New Hybrid Method for Buffer Positioning and Production Control Using DDMRP Logic in Smart Manufacturing

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The evaluated work concerns an important practical issue in production management, in particular material resource planning. The authors proposed their own method based on the DDMRP methodology. Their model comprehensively takes into account the interaction between factors such as demand, buffer status, inventory variability and replenishment methods. To solve the optimisation problem, the authors of the paper propose an original hybrid genetic algorithm. This algorithm has been implemented and verified in a simulation environment. Therefore, the authors' own contribution to the development of the field is evident, and for this reason I recommend the paper for publication in its proposed form.

The weaker aspect of the work is the absence of industrial verification of the proposed method and conclusions based only on simulation studies. Therefore, despite the positive assessment, I suggest that the authors make minor editorial corrections and revise the Conclusions and Abstract. 

Editorial reservations include:
- inconsistent style of referencing literature - in one part of the paper, references are given as item no. [x], while in another part, the authors' names or names and item numbers are given;
- incorrect positioning of equations, which are too far to the left of the text;
- difficulty reading the font used for numbers in the research results charts.

The content of the last sentence in the Abstract is inconsistent with reality. No experimental research was conducted for the three production topologies in the study. The study only involved simulation research, not experimental verification in industrial conditions. 
In Conclusions, the new solution was not evaluated critically enough, in particular, the results obtained were not compared with other methods used. 

Author Response

The modifications made to the article in response to the reviewer's comments are highlighted. The revised article is attached.

We thank the reviewer for his careful evaluation of our manuscript and his constructive feedback. Below, we address each point raised by the reviewer:  

A. Overall Assessment

We appreciate the reviewer's positive evaluation of our contribution to production management, particularly regarding the DDMRP methodology and our hybrid approach combining Mixed-Integer Programming and Genetic Algorithms. We are grateful for the recommendation for publication  

B. Industrial Verification

Comment: The weaker aspect of the work is the absence of industrial verification of the proposed method and conclusions based only on simulation studies.

Response: We acknowledge this limitation in our study and appreciate the reviewer’s observation. Our current work indeed focuses on simulation-based validation, and we agree that industrial verification would strengthen our findings. We have addressed this limitation in several ways:

• We have revised the manuscript to clearly acknowledge the simulation-based nature of our validation approach.

• We have elaborated on the theoretical foundations of our method, emphasizing that the resulting production plan would be difficult to apply if the model assumptions are not compatible with a real-world production environment.

• We have expanded the conclusion section to address this limitation by outlining specific areas where the model could be enhanced (e.g., incorporating machine breakdowns, setup times, and other real-world variables), and by emphasizing the need for future industrial validation.

We believe these revisions provide a more balanced presentation of the current scope of our work while acknowledging the importance of model extensions and future industrial validation.    

C. Editorial Corrections

1. Inconsistent Referencing Style

Comment; Inconsistent style of referencing literature - in one part of the paper, references are given as item no. [x], while in another part, the authors' names or names and item numbers are given.

Response: We thank the reviewer for noting this inconsistency. We have thoroughly revised the manuscript to implement a uniform referencing style that strictly adheres to the JMMP journal guidelines, consistently using the numbered format [x] throughout the text. Additionally, we have enhanced the overall manuscript structure and readability through careful paragraph organization and improved transitions. All these modifications are clearly highlighted in the revised manuscript for easy review.  

2. Equation Positioning

Comment: Incorrect positioning of equations, which are too far to the left of the text.

Response: We have carefully reformatted all equations to ensure proper centering and alignment according to the journal's formatting requirements. This includes standardizing equation numbering, spacing, and indentation throughout the manuscript to maintain consistency and improve readability.

3. Chart Readability

Comment: Difficulty reading the font used for numbers in the research results charts.

Response: We have enhanced the visual presentation of all charts by:

•  Increasing the font size of numerical values for better readability
• Implementing a consistent, clear font style across all figures
• Adjusting contrast and spacing to improve overall clarity
• Adding appropriate gridlines where needed to facilitate data interpretation

D. Abstract Revision

Comment: The content of the last sentence in the Abstract is inconsistent with reality. No experimental research was conducted for the three production topologies in the study. The study only involved simulation research, not experimental verification in industrial conditions.

Response: We agree with this observation and have revised the abstract's final sentence to more accurately represent our work. The modified text now explicitly states that our validation was conducted through simulation studies rather than physical experiments. Specifically, we have clarified that the results demonstrate the theoretical performance improvements achieved through simulation analysis of three representative production configurations. This revision better aligns with the actual scope and methodology of our study while maintaining transparency about the nature of our validation approach.

E. Conclusions

Comment: In Conclusions, the new solution was not evaluated critically enough, in particular, the results obtained were not compared with other methods used.

Response: We acknowledge this concern and have enhanced our conclusions section. We would like to clarify that the unique nature of our contribution—a mathematical model that encapsulates DDMRP principles in multi-stage production systems, combined with a Genetic Algorithm for buffer positioning optimization—presents specific challenges for direct comparison with existing methods. Direct comparisons with alternative approaches (such as Kanban-based MIP) are challenging due to fundamental differences in optimization objectives. For instance, while Kanban systems primarily focus on WIP reduction, DDMRP deliberately maintains strategic buffer levels to ensure system robustness. Similarly, regarding buffer positioning optimization, our approach uniquely conditions GA exploration based on MIP outputs, representing a novel hybrid methodology.

Nevertheless, we have substantially revised the conclusions to include: 1. A more critical evaluation of our approach's strengths and limitations 2. A detailed discussion of the underlying assumptions and their implications for industrial implementation 3. An expanded section on future research directions, including: 

• Potential comparative studies using simulation-based approaches.
• Investigation of machine learning techniques for buffer positioning.
• Extension of the model to handle additional real-world constraints.

These revisions provide a more balanced and comprehensive assessment of our contribution while acknowledging areas for future development.

We appreciate the reviewer's thorough feedback, which has helped us improve the clarity and accuracy of our manuscript.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The present work proposes an innovative approach to integrating demand driven material requirements planning (DDMRP) principles within a production control framework based on a multi-stage production control mechanism that gives a novel hybrid method to optimize both buffer positioning and production scheduling decisions in smart manufacturing environments.
At the core of the proposed approach is a Mixed-Integer Programming model (MIP), which define complex, multi-stage interactions among demand signals, strategic buffer placement, and corresponding replenishment policies as it is prescribed by DDMRP approach. Enhancing the performance of the MIP model, a hybrid genetic algorithm is introduced to explore the solution space more effectively and avoid premature convergence to suboptimal solutions. By integrating these heuristic techniques, the method is enhanced to solving the underlying optimization problem more efficiently than traditional methods. Thus, the proposed approach is aimed to bridgethe gap between theoretical DDMRP models and practical, automated production control, thereby setting the goriund for more resilient and adaptive manufacturing systems in the context of smart manufacturing.

The work is written on a high enough scientific level, and illustrated by a lot of equations and diagrams. However, there are some isuess that must be refined to meet the requirements. There are as follows:

1. Citing style is a mixture and differs from the JMMP template requirements;
2. In some of the figures given there are some abbreviations that are not explained, for example in Fig. 2 - PLC;
3. For most of the formulas given there are no clarifications about the meaning of the participated components, i.e. "formula" (...), where: XX is ,,,; YY is..., etc.
4. There are some typos in the text, for example "4.3. Mutationr probability" (see line 343) that should be corrected;
5. The authors could include some insights in the discussion about what exactly manufacturing environments the proposed approach is suitable to be applied, and whether the approach is applied already somewhere, or it was theoretically developed before its application in real manufacturing environment.

Author Response

The modifications made to the article in response to the reviewer's comments are highlighted. The revised article is attached.

We sincerely thank the reviewer for this thorough evaluation of our manuscript and this constructive feedback regarding both the technical content and presentation quality. Below, we address each point raised:

Overall Assessment

We appreciate the reviewer's recognition of our work's scientific merit and the comprehensive presentation through equations and diagrams. We have carefully addressed the issues raised to improve the manuscript's quality.

1. Citation Style

Comment: Citing style is a mixture and differs from the JMMP template requirements

Response: We thank the reviewer for bringing this inconsistency to our attention. We have thoroughly revised the manuscript to ensure all citations strictly follow the JMMP template requirements, maintaining a consistent format throughout the document.

2. Abbreviations in Figures

Comment: In some of the figures given there are some abbreviations that are not explained, for example in Fig. 2 - PLC

Response: We acknowledge this oversight. We have revised all figures to include clear explanations of all abbreviations used. Specifically:

• In Figure 2, we have added a note explaining that PLC stands for Programmable Logic Controller
• We have conducted a comprehensive review of all figures to ensure that any other abbreviations are properly defined either in the figure caption or upon first use in the text.

3. Formula Components

Comment: For most of the formulas given there are no clarifications about the meaning of the participated components

Response: We agree that clearer explanations of formula components would improve readability. We have revised all mathematical formulations to include comprehensive descriptions of their components. Each formula is now followed by a detailed "where" clause that defines all variables, parameters, and indices used.

4. Typographical Errors

Comment: There are some typos in the text, for example "4.3. Mutationr probability" (see line 343)

Response: We have carefully proofread the entire manuscript and corrected all typographical errors, including the specific instance mentioned ("Mutationr" has been corrected to "Mutation"). We have also conducted a thorough review to identify and correct any other similar issues throughout the text.

5. Application Environment and Implementation Status

Comment: The authors could include some insights in the discussion about what exactly manufacturing environments the proposed approach is suitable to be applied, and whether the approach is applied already somewhere

Response: We appreciate this valuable suggestion and have enhanced the overall content of the manuscript by addressing the following points:

1. Suitable Manufacturing environments

   • In Section 3, a paragraph was added to introduce the characteristics of the production environment to be modeled, along with the main assumptions that may limit the applicability of the model.
   • Although DDMRP is widely applied across several industries, our model focuses on a specific set of production topologies and manufactured products. This clarification has also been added to Section 3.

2. Implementation Status:

   • Clarification that the current work represents a theoretical development with simulation-based validation.
   • We have expanded the conclusion section to address this limitation by outlining specific areas where the model could be enhanced (e.g., incorporating machine breakdowns, setup times, and other real-world variables), and by emphasizing the need for future industrial validation.

We believe these additions significantly strengthen the practical relevance and applicability of our work. Thank you for helping us improve the manuscript's completeness and clarity.

Author Response File: Author Response.pdf