A Carbon Efficiency Traceability Monitoring Model for Discrete Manufacturing Workshops with Event Concurrency

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper proposes a carbon efficiency traceability monitoring model for discrete manufacturing industries. The research topic is generally interesting and has strong application focus. Below, I offer suggestions for the authors to consider.

1) In the abstract section, there is no need to define abbreviations used only once, including O&M, PDEVS, and DES. If an abbreviation is defined in the abstract, it must be redefined in other sections of the manuscript when it is used for the first time. Additionally, abbreviations cannot be used as keywords.

2) I suggest that the authors combine the highlights in Section 2.3 with the contributions in Section 1, then remove Section 2.3 from the current manuscript. Additionally, they should simplify Section 2 by avoiding detailed interpretations of reference studies.

3) Figs. 1, 2, and 4 are difficult to read because it is too complex. Please simplify it and increase the font size.

4) Section 6 should provide more insights from the proposed monitoring model. Furthermore, I suggest that the authors verify the model's effectiveness by comparing it with more state-of-the-art methods, such as statistical analysis and machine learning approaches.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1. Clearly highlight the novelty of the proposed framework and explicitly differentiate it from existing PDEVS- and digital twin-based carbon monitoring approaches.
2. The validation is limited to a single case study. Discuss the applicability and generalizability of the proposed framework to other discrete manufacturing systems.
3. Strengthen the validation by providing quantitative comparisons with existing methods or benchmark approaches.
4. Discuss the computational efficiency and scalability of the proposed framework, particularly for large-scale manufacturing systems with numerous concurrent events.
5. Explicitly summarize the key assumptions of the proposed model (e.g., deterministic event priorities, constant emission factors, and predefined operating rules) and discuss their potential influence on the results.
6. The methodology contains repetitive descriptions, particularly in the PDEVS framework and multi-resolution modeling. Condensing these sections would improve readability.
7. Simplify Figures 1 and 2 by reducing textual content and improving font readability. Clearly distinguish the novel components of the proposed framework from the standard PDEVS architecture.

Comments on the Quality of English Language

The manuscript would benefit from careful English proofreading to improve sentence structure, reduce repetition, and enhance overall readability

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

the manuscript presents a valuable and timly study on carbon efficiency traceability monitoring for discrete manufacturing workshops under concurrent event conditons. The topic is highly relevant to low-carbon manufacturing, intelligent workshop operation, and sustainable production managemnt. The proposed framework is logically structured, and the integration of multi-resolution carbon efficiency information transfer with PDEVS-based event-concurrency handling is a strong point of the work. The paper also provides clear modelling steps, a useful case study, and practical implications for identifyng the causes of carbon-efficiency fluctuations. Overall, the manuscript is well organized and has good potential for publication after minor clarification and polishing.

1. Could the authors further clarify how the threshold for identifying a “significant” carbon efficiency fluctuation is determined in practical workshop monitorng?
2. The proposed priority deduction strategy for concurrent events is interesting, but could the authors briefly explain whether the priority rules are generalizable to other types of manufacturing workshps?
3. Since carbon emission factors may vary by region, energy source, and supplier, could the authors add a short discussion on the influence of emission-factor uncertainty on the model results?
4. Could the authors provde more details about the data sources used in the case study, especially the origin of equipment power, material emission factors, cutting fluid data, and maintenance-event data?
5. It would be useful if the authors could briefly compare the computational complexity or implementation difficulty of the proposed model with a traditional DES-based monitoring model?
6. Some figures contain rich information but are slightly dense. Could the authors improve figure readability by enlarging key labels and making the symbol explanations more consistent across the manuscript?

In general, the manuscript is technically sound, clearly motivated, and relevant to the scope of the journal. I recommend minor revision before acceptance.

Comments on the Quality of English Language

Minor

Author Response

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Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

Comments after reviewing the manuscript titled “A Carbon Efficiency Traceability Monitoring Model for Discrete Manufacturing Workshops with Event Concurrency”

This topic proposes a deductive monitoring model to analyze carbon efficiency changes under event concurrency. The findings in the current work are important. However, I suggest a major revision to improve the manuscript.

Comments:

Abstract

• The abstract will be strengthened if you add specific quantitative results such as the number of runs and percentage improvement in traceability speed.

Introduction

• In the second paragraph, the manuscript introduce carbon efficiency as the effective output created per unit of carbon emissions. Although it makes sense, it would improve the introduction by clearly stating how "effective output" is measured in discrete manufacturing (qualifying parts vs. total manufactured parts, for example) in order to prevent confusion from the outset. To help the reader understand the theoretical issue of "multi-event concurrency," strengthen the transition by clearly introducing a short, real scenario early on (such as simultaneous tool replacement and equipment parameter adjustments).
• Although the network and model are clearly outlined in Objectives (1) and (2), they read more like approachs summaries than as unique research contributions that fill in the gaps. Frame these objectives explicitly using action-oriented language that pairs the gap with the solution.

Literature review

• It is clear, in section 2.2, how discrete-time step models and discrete-event sequence models differ from one aother. However, rather than focusing on particular shortcomings in carbon accounting, the evaluation of discrete-event models mostly depends on general scheduling issues. Make a clear connection between the limitations of sequence models and the distortion of carbon accumulation rates caused by arbitrary randomization of event ordering during concurrent execution.
• Additionally, explain briefly why, while addressing multi-resource manufacturing concurrency, PDEVS's parallel transition handling and structured selection mechanism perform better than standard DEVS
• In section 2.3, the summary of contributions may seem insignificant because it closely matches previous aims. Instead of rewriting the functional description, concentrate the highlights section on the mechanism's novelty, highlighting a combination of multi-resolution granularity with PDEVS execution semantics.

Method Framework

• The text mentioned PDEVS across equipment-level atomic models and cell/workshop-level coupled models, but it lacks specific details on how coupling interfaces and message-passing protocols are formally defined. To make the input/output ports, state transition functions, and time-advance functions of the PDEVS atomic and linked models more understandable, I suggest adding brief mathematical or formal specification paragraph. This will improves the multi-resolution framework's reproducibility and methodological rigor.

Multi-Resolution Enhanced Carbon Efficiency Information Transfer Network

• The InfoPkt structure, state transitions, and bidirectional flows are all included in Figure 2, which is rich in detail. However, some text parts and routes appear dense, making it difficult to read at a glance. Can you modify the figure caption to clearly explains the visual flow to the reader (e.g., how the top half represents downward traceability and the bottom-left/right represent upward aggregation), and think about making the embedded table text in the figure graphic more readable. Or, you can split Figure 2 into two sub-figures.

Dynamic Carbon Efficiency Monitoring Model for Event Concurrency

• According to Section 5.2, preventive maintenance task's priority are automatically raised from P3 to P2 when it go beyond its specified window. Can you provide a concise mathematical condition or rule description for how that time window expiration is tracked within the PDEVS framework (e.g., via a time-advance check or a dedicated state variable).
• Step 3 and Table 2 use ascending order of equipment numbers as tie-breaker when events are otherwise indistinguishable. Can you Talk about the possible systemic or physical bias that this fixed-value tie-breaker might introduce in large-scale manufacturing cells (e.g., equipment with lower IDs consistently receiving processing precedence) and briefly explain why the validity of the carbon efficiency trajectory is unaffected.

Case Study

• According to Section 6.1, carbon emissions were not subtracted, but the simulated cumulative effective physical output was adjusted using a historical statistical waste rate of beta = 2%. Can you Include a brief explanation of why waste product-related carbon emissions are not subtracted. The methodological clarity will be strengthened by making clear if the embodied carbon of defective items is still included in the overall workshop footprint.
• The two-parameter heatmap (Figure 10) finds that while the repair duration change has a little effect on the endpoint efficiency, changing the workpiece release interval from 3 to 8 minutes considerably affects it. Can you Extend the discussion to address the practical manufacturing implications of this discovery, particularly why steady-state pacing protects against sudden disruptions better than the absolute duration of the downtime within the tested parameters.

Discussion

• The insights are heavily anchored in a specific scenario (a single grinding machine fault within a turning-grinding layout). The authors should make it clear whether these results apply to other kinds of production disruptions (such as bottleneck shifts, tool wear, or unexpected logistics blockages) in order to increase the study's wider application. The discussion should also briefly examine how the suggested PDEVS-based model will scale when managing multi-stage, highly non-linear production lines where cascade effects extend beyond adjacent cells, as the restrictions state that assembly and complex logistics are ignored.

Conclusions and Outlook

• Improve the "Future work" section to cover scalability and computational complexity. In particular, since this is typical bottleneck for discrete event simulation models in actual industrial settings, talk about how the multi-resolution PDEVS framework and the three-level priority rule will scale when applied to larger-scale, highly distributed smart factories with thousands of concurrent events.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I satisfy revisions performed by authors and would like to recommend an acceptance decision as well.

Reviewer 4 Report

Comments and Suggestions for Authors

The authors modified the revised manuscript. They considered all the comments and replied to each comment and made the required modification to the revised manuscript. I recommend accepting it in the present form.