Collaborative quality value simulation method for nuclear power equipment manufacturing based on system power flow diagram

Abstract

The present invention relates to a method for simulating the collaborative quality value of nuclear power equipment manufacturing based on a system power flow diagram, comprising the following steps: S1, establishing a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment; S2, constructing a system power flow diagram model for the collaborative quality value chain of intelligent manufacturing of nuclear power equipment based on the collaborative quality value chain model of intelligent manufacturing of nuclear power equipment; S3, performing collaborative quality value simulation by running the system power flow diagram model for the collaborative quality value chain of intelligent manufacturing of nuclear power equipment. The present invention constructs a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment, generates a system power flow diagram model, simulates and analyzes the formation and value-added process of collaborative quality value, and provides a feasible new method for the research on maximizing the quality benefits of the entire value chain and minimizing the collaborative costs, thereby avoiding the problems of insufficient collaborative control and excessive costs that may exist in traditional quality management methods.

Description

Technical Field

[0001] The present invention belongs to the technical field of quality management of intelligent manufacturing of nuclear power equipment, and specifically relates to a collaborative quality value simulation method for nuclear power equipment manufacturing based on a system power flow diagram. Background Art

[0002] The construction of nuclear power equipment is a highly complex system engineering project, involving hundreds of thousands of parts and thousands of suppliers. It has the characteristics of a life cycle spanning centuries, many participating enterprises, a wide range of business fields, and multi-source heterogeneous information. Its quality control involves cross-domain quality business collaboration, cross-platform quality information transmission, and cross-enterprise quality process docking (hereinafter referred to as "three spans"). Realizing collaborative quality control under the three spans is an inevitable choice for the construction of nuclear power equipment. However, in the process of three-span collaboration, it is very easy for the participating entities to form a situation of fighting each other due to different economic interests, resulting in inconsistent quality goals, asymmetric quality information, reduced harmony of the construction process, and increased difficulty in collaborative control. To this end, it is necessary to increase the cost investment in collaborative control activities, but the investment in this regard cannot be increased blindly. Once it exceeds a certain amount, it will inevitably cause a decline in the economic benefits of the entire value chain, which is not worth the loss.

[0003] The development of intelligent manufacturing technology has provided a new direction for the collaborative quality management of nuclear power equipment. However, at present, the existing research mainly focuses on two directions. One is to assist the collaborative quality management of nuclear power equipment by building an integrated platform, constructing an information system, and forming a management and control framework. The other is to eliminate redundant activities that affect collaboration to the greatest extent through organizational structure optimization, contract management, reward and punishment incentives and other management-level measures. None of the existing studies have studied the collaborative quality value of nuclear power equipment under the three spans from the perspective of the entire value chain. Therefore, how to study the formation of the collaborative quality value of intelligent manufacturing of nuclear power equipment, construct a collaborative quality value chain model to reveal the dynamic behavior of its value-added process, and then effectively control the collaborative quality value of intelligent manufacturing of nuclear power equipment is an urgent problem to be solved. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the technical problem to be solved by the present invention is to provide a collaborative quality value simulation method for nuclear power equipment manufacturing based on a system power flow diagram. By constructing a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment and generating a system power flow diagram model, the collaborative quality value formation and value-added process are simulated and analyzed, thereby providing a feasible new method for the research on maximizing the quality benefits of the entire value chain and minimizing the collaborative costs, thereby avoiding the problem of mismatch between collaborative control intensity and benefits that may exist in traditional quality management methods.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] The collaborative quality value simulation method for nuclear power equipment manufacturing based on system power flow diagram includes the following steps:

[0007] S1. Establish a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment;

[0008] S2. Based on the collaborative quality value chain model of nuclear power equipment intelligent manufacturing, a power flow diagram model of the collaborative quality value chain system of nuclear power equipment intelligent manufacturing is constructed;

[0009] S3. Conduct collaborative quality value simulation by running the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment.

[0010] To further improve the above technical solution, step S1 includes the following sub-steps:

[0011] S101. The key influencing factors of the collaborative quality value of intelligent manufacturing of nuclear power equipment are screened out through the Vague set method;

[0012] S102. Construct a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment through the value chain approach.

[0013] Furthermore, step S2 includes taking the key influencing factors as the boundary points of the system, determining the primary factors and setting them as horizontal variables, using arrows to represent the relationships between the factors, inputting all factors and relationships into computer software, and constructing a power flow diagram model of the nuclear power equipment intelligent manufacturing collaborative quality value chain system, which includes horizontal variables, rate variables and auxiliary variables.

[0014] Furthermore, the computer software is Vensim PLE7.3.5 software.

[0015] Furthermore, step S2 includes the following sub-steps:

[0016] S201. Determine the boundary point values ​​in the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment;

[0017] S202. Determine the numerical value of the influence degree between factors, including subjective weight, objective weight and comprehensive weight;

[0018] S203. Based on the weight calculation results, equations are constructed and values ​​are assigned for the horizontal variables, rate variables and auxiliary variables in the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment.

[0019] Further, step S3 includes setting the step size to 100, the unit is month, performing system simulation operation on the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment, and obtaining the simulation results of the collaborative quality value of intelligent manufacturing of nuclear power equipment.

[0020] Furthermore, the subjective weight is determined by the G1 method; the objective weight is determined by the entropy method; and the comprehensive weight is determined by the comprehensive integrated weighting method.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The collaborative quality value simulation method for nuclear power equipment manufacturing based on the system power flow diagram of the present invention selects the key influencing factors of collaborative quality value through the Vague set method, and constructs the collaborative quality value chain model of nuclear power equipment with the value chain method. On this basis, its system power flow diagram model is established, and the numerical values ​​of the influence degree between the boundary points and factors in the model are calculated. The collaborative quality value simulation results are obtained by running the system power flow diagram model, and the optimal quality collaborative path is found according to the simulation results, so that the enterprises participating in the nuclear power equipment construction process can make the optimal quality decision through this simulation method, assist in establishing a value-driven collaborative quality assurance mechanism, and improve the quality control level of nuclear power equipment.

[0023] The intelligent manufacturing process of nuclear power equipment is a typical complex system, and general methods cannot describe its complex dynamic behavior. Based on system dynamics and using simulation technology, this invention can qualitatively and quantitatively analyze and study the dynamic behavior of the feedback system from the inside of the system. By constructing a system power flow diagram to study the collaborative quality value of intelligent manufacturing of nuclear power equipment, it clearly reflects the dynamic operation process of this complex system with multiple variables and multiple loops and multiple feedbacks, and provides a feasible new method for the study of maximizing the quality benefits of the entire value chain and minimizing the collaborative costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment according to a specific embodiment;

[0025] Figure 2 It is a schematic diagram of a power flow diagram model of a nuclear power equipment intelligent manufacturing collaborative quality value chain system of a specific embodiment;

[0026] Figure 3 It is a schematic diagram of collaborative quality value simulation of intelligent manufacturing of nuclear power equipment in a specific embodiment;

[0027] Figure 4 It is a schematic diagram of simulation of dynamic behavior characteristics of three major collaborative capabilities in a specific embodiment;

[0028] Figure 5 It is a simulation diagram of owner satisfaction in a specific embodiment;

[0029] Figure 6 It is a schematic diagram of collaborative quality cost simulation in a specific embodiment. DETAILED DESCRIPTION

[0030] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0031] A specific embodiment of a nuclear power equipment manufacturing collaborative quality value simulation method based on a system power flow diagram; the method can be executed by a storage medium storing corresponding computer program codes when running a corresponding program; the relevant data can be manually input or determined by a computer according to a pre-set standard; by way of example, the following steps can be included:

[0032] S1. Establish a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment; specifically include:

[0033] S101. The key influencing factors of the collaborative quality value of intelligent manufacturing of nuclear power equipment are screened out through the Vague set method; Vague sets, as a mathematical tool for dealing with uncertainty problems, are often used to quantify qualitative evaluations.

[0034] Based on the existing research, through the investigation of nuclear power equipment construction enterprises, the factors affecting the value of collaborative quality are collected and summarized into 41 major factors involving the three core categories of "cross-enterprise process docking", "cross-field business collaboration" and "cross-platform information transmission". Please see Table 1-List of factors affecting the value of collaborative quality below;

[0035] Table 1

[0036]

[0037] Experts in related fields evaluated the importance of 41 collaborative quality value influencing factors, and the evaluation opinions were divided into three levels, namely {important, neutral, unimportant}; combined with the Vague method, the ranking function formula of collaborative quality value influencing factors was obtained:

[0038] s i (a i ) = t i (a i )-f i (a i )+(β-γ)π i (a i );

[0039] In the formula, t i (a i ) = the number of experts who think the i-th indicator is important / the total number of experts, f i (a i ) = the number of experts who think the i-th indicator is not important / the total number of experts. π i (a i )=1-t i (a i )-f i (a i ) is the hesitation degree. i (ai )-f i (a i )≠0, β=t i (a i ),γ=f i (a i ).

[0040] The final importance ranking values ​​of each influencing factor are obtained, as shown in Table 2-Importance ranking values ​​of influencing factors;

[0041] Table 2

[0042]

[0043] Take ɑ>0.75 as the key indicator or the remaining factors after removing the last 20% of the influencing factors are the key influencing factors.

[0044] S102. Construct a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment through the value chain approach;

[0045] The collaborative quality value chain of intelligent manufacturing of nuclear power equipment is a tool used to characterize the collaborative quality value-added process of intelligent manufacturing of nuclear power equipment. It can be defined as a complex dynamic chain structure model formed by the integration of quality chain and value chain, guided by the owner's quality needs and the "four things" principle, based on quality business processes, supported by intelligent manufacturing technology and system development and application, and with the core goal of maximizing the quality benefits of the entire value chain through the coordination of cross-enterprise quality processes, cross-domain quality business, and cross-platform quality information. Its elements include quality formation activities such as design, procurement, construction, and commissioning that support the realization of collaborative quality value, as well as supporting value activities such as cross-enterprise quality process docking, cross-domain quality business collaboration, and cross-platform quality information transmission that help increase the value of collaborative quality.

[0046] Basic quality activities such as design, procurement, construction, and commissioning form the foundation of collaborative quality value. The optimization of each activity can provide incremental value. The application of intelligent manufacturing technology and systems provides important support for the realization of supporting value activities such as cross-enterprise quality process docking, cross-domain quality business collaboration, and cross-platform quality information transmission, which can help increase the value of collaborative quality. The value-added of collaborative quality will in turn affect basic quality activities and supporting value activities, and help a new round of collaborative quality value-added. Based on the key influencing factors of collaborative quality value analysis and screening of intelligent manufacturing of nuclear power equipment, the value chain theory is applied to build a collaborative quality value chain model. Please refer to Figure 1 .

[0047] S2. Based on the collaborative quality value chain model of nuclear power equipment intelligent manufacturing, a power flow diagram model of the collaborative quality value chain system of nuclear power equipment intelligent manufacturing is constructed; specifically, the key influencing factors are taken as the boundary points of the system, and the cross-enterprise quality process docking capability, cross-domain quality business collaboration capability, cross-platform quality information transmission capability, design quality, procurement quality, construction quality, and commissioning quality are taken as first-level factors and set as horizontal variables. Arrows are used to represent the relationship between factors. All factors and relationships are input into Vensim PLE7.3.5 software to construct a digital model of the power flow diagram of the collaborative quality value chain system of nuclear power equipment intelligent manufacturing. Please refer to Figure 2 Specific details include:

[0048] S201. Determine the boundary point values ​​in the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment;

[0049] In order to ensure the consistency of the data, the value is assigned within the range of 0-1. The larger the value, the greater the impact of the factor on the collaborative quality value of nuclear power equipment intelligent manufacturing. Let (i=1,2,…,24; j=1,2,…,5) be the value of the jth indicator of the i-th evaluated object. The experts were randomly divided into four groups. Each expert was required to score the minimum value, most likely value, and maximum value of each boundary point. The expert scores were averaged. Then average the scores of each group of experts Then the scores of the four groups of experts were averaged. The values ​​of each boundary point are calculated as shown in Table 3-Boundary point values ​​of factors affecting the collaborative quality value of intelligent manufacturing of nuclear power equipment:

[0050] Table 3

[0051]

[0052] S202, determine the influence degree values ​​between factors;

[0053] 1) G1 method determines subjective weight:

[0054] The key influencing factor indicators x1, x2, ..., x n Sort by importance, and we get the relationship x1 * , x2 * , …, x n * , x i * For {x i} The i-th evaluation index after ranking in order. Suppose the expert's opinion on the influencing factor index x i-1 With x i The importance ratio w i-1 / w i The rational judgment is ri (i=n,n-1,…,2). i The values ​​of are shown in Table 4.

[0055] Table 4 ri value reference

[0056]

[0057] According to the experts’ i Value, calculate weight w i :

[0058]

[0059] w i-1 =r i w i (i=n,n-1,…,3,2);

[0060] 2) Determine objective weights using entropy method:

[0061] Based on the boundary point assignment above, the entropy method is used to calculate the entropy value e of the jth factor j , the formula is:

[0062]

[0063] In the formula, p ij It represents the characteristic weight of the i-th evaluation object of the j-th factor, Obtained by calculation.

[0064] The entropy weight formula of the jth factor is:

[0065]

[0066] In the formula, g j =|1-e j | represents the coefficient of variation.

[0067] 3) Comprehensive integrated weighting method to determine the final weight:

[0068] The comprehensive integrated weighting method is used to organically couple the two weights to improve the reliability of the data. The subjective weight w is obtained from the above two steps. j and objective weight W j , comprehensive weight formula:

[0069] P = aw j +bW j ;

[0070] In the formula, a and b are determined according to the following formulas:

[0071]

[0072]

[0073] According to the above formula and standardization processing, the comprehensive weight P is obtained, as shown in Table 5 - Weight table of comprehensive weighting method of key influencing factors.

[0074] Table 5

[0075]

[0076]

[0077] S203. Based on the above constants and parameter weight calculation results, equations are constructed and values ​​are assigned to the horizontal variables, rate variables and auxiliary variables in the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment. Each horizontal variable is the accumulation of rate variables, and each rate variable is a comprehensive calculation of the previous related variable, and its size determines the direction and speed of the change of the horizontal variable. The flow diagram constructed in this embodiment contains 8 horizontal variables, 10 rate variables and 7 auxiliary variables. As shown in Table 6-Main equation settings below.

[0078] Table 6

[0079]

[0080] S3. Perform collaborative quality value simulation by running the system power flow diagram model of the collaborative quality value chain of intelligent manufacturing of nuclear power equipment. Specifically, the system runs the collaborative quality value chain model of intelligent manufacturing of nuclear power equipment represented by the system power flow diagram data model through Vensim PLE7.3.5 software, setting the step size to 1, the unit to be month, and the step size to 100. Perform system simulation on the system power flow diagram model of the collaborative quality value chain of intelligent manufacturing of nuclear power equipment to obtain the simulation results of the collaborative quality value of intelligent manufacturing of nuclear power equipment. Please refer to Figures 3 to 6 :

[0081] from Figure 3 The operation results show that in the cross-enterprise, cross-domain, and cross-platform environment, in the early stage of nuclear power equipment collaborative quality management, due to the delayed setting of indicators such as employee quality awareness and product qualification rate, the collaborative quality value did not increase significantly in the early stage. As the construction process progresses, under the influence of intelligent manufacturing technology and collaborative quality control mechanisms, cross-enterprise quality process docking, cross-domain quality business collaboration, and cross-platform quality information transmission capabilities have improved and enhanced the collaborative quality value of nuclear power equipment intelligent manufacturing.

[0082] from Figure 4The operation results show that the operation analysis of cross-enterprise process docking capability, cross-domain quality business collaboration capability, and cross-platform quality information transmission capability shows that the three capabilities are gradually improving with the advancement of nuclear power equipment construction. They have a significant positive effect on the collaborative quality value of intelligent manufacturing of nuclear power equipment, and the degree of influence is: cross-domain quality business collaboration capability > cross-enterprise quality process docking capability > cross-platform quality information transmission capability.

[0083] Owner satisfaction and collaborative management costs are important evaluation indicators of the collaborative quality value of intelligent manufacturing of nuclear power equipment. Figure 5 The results show that owner satisfaction has been growing at a relatively high rate from the first month to the 20th month. After the 20th month, owner satisfaction has tended to be stable. Figure 6 It shows that the collaborative management cost of the nuclear power equipment construction process is very high in the early stage, and drops sharply from the first month to the tenth month. After the tenth month, the collaborative management cost tends to be stable.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A collaborative quality value simulation method for nuclear power equipment manufacturing based on a system power flow diagram, characterized by: The steps include: S1. Establish a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment; S2. Based on the collaborative quality value chain model of nuclear power equipment intelligent manufacturing, a power flow diagram model of the collaborative quality value chain system of nuclear power equipment intelligent manufacturing is constructed; S3. Conduct collaborative quality value simulation by running the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment; Step S1 includes the following sub-steps: S101. The key influencing factors of the collaborative quality value of intelligent manufacturing of nuclear power equipment are screened out through the Vague set method; S102. Construct a collaborative quality value chain model for intelligent manufacturing of nuclear power equipment through the value chain approach; Step S2 includes taking the key influencing factors as the boundary points of the system, determining the primary factors and setting them as horizontal variables, using arrows to represent the relationships between the factors, inputting all the factors and relationships into computer software, and constructing a power flow diagram model of the nuclear power equipment intelligent manufacturing collaborative quality value chain system; Step S2 includes the following sub-steps: S201. Determine the boundary point values ​​in the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment; S202. Determine the numerical value of the influence degree between factors, including subjective weight, objective weight and comprehensive weight; S203. Based on the weight calculation results, equations are constructed and values ​​are assigned to the level variables, rate variables and auxiliary variables in the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment; The computer software is Vensim PLE7.3.5 software; The subjective weight is determined by the G1 method; the objective weight is determined by the entropy method; the comprehensive weight is determined by the comprehensive integrated weighting method; Step S3 includes setting the step size to 100, the unit is month, performing system simulation operation on the power flow diagram model of the collaborative quality value chain system of intelligent manufacturing of nuclear power equipment, and obtaining the simulation results of the collaborative quality value of intelligent manufacturing of nuclear power equipment.

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