Change risk control method based on product multi-domain design information association constraint network model

Abstract

The present invention discloses a change risk control method for a product multi-domain design information association constraint network model. The method organizes the design information of the product function domain, parameter domain and structure domain into a multi-layer network model, which can intuitively and profoundly express the detailed association rules of the relevant parameter information in the product design parameter information domain, as well as the influence process of the parameter information on the function and structure information after modification. It is an important guarantee for realizing the consistency modification of product design information, and is also a data-driven method for design change analysis. Then, according to the change requirements, the design elements affected by the change are determined by means of parameter calculation, and based on the set of functional and structural elements affected by the change, the risk of the change to the product is further evaluated through the change risk evaluation index, thereby realizing the risk prevention and control of the design change, and meeting various needs in practical applications.

Description

Technical Field

[0001] The present invention relates to the field of product design, and in particular to a method for controlling the change risk of a product multi-domain design information association constraint network model. Background Art

[0002] With the development of the economy and society, enterprises will make adaptive modifications to the original products to meet new customer needs in order to better meet customer needs. These needs may be new functions, performance requirements for products, or improvements and optimizations in product structure. However, this adaptive modification will lead to a series of chain-related changes, and even produce an avalanche effect of design change propagation, causing excessive consumption of design resources (relative to product development resource constraints), making the efficiency and effect of variant design less than ideal. If the change risk of the product is obtained through predictive analysis of the impact of the change before design, there are two benefits for the enterprise. First, based on the change risk, the decision-making department for change execution can make a more scientific decision on whether to execute the change, rather than relying solely on experience, to avoid the effect of the change after execution not meeting expectations; in addition, if the change must be executed, the impact range of the change can be predicted to guide the designer to take risk prevention measures for specific key functions and structures to avoid further expansion of the impact of the change.

[0003] However, the current change risk analysis and decision-making within the enterprise only involves certain key requirements and key product series. When faced with certain personalized requirements and small batch customized products, the decision-making department often does not participate in risk analysis and decision-making. Designers can only judge their feasibility through experience, and specific expenditures are also evaluated by experience. For this reason, it is particularly important to build a comprehensive management model for product design information and propose a means of risk analysis based on this model, especially for the evaluation of change requirements at all levels of product characteristics. Summary of the invention

[0004] The present invention provides a change risk control method for a product multi-domain design information association constraint network model. The present invention effectively organizes product design information, can realize the visualization of change information, and also improves the efficiency of change analysis. See the following description for details:

[0005] A method for controlling the change risk of a product multi-domain design information association constraint network model, the method comprising the following steps:

[0006] According to the product design principles, the design information of the product function domain, parameter domain and structure domain is extracted to build a multi-domain association constraint network model of the product;

[0007] Under the multi-domain association constraint structure of the product, the change parameters are determined through an automated parameter matching mechanism or parameter calculation involving designers; the functional structure affected by the change is determined through a mapping relationship between the change parameters and the function and structure;

[0008] The function set and structure set affected by the change are input into the indicator system for change risk prediction, and the risk value of the change is obtained through risk quantification methods, thereby achieving prevention and control of change risks.

[0009] The product multi-domain association constraint network model includes: an association constraint network model in a parameter domain, and a binary network model of a function tree and a structure tree.

[0010] Furthermore, the association constraint network model in the parameter domain is:

[0011] G P =(DP, AC, PE)

[0012] Among them, the parameter node set DP=(P1,P2,...P k ,...P m ) indicates that P k is the kth design parameter, the associated constraint set AC=(R1,R2,...R h ,...R n ) indicates that R h is the hth association constraint, the parameter and the association constraint edge set PE = (P1-R1, P2-R 1... P k -R h ,...P m -R n ), P k -R h Indicates that the kth design parameter is associated with the hth association constraint, or the hth association constraint contains the design parameter P k .

[0013] Among them, the binary network model of the function tree and the structure tree is:

[0014] G F =(F, FE)

[0015] G S =(S, SE)

[0016] Among them, the design function node set is F=(F1,F2,...F k ,...F i ) indicates that F k is the kth product function, and the edge set of the function tree is expressed as FE = (F1-F 1,1 ,...Fk -F k,1 ,...F k,1 -F k,1,2... ), F k -F k,1 represents the edge between the kth function and its first sub-function, F k,1 -F k,1,2 It represents the edge between the first sub-function and its second sub-function in the kth function. The product structure node set is represented by S = (S1, S2, ... S k ,...S j ) indicates that S k represents the kth product structure, SE = (S1-S 1,1 ,...S k -S k,1 ,...S k,1 -S k,1,2... ), S k -S k,1 , represents the edge between the kth structure and its first substructure, S k,1 -S k,1,2 Represents the edge between the first substructure and its second substructure in the kth structure.

[0017] Preferably, the parameter change is determined by an automated parameter matching mechanism or parameter calculation involving designers:

[0018] When changes propagate within the parameter range, the design team determines whether the change requirements exceed the design margin of the parameters, and performs parametric calculations based on the associated constraints to determine which design parameters need to be adjusted and the amount of change in the parameters, and conducts the impact mapping process from parameters to functional structures.

[0019] The beneficial effects of the technical solution provided by the present invention are:

[0020] (1) Effectively organizing product design information can visualize change information and improve the efficiency of change analysis;

[0021] (2) The present invention uses comprehensive analytical indicators to quantify the risk of product changes, thus getting rid of the ambiguity of empirical decision-making and making the risk analysis of changes more accurate and scientific. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a schematic diagram of the product multi-domain association constraint network model;

[0023] Figure 2 Provides a risk assessment indicator architecture. DETAILED DESCRIPTION

[0024] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention are described in further detail below.

[0025] A change risk control method for a product multi-domain design information association constraint network model is proposed. A product multi-domain association constraint network model is constructed. The model is based on the change impact association between design elements. At the same time, a multi-index risk assessment method is proposed based on the model, and quantitative analysis is performed to more accurately predict the risks brought by product changes to enterprises. The specific implementation methods are as follows:

[0026] 1. The method for constructing a product multi-domain association constraint network model includes:

[0027] When constructing the association constraint network model in the parameter domain, first extract the design parameters of the product from the product parametric design manual or parametric configuration system. In the parameter domain, parameters can be divided into performance parameters, structural parameters, material parameters, process parameters, etc. The association constraints between parameters are mainly divided into two categories, functional association and conditional association. The functional association is represented by y=f(x1, x2,…, x n ) represents, where y is the parent node, x1, x2, ..., x i For child nodes, the relative relationship between the parent node and the child node in the function association will change due to different design goals, but they still belong to the same association constraint. The conditional association is a non-equality, using the formula f(x1, x2, ..., x n )>0 indicates.

[0028] By extracting basic data such as product design parameters and functional associations and conditional associations between parameters, a parameter network model of the product is established. Assuming that the design of a product involves m design parameters, the design parameter node set can be represented by DP = (P1, P2, ... P k ,...P m ) indicates that P k is the kth design parameter. In the network model, a circle can be used to represent the parameter node. If the product design involves n associated constraints, the associated constraint set can be represented by AC = (R1, R2, ... R h ,...R n ) indicates that R h is the hth association constraint. In the network model, a rectangle can be used to represent the association constraint node. Parameters and association constraint edge set PE = (P1-R1, P2-R 1... P k -R h ,...P m -R n ), where P k -R hIndicates that the kth design parameter is associated with the hth association constraint, or the hth association constraint contains the design parameter P k In the network model, the edge between a function association and a parameter node can be represented by a bidirectional arrow, and the edge between a conditional association and a parameter node can be represented by a unidirectional arrow pointing from the conditional association to the corresponding parameter node.

[0029] Therefore, the parameter network model G P It can be expressed as:

[0030] G P =(DP, AC, PE)

[0031] If the design of a product involves i basic functions of the product, the design function node set can be used as F = (F1, F2, ... F k ,...F i ) indicates that F k is the kth product function. In order to more clearly express the hierarchical relationship between the function trees, the first sub-function node of the kth function can be represented by F k,1 It means that as the function tree is further decomposed, F k,1 The first subfunction can be used with F k,1,1 In other words, the functional structure in the function tree can be expressed by analogy. In the network model, a rounded rectangle can be used to represent a functional node. The edge set of the function tree can be expressed as FE = (F1-F 1,1 ,...F k -F k,1 ,...F k,1 -F k,1,2... ), where F k -F k,1 represents the edge between the kth function and its first sub-function, F k,1 -F k,1,2 Indicates the edge between the first sub-function and its second sub-function in the kth function. In the network model, it can be represented by a one-way arrow from the parent function node to the child function node. The product structure tree can be expressed in the same way. The product structure node set can be represented by S = (S1, S2, ... S k ,...S j ) indicates that in the model, in order to distinguish it from the function node, a parallelogram can be used to represent the component structure node of the product. In summary, the function tree and the structure tree can be represented by a network model containing two tuples:

[0032] G F =(F, FE)

[0033] G S =(S, SE)

[0034] By constraining the parameter nodes and the associations between parameters, Figure 1 When modeling the functional domain network of a product, it is necessary to extract the functional element information of the product from the functional design specification, and combine the experience of designers to establish the logical relationship and affiliation between the functional elements into a functional tree or functional chain structure, and construct the functional element nodes and the associated constraints between the nodes. Figure 1 When modeling the structural domain network of a product, it is necessary to extract the structural information of the product from the BOM (Bill of Materials) table and the CAD (Computer-Aided Design) system, build a product structure model through the assembly relationship and affiliation between parts, and establish the relationship between part nodes and nodes. Figure 1 The structural domain network model shown.

[0035] Finally, cross-domain association constraints are established through the matching relationship between design parameters and functions and structures. The specific data sources are shown in Table 1:

[0036] Table 1 Data requirements for product multi-domain association constraint network model

[0037]

[0038]

[0039] 2. Methods for determining the scope of impact of changes include:

[0040] The means for determining the scope of change impact are generally divided into two categories, one is the automated change scope search based on experience and rules, and the other is the determination of the change impact scope based on the calculation of the designer. Based on the multi-layer network model of multi-domain association constraints, the embodiment of the present invention adopts a combination of two methods when determining the scope of change impact. First, when the change is propagated within the parameter range, the design team determines whether these requirements exceed the design margin of the parameters according to the change requirements, and performs parametric calculations according to the association constraints. The calculation process mainly determines which design parameters need to be adjusted and the amount of parameter change. This is because parametric design involves a lot of implicit knowledge, which is difficult to achieve automation. After the parameter change range and change amount are determined, the impact mapping process of the parameters to the functional structure is performed. This process can be stored by the computer. Taking the elevator as an example, when the height of the elevator car is increased by 0.5m, which structures will be affected? Which functions will be affected? This is related to the module division, functional structure configuration and other aspects at the beginning of product design. The matching of parameter domain functional structure can be achieved and stored in the network structure through information extraction.

[0041] III. Construction of change risk indicator system and risk quantitative assessment method:

[0042] The embodiment of the present invention takes into account various factors that may cause risks to the enterprise after product changes, and establishes an indicator system for risk assessment. The indicators mainly include:

[0043] (1) Safety indicators, i.e., whether the product change will cause personal injury to the users of the product, whether it complies with ergonomics, etc.;

[0044] (2) Economic indicators, that is, whether the cost of the product change exceeds the benefits. If the economic risk is assessed to be low, the change is a high-risk change. Cost indicators include production costs and change process management costs, etc. Benefits include not only economic benefits but also social benefits, as well as the promotion of product brand effects.

[0045] (3) Construction period indicators: First, analyze the importance and priority of the change, and at the same time analyze the actual processing conditions of the workshop production line within the enterprise and the time for personnel organization. If the change cannot be completed within the specified time, the risk of breach of contract will be borne;

[0046] (4) Performance and quality indicators: whether the integrity of the product can be guaranteed after the product change is completed, whether the durability is reduced, and whether the overall quality of the product is reduced. Although the basic functional requirements of the product are met, there are still risks in terms of performance and quality;

[0047] (5) Technical indicators: that is, how difficult it is to complete the product change. If the change involves a large number of parameter modification and optimization, product structure remanufacturing, and functional performance verification, the product design is generally difficult and requires multiple coordination and implementation between departments. If the technical risk is too high, product redesign can be considered.

[0048] (6) Environmental protection index: whether the product meets environmental protection requirements after the change, whether there are processes and equipment that seriously pollute the environment, whether the product's emission and radiation meet the standards, etc. If the environmental protection requirements stipulated by law are violated, there is a risk of product write-off and recall.

[0049] Through the above basic risk assessment indicators, we can construct Figure 2 The indicator system shown.

[0050] Based on the index system, the risk assessment method can further adopt the quantitative analysis of risk. The embodiment of the present invention adopts the improved TOPSIS method (superiority and inferiority solution distance method) to realize the quantitative analysis of risk, because the set of design elements affected by the change is fixed:

[0051] (1) Index attribute homogeneity

[0052] Since the constructed indicator system does not contain intermediate indicators and interval indicators, only very small indicators are positively oriented. The indicators that need to be oriented include: cost evaluation X 21、Project cycle evaluation X 31 , Technical implementation difficulty assessment X 51 For the three items, just convert them into inverse numbers.

[0053] That is: cost assessment X * 21 =1 / X 21 , Project Cycle Evaluation X * 31 =1 / X 31 , technical implementation difficulty assessment X * 51 =1 / X 51 .

[0054] (2) Constructing the initial matrix

[0055] Since there is no historical comparable data for some changes, it is impossible to determine which solutions are the best by comparison. Therefore, the expert scoring method is used to obtain the value of the product change risk characteristic. The specific value can be obtained by scoring S by n experts. i The mean of is obtained:

[0056]

[0057] Construct an initial 12-dimensional matrix containing 12 indicators:

[0058] X=[x 11 x 12 x 13 x * 21 x 22 x * 31 x 32 x4 x * 51 x 52 x 61 x 62 ]

[0059] Normalized matrix:

[0060] Z = [x 11 x 12 x 13 x * 21 x 22 x * 31 x 32 x4 x * 51 x 52 x 61 x 62 ]

[0061] (3) Determine the ideal solution and the highest risk solution

[0062] Similarly, since there is no comparison plan, it is still impossible to obtain the optimal solution and the most accurate split of the product risk indicators. Therefore, it is still necessary to use the expert scoring method to determine the ideal risk level and the acceptable minimum risk as two ideal solutions:

[0063]

[0064]

[0065] Z + =[z + 11 z + 12 z + 13 z + 21 z + 22 z + 31 z + 32 z + 4 z + 51 z + 52 z + 61 z + 62 ]

[0066] Z - =[z - 11 z - 12 z - 13 z - 21 z - 22 z - 31 z - 32 z - 4 z - 51 z - 52 z - 61 z - 62 ]

[0067] (4) Determination of indicator priority

[0068] The priority of indicators is determined by product characteristics. Taking elevator products as an example, the environmental risk and technical risk of the product are not the main considerations, because the technical difficulty of elevator products is low, the application of new technologies is slightly lacking, and there is no pollution emission problem with electric drive. Whether the safety meets the standards, whether the product is durable, and resource scheduling and economic benefits under mass production conditions should be considered as the key issues. Priority should be determined at the beginning of product design, and each indicator should have a corresponding weight, which can be represented by w.

[0069] (5) Evaluate the risk of change

[0070] Calculate the distance between each risk indicator of the product and the ideal solution and the worst solution:

[0071]

[0072]

[0073] Calculate the closeness to indicate the risk value of product change:

[0074]

[0075] C is a value greater than 0 and less than 1. The closer its value is to 1, the lower the risk of implementing a product change. Based on expert scoring and combined with the improved TOPSIS method, the risk value of the change can be quantified.

[0076] Unless otherwise specified, the models of the components in the embodiments of the present invention are not limited, and any device that can perform the above functions may be used.

[0077] Those skilled in the art will appreciate that the accompanying drawing is only a schematic diagram of a preferred embodiment, and the serial numbers of the embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A change risk control method for a product multi-domain design information association constraint network model, characterized in that: The method comprises the following steps: According to the product design principles, the design information of the product function domain, parameter domain and structure domain is extracted to build a multi-domain association constraint network model of the product; Under the multi-domain association constraint structure of the product, the change parameters are determined through an automated parameter matching mechanism or parameter calculation involving designers; the functional structure affected by the change is determined through a mapping relationship between the change parameters and the function and structure; Input the function set and structure set affected by the change into the indicator system for change risk prediction, obtain the risk value of the change through risk quantification method, and then realize the prevention and control of change risk; The product multi-domain association constraint network model includes: an association constraint network model in a parameter domain, a binary network model of a function tree and a structure tree; Among them, the association constraint network model in the parameter domain is: G P =(DP, AC, PE) Among them, the parameter node set DP=(P1,P2,...P k ,...P m ) indicates that P k is the kth design parameter, the associated constraint set AC=(R1,R2,...R h ,...R n ) indicates that R h is the hth association constraint, the parameter and the association constraint edge set PE = (P1-R1, P2-R 1... P k -R h ,...P m -R n ), P k -R h Indicates that the kth design parameter is associated with the hth association constraint, or the hth association constraint contains the design parameter P k ; Among them, the binary network model of the function tree and the structure tree is: G F =(F,FE) G S =(S, SE) Among them, the design function node set is F=(F1,F2,...F k ,...F i ) indicates that F k is the kth product function, and the edge set of the function tree is expressed as FE = (F1-F 1,1 ,...F k -F k,1 ,...F k,1 -F k,1,2... ), F k -F k,1 represents the edge between the kth function and its first sub-function, F k,1 -F k,1,2 It represents the edge between the first sub-function and its second sub-function in the kth function. The product structure node set is represented by S = (S1, S2, ... S k ,...S j ) indicates that S k represents the kth product structure, SE = (S1-S 1,1 ,...S k -S k,1 ,...S k,1 -S k,1,2... ), . S k -S k,1 , represents the edge between the kth structure and its first substructure, S k,1 -S k,1,2 Represents the edge between the first substructure and its second substructure in the kth structure.

2. The change risk control method of a product multi-domain design information association constraint network model according to claim 1 is characterized in that: The parameter change is determined by the automated parameter matching mechanism or the parameter calculation involving the designer as follows: When changes propagate within the parameter range, the design team determines whether the change requirements exceed the design margin of the parameters, and performs parametric calculations based on the associated constraints to determine which design parameters need to be adjusted and the amount of change in the parameters, and conducts the impact mapping process from parameters to functional structures.

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