Simulation of Energy and Media Demand of Beverage Bottling Plants by Automatic Model Generation

Round 1

Reviewer 1 Report

The paper "Simulation of energy andmedia demand of beverage bottling plants by automatic model generation" by Bär et al covers a very important topic: lowering the burden of simulation modelling to be applied in small to medium enterprises (SMEs). The authors provide a well written and well analyzed study.

A few suggestions to the authors:

• The doctoral thesis of Hubert "Unternehmensweite Modellierung und Simulation von Produktionssystemen der Prozessindustrie am Beispiel von Brauereien" (FAU, 2018) should be included in relevant literature. Certain aspects (bottling lines, SMEs aspects and holistic approaches incl. modelling and simulation of breweries) are discussed there, which could be beneficital for this paper and your future research
• An easy to grasp graphical overview (e. g. real SME bottling line --> data --> database --> XML --> simulation model) --> simulation sofware PacSi) of the approach shown in this paper good be beneficial for the reader to better understand your work
• In the introduction line 38, a number/percentage instead of "large part" would be helpful
• Literature / details to PacSi might be beneficial

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Guidelines for Authors:

The abstract does not clearly indicate the purpose of the work and the methodology of conduct.

Point 2 in the article is modestly described. The analyzed areas of the process should be clearly indicated, in addition, please indicate in the diagram the technological operations that require modernization. What is the scale of the plant's operations, what markets do the products go to (domestic, foreign). These aspects require detailed clarification.

The diagram description should include the time, cost and energy consumption of each stage before and after the upgrade.

There are no such indicators in the article. What is the economic effect?

There is a need to separate a subchapter containing the effects of the changes introduced in the plant.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

The abstract is difficult to follow. Please consider rewriting as follows:

[Small and medium-sized enterprises of the brewing and beverage industry cannot ensure energy and media efficiency mainly due to capital and knowledge inadequacy. This paper addresses this problem. In particular, this paper presents a pragmatic method. The method can determine the energy and media demands even though there is a lack of capital and knowledge (i.e., databases and models of the complex brewing and beverage production plant). Accordingly, a modeling editor is developed to implement the method. The editor integrates a standardized data structure and a parameter simulation tool. A given production plant can be modeled with adequate details using the editor. In addition, the editor automatically generates a simulation model. A beverage bottling plant was studied, and the necessary datasets were obtained for implementing the proposed editor, thereby, the method. It was confirmed that the simulated values of electrical energy and compressed air consumption match the real ones. The measures to increase energy and media efficiency are also found effective. Using the present method, small and medium-sized enterprises of the brewing and beverage industry can easily uncover the avenues of potential savings, test the effectiveness of optimization strategies, and substantiate possible investment decisions.]

Issue of sustainability:

There are four issues that should be tackled simultaneously if someone wants to ensure sustainability in real-life setting. material efficiency, energy efficiency, product efficiency. Regarding materials and energy efficiency see the following paper.

International Journal of Sustainable Manufacturing, 2013 Vol.3 No.1, pp.20 – 36 DOI: 10.1504/IJSM.2013.058640

Analyzing the Sustainability of Bimetallic Components, Int. J. Automation Technol., Vol.8, No.5, pp. 745-753, 2014. doi: 10.20965/ijat.2014.p0745

As can be seen in the above papers, material efficiency calculation requires datasets of primary materials production (both energy and resources related) whereas the energy efficiency calculations require datasets of manufacturing processes in finished product (in authors’ case figure 2). All these datasets are subjected to uncertainty.

However, when we want to improve the product efficiency (whether or not the product can fulfill the customer needs) requires innovative solutions. For example, consider the following work.

Strategies for Developing Milling Tools from the Viewpoint of Sustainable Manufacturing, Int. J. Automation Technol., Vol.10, No.5, pp. 727-736, 2016. doi: 10.20965/ijat.2016.p0727

Lastly, if we want to improve system efficiency, we need to borrow human intelligence on ground. For a description of system efficiency (which is a relatively new idea), please refer to the following work:

A Sustainable Reverse Engineering Process, https://doi.org/10.1016/j.procir.2021.01.144

Issue of lack of datasets or sophisticated modeling technique.

This issue is referred to as epistemic uncertainty. In this case, we jump to a situation where we find vague and imprecise pieces of information, we call the granular information. We need special computational methods and tools for dealing with granular information. The author may refer to the following for epistemic uncertainty and granular information computation-based decision making.

A decision model for making decisions under epistemic uncertainty and its application to select materials. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 31(3), 298-312. doi:10.1017/S0890060417000191

Based on the comments, please revisit some of relevant segment of the manuscript.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

ISSUE 1: The manuscript is an extended work of authors’ previous publication (attached). Please compare Figure 6 of the attached file with Figure 3 of the manuscript. Authors’ did not use the attached publication in the manuscript as a reference and did not highlight the similarity and dissimilarly.

ISSUE 2: In both cases (published work and manuscript), the authors consider time series datasets of energy consumptions in deciding the right course of action toward sustainability.

ISSUE 3: SMEs do not have enough IT infrastructure as well as human resources to run data- and XML-coding-based modeling and simulation systems. We need to turnkey system to make it sustainable for SMEs. Authors must show a turnkey solution, if they want to help SMEs. This element was missing in the manuscript.

Therefore, authors must acknowledge their own work in the manuscript and show us that is the originality. Otherwise, we cannot accept the manuscript as a new work.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Round 3

Reviewer 3 Report

authors cleared the concerned raised in the revised version.