388217.

Psarommatis, F.; Azamfirei, V. Zero Defect Manufacturing: A Complete Guide for Advanced and Sustainable Quality Management. J Manuf Syst 2024, 77, 764–779, doi:10.1016/j.jmsy.2024.10.022.

 

 Address the limitations of NDIT technologies more explicitly. For instance: Certain methods are unable to detect subsurface defects in specific materials.

 

We sincerely thank the reviewer for their insightful feedback. We have included the following text to comment on the limitations of NDIT technologies:

“Each NDIT technology presents its specific strengths and weaknesses, making them suitable for particular applications and materials. For instance, acoustic emission applied on steel materials provides a broad detectability range, including subsurface defects and information on defect location and shape on ferromagnetic materials. On the other hand, automatic visual inspection technologies are highly promising for parts with complex geometries but may face limitations in detectability and sensitivity. These constraints highlight the need to integrate and combine complementary contactless NDIT methods and sensor technologies to enhance real-time defect detection, monitor process characteristics, and measure process parameters effectively”.

• Challenges in deploying AI-driven inspection systems in SMEs due to high computational requirements.

We sincerely thank the reviewer for their valuable feedback. We have included the following text to comment on the limitations of AI-driven inspection systems:

 

“To address the challenges of deploying AI-driven inspection systems in SMEs face hurdles due to high computational requirements and the labour-intensive process of creating balanced datasets. Techniques like data augmentation, transfer learning, and synthetic training data can help mitigate these limitations, enhancing their feasibility for SMEs”.

 

 

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Is a paper on Towards Zero Defect and Zero Waste Manufacturing by implementing Non-Destructive Inspection Technologies. The paper is well suited to the scope of the journal and the field of interest. The presentation is good, but some improvements are needed.

Comment 1:  The references in the paper need to be reviewed and put in accordance with the recommendations of the Journal Manufacturing and Materials Processing.

Comment 2: The tables in the paper need to be reviewed and put in accordance with the recommendations of the Journal Manufacturing and Materials Processing.

Comment 3: Sections 4 and 5 needs to be revised and improve.

Comment 4: In section 5, the authors present Tables 5 and 6. Are the tables based on some specifications or literature? If so, which ones?

Comment 5: In line 449, CO₂ must write in the correct form.

Comment 6: In general, the manuscript is a little vague, because the passage between themes is not done in the best way. The transition of ideas should be improved, especially in sections 4 and 5.

Author Response

Reviewer 2 comments:

 

Is a paper on Towards Zero Defect and Zero Waste Manufacturing by implementing Non-Destructive Inspection Technologies. The paper is well suited to the scope of the journal and the field of interest. The presentation is good, but some improvements are needed.

Comment 1:  The references in the paper need to be reviewed and put in accordance with the recommendations of the Journal Manufacturing and Materials Processing.

We sincerely thank the reviewer for their valuable feedback. The references in the manuscript have been thoroughly reviewed and updated to align with the Multidisciplinary Digital Publishing Institute (MDPI) citation style, as recommended by the Journal of Manufacturing and Materials Processing. We appreciate the reviewer’s attention to detail and commitment to maintaining the journal's standards.

 

Comment 2: The tables in the paper need to be reviewed and put in accordance with the recommendations of the Journal Manufacturing and Materials Processing.

We sincerely thank the reviewer for their valuable feedback. The tables in the manuscript have been thoroughly reviewed and reformatted to align with the MDPI_4-2_table style, as recommended by the Journal of Manufacturing and Materials Processing.

Comment 3: Sections 4 and 5 needs to be revised and improve.

We sincerely thank the reviewer for their valuable feedback. In response, Sections 4 and 5 have been merged to enhance readability and ensure a smoother transition of ideas. This revision aims to present the content more cohesively, improving the overall flow and clarity of the manuscript. We appreciate the reviewer’s input in helping us refine the structure of the paper.

Comment 4: In section 5, the authors present Tables 5 and 6. Are the tables based on some specifications or literature? If so, which ones?

We sincerely thank the reviewer for their insightful comment. Tables 5 and 6 in Section 5 are not based on specific literature or external specifications. Instead, they are derived from the authors' professional industry experience, providing a practical perspective informed by real-world applications and industry knowledge. We appreciate the opportunity to clarify this point.

Comment 5: In line 449, CO₂ must write in the correct form.

We sincerely thank the reviewer for their observation. The issue in line 449 has been addressed, and "CO₂" has been corrected to the appropriate form.

Comment 6: In general, the manuscript is a little vague, because the passage between themes is not done in the best way. The transition of ideas should be improved, especially in sections 4 and 5.

We sincerely thank the reviewer for their valuable feedback. In response, Sections 4 and 5 have been merged to enhance readability and ensure a smoother transition of ideas. This revision aims to present the content more cohesively, improving the overall flow and clarity of the manuscript. We appreciate the reviewer’s input in helping us refine the structure of the paper.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This work aligns very well with the development goal of many industries. Cost reduction and efficiency improvement are always the hot topics. NDT and NDI are usually time and labor consuming, and there is already a growing trend of difficulty in hiring. Therefore, innovative techniques that needs less operator involvement are highly demanded.  Combining traditional NDT techniques with AI is a good way. Another possibility is using structural health monitoring methods/techniques to optimize the inspection and maintenance schedule. New optical strain sensors that can enable long-term structural health monitoring and collect real-life load data would be helpful for achieve the zero-defect and zero-waste goal. Here is an example of the sensor that is under developing: https://www.nature.com/articles/s41598-022-15332-1

 

Author Response

Reviewer 3 comments:

 

This work aligns very well with the development goal of many industries. Cost reduction and efficiency improvement are always the hot topics. NDT and NDI are usually time and labor consuming, and there is already a growing trend of difficulty in hiring. Therefore, innovative techniques that needs less operator involvement are highly demanded.  Combining traditional NDT techniques with AI is a good way. Another possibility is using structural health monitoring methods/techniques to optimize the inspection and maintenance schedule. New optical strain sensors that can enable long-term structural health monitoring and collect real-life load data would be helpful for achieve the zero-defect and zero-waste goal. Here is an example of the sensor that is under developing: https://www.nature.com/articles/s41598-022-15332-1

We sincerely thank the reviewers for their insightful comments and highlighting the importance of innovative techniques requiring less operator involvement. To address this valuable feedback, we have included the suggested reference in Chapter 3.4, Artificial Intelligent Visual Inspection, to emphasise the potential of optical strain sensors for enabling long-term structural health monitoring and collecting real-life load data. This addition underscores the role of advanced sensors in achieving zero-defect and zero-waste goals through optimised inspection and maintenance schedules. We greatly appreciate the reviewer’s contribution to enriching our work.

 

[82]      W. Meng, A. Pal, S. M. Bachilo, R. B. Weisman, and S. Nagarajaiah, “Next-generation 2D optical strain mapping with strain-sensing smart skin compared to digital image correlation,” Sci Rep, vol. 12, no. 1, pp. 1–12, 2022, doi: 10.1038/s41598-022-15332-1.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript is suitable for publication in its current format.

Author Response

Thank you for your feedback. We have updated the references in the manuscript in accordance with Reviewer 2's recommendation to ensure they align with the guidelines of the Journal of Manufacturing and Materials Processing. Specifically, we have included the ISBN for reference [86]. No further changes have been made, as the comments and suggestions for authors stated, "This manuscript is suitable for publication in its current format."

Reviewer 2 Report

Comments and Suggestions for Authors

After performing the review of the paper, Towards Zero Defect and Zero Waste Manufacturing by Implementing Non-Destructive Inspection Technologies - V2. I consider that the paper can be accepted after minor revisions. 

Comment 1: Some citations in the paper need to be reviewed and put in accordance with the recommendations of the Journal Manufacturing and Materials Processing.

Author Response

Thank you for pointing this out. We have reviewed and updated the references in the manuscript to ensure they are in accordance with the recommendations of the Journal of Manufacturing and Materials Processing. Specifically, we have included the ISBN in reference [86] for the updated references where applicable. Additionally, the rest of the references have been revised and formatted following the Multidisciplinary Digital Publishing Institute (MDPI) citation style, utilizing Mendeley software to ensure consistency and accuracy.