The Research of Complex Product Design Process Model under the Concept of Self-Recovery

Round 1

Reviewer 1 Report

Congratulations to the authors for this interesting and comprehensive work!

These are some of my suggestions for improving the quality of the article: 

1. Please pay attention to some titles of figures and tables that start with a small letter;

2. I would prefer that the images in figure 3 be enlarged and their quality be increased;

3. Figure 13 - For "wind amplification device" I would prefer there to be a section where the geometry (technical dimensions) of the device is presented;

4. Figure 18 - maybe the presentation from another angle of the stand would help to understand it;

5. Attention to the References - there is a double numbering of the sources.

Author Response

The authors would like to express their sincere gratitude and appreciation to the reviewer for the precious time and effort to review, comment and advise, which benefit a great deal for the improvement of the current manuscript. 

Below are our point-to-point responses to the reviewer‘s comments. All the revisions in the manuscript are specified in the authors’ responses. All revisions in the revised manuscript（attachment 1）, shown in blue font. Hope the authors’ revisions and modifications meet the reviewer’s expectation and the requirements of the Applied Sciences.

Reviewer 1’s comment item 1

Please pay attention to some titles of figures and tables that start with a small letter;

Authors’ response to Reviewer 1’s comment item 1

The author team express their grateful thanks to the reviews. The author team has revised the all figure and table headings in the manuscript to ensure there are no similar problems.

Reviewer 1’s comment item 2

I would prefer that the images in figure 3 be enlarged and their quality be increased;

Authors’ response to Reviewer 1’s comment item 1

We thank the reviewers for pointing this. The figure 3 has been re-layout, and the image in the figure has been enlarged. (Pg. 9 in the revised manuscript).

Reviewer 1’s comment item 3

Figure 13 - For "wind amplification device" I would prefer there to be a section where the geometry (technical dimensions) of the device is presented;

Authors’ response to Reviewer 1’s comment item 3

Thanks to the reviewer for the comments. Author team added a section of technical dimensions marking to the original Figure 13. (Pg.19 in the revised manuscript).

 

Reviewer 1’s comment item 4

Figure 18 - maybe the presentation from another angle of the stand would help to understand it;

Authors’ response to Reviewer 1’s comment item 4

Thanks to the reviewer for the comments. Author team added a side view section to the original Figure 18. (Pg.22 in the revised manuscript).

Reviewer 1’s comment item 5

Attention to the References - there is a double numbering of the sources.

Authors’ response to Reviewer 1’s comment item 5

Thanks to the reviewer for the comments. Author team has revised the all references in the manuscript to ensure there are no similar problems. (Pg.23-24 in the revised manuscript)

 

 

 

The author team would like to express our gratitude to the reviewer again, and these review comments have been very helpful in improving the manuscript.

Author Response File: Author Response.pdf

Reviewer 2 Report

First of all, the abstract of the manuscript needs significant improvement. It does not read fluently and does not provide a clear indication what has been achieved and how. Please revisit the abstract and re-write.

At the very first paragraph, the definition of industrial product needs to be defined in precise terms. It seems like the authors were talking about industrial systems rather than products? Product is the end result of running your system, e.g. 3D printer is a system whilst the printed components are its product. Since the authors mentioned maintenance, I assume they were talking about systems?

The introduction does not set the scene clear enough. Why analysing the product from functional level is an effective way to reduce the complexity of the product? The author mentioned “a large number of tools exist at the functional level….”, examples are necessary, even in introduction. The motivation of the study needs to be stated clearer.

In section 2.1 reference 4 is not Yao et al, according to the reference list.

Line 100 is the first time “LT” has appeared. It would be necessary to use the full name here.

Not enough literature has been reviewed in the related work to support the arguments. Please make sure more literature is included.

Section 3, line 113-116, the authors mention “realise the…..through existing components in the product”, does this imply that in order to apply the functional self-recovery process you have to have an existing product, i.e. your process is an optimisation process rather than a design process?

In section 3.1 the authors introduce main function and addition function. An example would be beneficial to help the reader understand their differences.

Section 3.2 needs better explanation.

Is table 1 from the reference of the authors derived from themselves?

Figure 1 is a little bit unclear. A better layout would be beneficial for readers to understand.

Figure 8 should appear much earlier as it explains the proposed process much clearer.

It is good to include a case study to demonstrate the approach proposed. However the paper itself is very difficult to follow mainly due to the clarity of English.

The written English is poor in this manuscript. Proof-reading is strongly recommended in future submissions.

 

References have duplicated numbers. 

Author Response

The authors would like to express their sincere gratitude and appreciation to the reviewer for the precious time and effort to review, comment and advise, which benefit a great deal for the improvement of the current manuscript. 
Below are our point-to-point responses to the reviewer‘s comments. All the revisions in the manuscript are specified in the authors’ responses. All revisions in the revised manuscript（attachment 1）, shown in blue font. Hope the authors’ revisions and modifications meet the reviewer’s expectation and the requirements of the Applied Sciences.

Reviewer 2’s comment item 1

First of all, the abstract of the manuscript needs significant improvement. It does not read fluently and does not provide a clear indication what has been achieved and how. Please revisit the abstract and re-write.

Authors’ response to Reviewer 2’s comment item 1

We thank the reviewers for pointing this. The author has rewritten the abstract of the paper and lines 7-10 of the abstract state the methodology of the study and the results obtained from the research. In the manuscript, the abstract has been indicated in blue, and the full abstract is also stated as follows (Pg. 1 in the revised manuscript).

The working environment of contemporary mechanical products is becoming more complex, and the working conditions are becoming more extreme. This has led to a significant increase in the frequency of problems in mechanical products. In order to reduce the frequency of human repair after problems, the application of the self-recovery concept has become a hot research topic in the area of smart design. However, the current application of the self-recovery concept is mostly limited to the structural and parametric levels, with less research at the functional level, which may lead to a waste of resources within products. To solve this problem, this research combines the functional-level product research method with the self-recovery concept and establishes a design process model of complex products under functional self-recovery. This model extends the application scope of the self-recovery concept and improves the efficiency of resource utilization in the product. The design process model has six steps. First, according to the user requirements and the existing product, the initial function solving is carried out, and the initial function model of the product is established. Next, the main functions of the product are determined based on the initial function model of the product. Then, according to the determined main functions of the product, combined with the parameters marked in the function structure, the self-diagnosis function is designed. After that, the LT matrix and effect library are used to design the self-regulation function corresponding to the main functions, and the parameters are used to screen the self-regulation function design scheme. Finally, according to the design scheme of the self-diagnosis function and self-regulation function, the functional period oriented to self-recovery is constructed to ensure the realization of the main functions of the product. The effectiveness of the design process model is proved through the design process of an intelligent photovoltaic power generation system at the end of the paper.

Reviewer 2’s comment item 2

At the very first paragraph, the definition of industrial product needs to be defined in precise terms. It seems like the authors were talking about industrial systems rather than products? Product is the end result of running your system, e.g. 3D printer is a system whilst the printed components are its product. Since the authors mentioned maintenance, I assume they were talking about systems?

Authors’ response to Reviewer 2’s comment item 2

We thank the reviewer for the comments. The team has thought and researched again. The product is defined as something that can be exchanged or has the potential to be exchanged^[1]. (for example, beef can be called a product, but the solar system can’t be called as product). In this paper, the designer can design an object through the functional self-recovery design process model that has the ultimate goal of satisfying a specific requirement, so the designed object must be able to be exchanged with other objects. It can be seen that the product is an appropriate word in this paper. For example, in the case of 3D printers, both the 3D printer itself and the components printed by the 3D printer have the potential to be exchanged, and both can be called as products, which can also be used in words such as maintenance.

If the reviewer has other comments, we kindly request the reviewer to point out them, and the author team will discuss and respond again. Thank you so much.

1. Edwaed Crawley, Bruce Cameron, Daniel Selva. System Architecture: Strategy and Product Development for Complex Systems[M]. New York: Pearson Education, 2016.

Reviewer 2’s comment item 3.

The introduction does not set the scene clear enough. Why analysing the product from functional level is an effective way to reduce the complexity of the product?

Authors’ response to Reviewer 2’s comment item 3

Thanks to the reviewer for the comments. The manuscript may be a bit deviating in expression, the opinion that the author wants to express is that analyzing the product from the functional level can reduce the design process complexity of the product.

In the manuscript “reduce product complexity” has been changed to “reduce design process complexity of the product”. (Lines 45-48, Pg.2 in the revised manuscript) And a brief introduction to the principle is added in the manuscript, the opinion comes from the axiomatic design and the specific reasons are explained in detail as follows.

Complexity is defined as "the measure of uncertainty in satisfying a specified functional requirement (FR)" in Axiomatic Design. At the same time, Axiomatic Design states that design is a mapping process from user-domain to functional-domain to structure-domain to process domain, where functional requirements (FR) and design parameters (DP) are needed to express system function in the functional domain, which is written in the form of FR=A*DP, Where A is the design matrix.

Through the matrix A, the designer can judge whether the system satisfies the independence axiom, and then judge the current design type of the system before mapping to the structure-domain. If the system is a coupled design, decoupling can be performed to transform the product into an uncoupled design before mapping. Therefore, the design process complexity of the system can be reduced from the functional level (function-domain) by using the design matrix A.

If the reviewer has other comments, we kindly hope the reviewer to point out.

Reviewer 2’s comment item 4.

The author mentioned “a large number of tools exist at the functional level….”, examples are necessary, even in introduction.

Authors’ response to Reviewer 2’s comment item 4

We thank the reviewer for pointing out that and a statement to this has been added to the introduction. The description is as follows (Lines 48-51, Pg.2 in the revised manuscript).

At the same time, there are a large number of problem analysis tools at the functional level, such as function models^[3], function structures^[4], resource analysis^[5], and conflict area analysis^[6], and a large number of problem-solving tools, such as effect libraries^[7], standard solutions and trimming^[8].

Reference:

3. Zhu, T.M.; Wu, C.L.; Zhou, Y.C.; Zhang, P.; Zhang, X.J. Construction of extended collision warning system digital twin conceptual scheme based on TRIZ functional modeling. Computer Integrated Manufacturing Systems. 2021, 27(02): 337-351.
4. Feng, P.E.; Yang, C.; Qiu, Q.Y.; Lou, Y.J.; Liu Y.K. Research on Functional Design of Multi-symmetry Mechanical System. Journal of Mechanical Engineering. 2016, 52(23): 1-16.
5. Guo, J.; Tan, R.H.; Sun, J.G.; Cao, G.Z.; Research on process of generating NDI ideas for products driven by design and resources. Chinese Journal of Engineering Design. 2015, 22(04): 309-316.
6. Zhang, P.; Yang, B.J.; Zhang, H.G.; Tan, R.H. Conflict determination oriented to CAI based on design-centric complexity. Computer Integrated Manufacturing Systems. 2013, 19(02): 330-337.
7. Wang, K.; Tan, R.; Peng, Q.; Sun, Y.; Li, H.; Sun, J. Radical innovation of product design using an effect solving method. Computers & Industrial Engineering. 2021, 151, 106970.
8. Bai, Z.H.; Zhang, S.; Yu, F.; Tan, R.H. Research on Trimming Method of Standard Solutions Aided Multi-level System Resource Derivation. Journal of Mechanical Engineering. 2020, 56(11): 108-120.

 

Reviewer 2’s comment item 5.

The motivation of the study needs to be stated clearer.

Authors’ response to Reviewer 2’s comment item 5

The author team has made additions to the paper (Lines 52-67, Pg.2 in the revised manuscript), marked in blue. The description is as follows：

Currently, functional-level product research methods are not well integrated with the self-recovery concept, which may lead to the wastage of functional-level resources within the product, resulting in increased difficulty in subsequent structural and parametric design.

To relieve the limitations of the current research on the self-recovery concept, this paper extends the application of the self-recovery concept to the functional level, introduces the function classification criteria to the complex product design process under the self-recovery concept, and proposes the criteria for judging the self-recovery priority of product functions. In addition, effect library software is introduced into the self-regulation function design process for predicting solutions to product problems and screening solutions to product problems by marking parameters in the function structure. After extending the application of the self-recovery concept to the functional level, the resources within the product can be maximized and the ideas of complex product design under the self-recovery concept can be broadened. Finally, a design process model of complex products under the concept of self-recovery is established to provide designers with more perspectives to realize product self-recovery.

Reviewer 2’s comment item 6.

In section 2.1 reference 4 is not Yao et al, according to the reference list.

Authors’ response to Reviewer 2’s comment item 6

Thanks to the reviewer for pointing it out. The author team has revised the all references in the manuscript to ensure there are no similar problems.

Reviewer 2’s comment item 7.

Line 100 is the first time “LT” has appeared. It would be necessary to use the full name here.

Authors’ response to Reviewer 2’s comment item 7

Thanks to the reviewer for pointing it out. Additions have been made to the corresponding sections. (Lines 130-131, Pg.3 in the revised manuscript)

Reviewer 2’s comment item 8.

Not enough literature has been reviewed in the related work to support the arguments. Please make sure more literature is included.

Authors’ response to Reviewer 2’s comment item 8

We thank the reviewer for pointing this out. Corresponding references have been added to the relevant research. The description is as follows. References 10,11,12,17,19,20 is new added.

 

2. Relevant research

2.1. Research on the concept of self-recovery

With the development of the self-recovery concept, Yang et al. ^[9] proposed a hybrid energy structure composed of solar cells and self-recovery nano-generators to solve the problem of reduced output capacity due to the potential mechanical damage of solar cells. Pan et al.^[10] used a liquid-transfer active balancing device to build a targeting self-recovery regulation system which realizes imbalance fault self-recovery at the structural level by injecting compressed air into the targeting chamber to change the mass distribution of the balancing disc and rotor. Wang et al.^[11] based on the reliability principle and self-recovery concept, proposed a multiple therapy target fault self-recovery regulation method for an electro-hydraulic control system, where the occurrence of displacement faults of the catalytic cracking unit in the refinery was reduced at the structural level by designing an adjustable actuator. Wu et al. ^[12] reasoned the situation change in a smelting furnace according to the fluctuation rate and duration of the raw material granule size in the smelting furnace by adjusting the current parameters between electrodes. YAO et al. ^[13] proposed a control method for rotor multi-frequency cycle vibration in rotor-bearing systems, which suppresses rotor multi-frequency vibration through parameter changes to achieve rotor self-seeking optimal control of vibration. Chen et al. ^[14] identified unbalanced vibrations with the help of the axial trajectory method and used a multi-directional vibration vector as the self-balancing control signal, where the unbalanced vibration was offset by parameter adjustment.

At present, the self-recovery concept is researched and applied extensively at the structural and parametric levels. Gao et al. ^[15] summarized the current research on the concept of self-recovery and formally proposed the theory of artificial self-recovery. Artificial self-recovery theory includes different technical fields, which are divided into two categories: parameter adjustment and structural adaptation, meaning that the system will be guarded against deviating from normal operation by regulating parameters, or the product will be self-adapted to variable operating conditions by changing the product structure, stiffness, and damping distribution.

At the structural and parametric levels, the research on the self-recovery concept has formed a relatively well-developed theoretical system. However, in the design stage, there are fewer research achievements in applying the self-recovery concept at the functional level.

2.2. Research of complex products at the functional level

Mechanical products designed under the self-recovery concept usually need to operate under extreme working conditions, and there will be non-linear, coupling, openness, time-varying, and other complex product features between various physical processes in the product. At the same time, in axiomatic design, Suh ^[2] proposed that product analysis from the functional perspective is an effective method for complex product design; therefore, the product analysis method and solution method at the functional level can be applied to the complex product design process under the self-recovery concept.

LI et al. ^[16] combined physical laws with function decomposition, subdivided product requirements through function units, and used physical laws to assist function unit solutions, thus improving the analysis speed and design accuracy of complex products. Liu et al. ^[17] quantified the similarity between each function unit and established the relationship between user requirements and each function unit through function decomposition and functional analogy, which accelerated the generation of conceptual solutions for ideal product principal solutions. Using function decomposition to decompose the total function of complex products into function units is the key to analyzing products from the functional perspective and reducing the difficulty of product design.

Wang et al. ^[18] organically combined the function units obtained by function decomposition with flows to establish the product function structure. The changes in product parameters were expressed in the function structure by flow attributes, and a model for analyzing and solving multi-flow problems of complex products was constructed. Pu et al. ^[19] analyzed the parameter changes in the product through the changes in flows in the function structure and established the process model of implicit conflict identification of complex products in combination with failure analysis to solve the problem of the strong latency of implicit conflict in complex products. By marking the flow in the function structure, the process of parameter change from raw materials to goods can be clearly expressed, and the functions that have problems in the products can be analyzed by detecting parameter changes.

Wang et al. ^[7] transformed the dimension of parameters in the product into the length and time dimension (LT parameter), and the genetic idea of the length and time dimension matrix (LT matrix) was applied to the product problem-solving process, combined with an effect library to produce a disruptive and innovative design solution for complex products. Cao et al. ^[20] built an effect chain reasoning process guided by idealized physical quantity resources through the connection between the LT dimension and physical effects, where the generation of high-level innovative solutions was accelerated by using an LT matrix. Using the connection between the LT dimension and effect and combining the genetic ideas in the LT matrix with effect library software for solving product problems will speed up the solution of complex products and improve the efficiency of complex product design.

As can be seen, scholars all over the world have conducted a lot of research at the functional level and put forward relatively perfect problem analyses and solutions. By combining the self-recovery concept with product analysis methods and solution methods at the functional level, and extending the application of the self-recovery concept to the functional level, intelligent product design will be carried out from more angles and the design ideas of complex products will be broadened.

 

References:

7. Wang, K.; Tan, R.; Peng, Q.; Sun, Y.; Li, H.; Sun, J. Radical innovation of product design using an effect solving method. Computers & Industrial Engineering. 2021, 151, 106970.
8. Yang, D.; Ni, Y.; Su, H.; Shi, Y.; Liu, Q.; Chen, X.; He, D. Hybrid energy system based on solar cell and self-healing/self-cleaning triboelectric nanogenerator. Nano Energy. 2021, 79, 105394.
9. Pan, X.; Wu, H.Q.; Gao, J.J. Rotating Machinery Targeting Self-recovery Regulation System for Imbalance Vibration Fault with Liquid-transfer Active Balancing Device. Journal of Mechanical Engineering. 2015, 51(01): 146-152.
10. Wang, Q.F.; Gao, J.J.; Yuan, Q.B.; Research and Application of Self-recovery Smart Electro-hydraulic Control System on Axial-blower Static Blade Adjustable Actuator. Journal of Mechanical Engineering. 2016, 52(20): 185-192.
11. Wu, Z.W.; Wu, Y.J.; Chai, T.Y; Sun, J. Data-driven abnormal condition identification and self-healing control system for fused magnesium furnace. IEEE Transactions on Industrial Electronics, 2014, 62(3): 1703-1715.
12. Yao, J.F.; Gao, J.J.; Wang, W.M. Multi-frequency rotor vibration suppressing through self-optimizing control of electromagnetic force. Journal of Vibration and Control. 2017, 23(5), 701-715.
13. Chen, L.F.; Li, Z.J.; Wang, W.M.; Gao, J.J. Self-recovery Principle and Method for Unbalanced Vibration of Rotating Machinery. Journal of Mechanical Engineering. 2022, 57(22), 416-424.
14. Gao, J.J. Artificial Self-recovery and machinery self-recovery regulation system. Journal of Mechanical Engineering. 2018, 54(8), 83-94.
15. Li, M.; Cao, G.; Liu, W.; Du, C.; Dong, D.; Tan, R. Research of Products’ Function Decomposition Drive by Reasoning of Physical Quantity. Procedia CIRP. 2016, 39, 114-118.
16. Liu, X.M.; Huang, S.P.; Wang, J.H.; Lin, G.J. Conceptual Design Based on TRIZ & Function Analogy for Product Innovation. Journal of Mechanical Engineering. 2016, 52(23): 34-42.
17. Wang, X.R.; Zhang, J.H.; Zhao, R.K.; Liu, J.S.; Ding, L.Q. Multi-flow problem analysis and solution process model of complex electromechanical system. Journal of Machine Design. 2020, 37(7).
18. Pu, X.J.; Zhang, J.H.; Li, J.Y.; Zhao, L.G. Research on Implicit Conflict Recognition Method for Complex Technology System. Machine Design and Research. 2021, 37(04): 1-8+25.
19. Cao, G.Z.; Han, W.P.; Sun, Y.D.; Wang, K.; Gao, C. Research and Application of Effect Reasoning Process Based on LT Table. Machine Design and Research. 2022, 38(01): 11-16.

 

Reviewer 2’s comment item 9.

Section 3, line 113-116, the authors mention “realise the…..through existing components in the product”, does this imply that in order to apply the functional self-recovery process you have to have an existing product, i.e. your process is an optimisation process rather than a design process?

Authors’ response to Reviewer 2’s comment item 9

We thank the reviewer for pointing this out. Regarding the design process and optimization process, the details are described as follows.

In the field of product design, design is divided into original design and redesign according to different design starting points and tasks ^[1]. And the redesign includes improved design and updated design, the optimization process belongs to the improved design in the redesign stage. The design process proposed in this manuscript contains two stages: the original design process and the redesign (improved design) process.

The initial function solving and the construction of the initial function model in Section 4.1 do not have a complete existing system as a starting point, therefore belongs to the original design stage; the design process in Section 4.2-4.6 is based on the initial model of the system constructed in Section 4.1, therefore belongs to the redesign (improved design) stage. The design process is used in the title of the manuscript because the design process presented in this manuscript cannot be expressed only by the original design process or the redesign (improved design) process. Perhaps the reviewer thinks that sections 4.2-4.6 should be marked that this 5 sections belonging to the redesign (improved design) stage?

 

References:

1. Dieter G E, Schmidt L C. Engineering design[M]. Boston: McGraw-Hill Higher Education Boston, 2009.

Reviewer 2’s comment item 10.

In section 3.1 the authors introduce main function and addition function. An example would be beneficial to help the reader understand their differences.

Authors’ response to Reviewer 2’s comment item 10

Thanks to the reviewer for pointing it out. The authors have given examples in section 3.1(Lines 161-169, Pg.4 in the revised manuscript) and the description is as follows.

For example, with the development of electronic devices, additional functions of the electric water heater such as “reducing energy consumption” and “timing shutdown” have emerged. However, for users, the main function of the electric water heater is always “improve water temperature”. When the “improve water temperature” function fails, the product will stop running directly. When the “timing shutdown” or “reduce energy consumption” function fails, the energy consumption of the electric water heater will increase, but the product will still run. Therefore, if the self-recovery concept is applied to the design process of the electric water heater, the first target is to ensure the realization of the function “improve water temperature”.

 

Reviewer 2’s comment item 11.

Section 3.2 needs better explanation.

Authors’ response to Reviewer 2’s comment item 11

Thanks to the reviewers for pointing this out. The revised manuscript explains the self-diagnosis function from “what is self-diagnostic function”, “why it is necessary to design self-diagnosis function”, and “how to design self-diagnosis function” three aspects in section 3.2(Lines 177-210, Pg.4-5 in the revised manuscript), the description is as follow 4 paragraphs. If the reviewer thinks that the explanation of the self-diagnosis function is still unclear, please point it out in detail, and the author team will add and explain again.

3.2. The principle of self-diagnosis function design

The self-diagnosis function is the section that gives the product the ability to diagnose problems in the design stage. The self-diagnosis function has two main roles in the product design process under the self-recovery concept: first, to detect whether the function has problems; second, to initiate the self-regulation function after diagnosing the product problems. A reasonable self-diagnosis function is a necessary link to construct a functional period oriented to self-recovery and is the key to realizing self-recovery regulation.

Function expresses the relationship between the input parameters and output parameters of a technical system, which is generally expressed in the form of a verb and a noun. The verb expresses the operation completed by the product, and the noun represents the operation object, in which the noun is measurable. When there is a problem with a function, the output parameters of the function will be changed, and by detecting the change in the parameters of the function, it can be judged whether there is a problem with the function. Some functions’ noun description is parameter information, where the noun can be directly confirmed as the diagnosis object. However, the noun description of some functions hides the parameter information, and thus the designer needs to identify the specific parameter information of the function according to the function's working environment before diagnosing. For example, in the function "generate pressure", the verb is “generate”, and the noun is “pressure”; the pressure itself is the parameter information, so it is feasible to diagnose problems with the function “generating pressure” by detecting the pressure. As for the function of “transport goods”, the noun is “goods”, designer needs to identify the parameter of the noun "goods", which may be "height" or "location", or other parameters according to the environment of the function. After confirming the parameter hidden in the noun, the designer will find the corresponding detection parameter.

As there may be a coupling between functions, when the main function of the product has problems, the output parameters of its coupled functions will also be changed. When the complexity of the product is high and it is difficult to diagnose the main function directly, the coupling between functions can be used to diagnose the main function indirectly by diagnosing the functions coupled with the main function.

In order to visually express the parameter changes within the product from raw materials to goods and to accelerate the efficiency of self-diagnosis function design, the product function structure could be established by combining the function units obtained by the function decomposition in an orderly manner. The changes in the flow attributes of the function structure could be marked to express the functional output parameters.

Reviewer 2’s comment item 12.

Is table 1 from the reference of the authors derived from themselves?

Authors’ response to Reviewer 2’s comment item 12

Thanks to the reviewer for pointing this out. The authors' team has added references in the corresponding positions in Table 1. (Lines 235, Pg.5 in the revised manuscript)

Reviewer 2’s comment item 13.

Figure 1 is a little bit unclear. A better layout would be beneficial for readers to understand.

Authors’ response to Reviewer 2’s comment item 13

Thanks to the reviewer for pointing this out. The figure 1 has been re-layout. (Pg.6, in the revised manuscript).

Reviewer 2’s comment item 14.

Figure 8 should appear much earlier as it explains the proposed process much clearer.

Authors’ response to Reviewer 2’s comment item 14

Thanks to the reviewer for pointing this out. The authors' team discussed and concluded that Figure 2 and Figure 8 are related. Figure 2 states the methods to construct the functional period and the principle of the functional period. Figure 8 expresses the form of the functional period. In order to express the discussion process earlier, the author team supplemented Figure 2 with a schematic representation of the product running different functional period for different work conditions, and also added the corresponding expression in Section 3.4. We hope that the added Figure 2(Pg.7 in the revised manuscript) can express the proposed process earlier and clearer.

The specific reasons for not changing the position of Figure 8 are as follows: The author team believes that the functional period expresses the information about the execution sequence of functions, and its construction process must be carried out after the completion of all function solving, so it should be used as the last part of the design process model. If the position of the self-diagnosis function and the self-regulation function in the functional period cannot be confirmed, the operation status of the main functions cannot be guaranteed, and the construction of the functional period oriented to self-recovery will be meaningless. Therefore, the construction of the functional period oriented to self-recovery in section 4.6 is arranged after the design of self-diagnosis function in 4.3 and the design of self-regulation function in 4.4. Next, only after finding the final principal solution, the designer can judge the coupling situation during the system operation and then construct the functional period to avoid the coupling of functions. Therefore, this paper arranges the construction of the functional period oriented to the self-recovery in Section 4.6 after the product function resolution oriented to self-recovery in Section 4.5.

We hope the changes in the manuscript are suitable to the reviewer’s comments. If the changes still do not answer the comments, please point out in detail and the team will think about the comments again and make changes and reply.

Reviewer 2’s comment item 15.

It is good to include a case study to demonstrate the approach proposed. However, the paper itself is very difficult to follow mainly due to the clarity of English.

Authors’ response to Reviewer 2’s comment item 15.

Thanks to the reviewers for pointing this out. In Chapter 5 Engineering Example (Pg. 14-21 in the revised manuscript), the design process model in Chapter 4 is proved by the design process of the intelligent photovoltaic power generation system. Perhaps the language of the article does not clearly express the ideas of the author team, the author team has made an English editing to the manuscript, and we hope that the English-edited article will express the author team's viewpoint more clearly. If the reviewer thinks that the case in Chapter 5 does not clearly prove the design process model, please point out in detail and the author team will further explain the unproven parts.

Reviewer 2’s comment item 16.

The written English is poor in this manuscript. Proof-reading is strongly recommended in future submissions.

Authors’ response to Reviewer 2’s comment item 16.

Thanks to the reviewers for pointing this out. The author team has made an English editing to the manuscript, and we hope that the English-edited article will express the author team's viewpoint more clearly.

Reviewer 2’s comment item 17.

References have duplicated numbers. 

Authors’ response to Reviewer 2’s comment item 17

Thanks to the reviewers for pointing this out. The author team has revised the all references in the manuscript to ensure there are no similar problems. (Pg. 23-24 in the revised manuscript)

 

 

 

The author team would like to express our gratitude to the reviewers again, and these review comments have been very helpful in improving the manuscript.

 

Author Response File: Author Response.pdf