CN109190204B - Complex mechanical product module division method based on complex network - Google Patents
Complex mechanical product module division method based on complex network Download PDFInfo
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Abstract
The invention discloses a complex mechanical product module division method based on a complex network, which applies a complex network theory to the complex mechanical product module division, takes parts of complex mechanical products as network nodes, membership among the parts as edges of the network, correlation strength among the parts as edge weights of the network, researches an edge weight quantification method of structure and function relationship strength, and simultaneously adopts a decision-making theory based on mixed fuzzy attributes to calculate the weighted complex network edge weights.
Description
Technical Field
The invention relates to the field of modular design of mechanical products, in particular to a complex mechanical product module division method based on a complex network theory.
Background
Mass-customized production is the mainstream production model in the 21 st century, and the goal is to provide personalized customized products and services for customers mainly at the cost and efficiency of mass production. The modular design is used as a key technology and an important implementation mode for large-scale customization, a series of universal modules are divided by decomposing different products, and then the modules are selected and combined, so that a product customized by a customer is formed. The module division is used as a premise and a basis for researching large-scale customized modular design, and the effective division mode can reduce the life cycle of a product, shorten the development time of the product and fully consider the customized design of a customer; meanwhile, reasonable module division can also provide effective guarantee for modular design and development design for large-scale customization.
At present, many scholars develop relevant researches aiming at a module division technology, but when the existing division method is applied to a complex product system, the problems of large calculation amount and complex division process exist, so that the method is not suitable for module division of complex products. And when the scholars use the complex network to solve the problem of module division, the scholars need to determine the size of the side weight, but the processing problem of some qualitative indexes exists at the moment, and some researchers define the qualitative indexes by simple semantic evaluation of strong, medium and weak, so that a lot of fuzziness and uncertainty exist at the moment, and the scholars are easily influenced by the complexity of objective environment and the specialization level of the decision maker.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide a complex mechanical product module division method based on a complex network theory, which can solve the module division of complex mechanical products, reduce subjectivity and fuzziness existing in the calculation process, has low dependence on the design experience of technicians and can accurately realize the module division of the complex mechanical products.
The invention is realized in the following way:
a complicated mechanical product module partitioning method based on complex network, said method comprises decomposing the given complicated mechanical product into the spare part, and regard spare part of the complicated mechanical product as the network node, the membership between the spare parts is regarded as the edge of the network, the correlation strength among the spare parts is regarded as the edge weight of the network, thus construct the spare part relation network model of the complicated mechanical product; then performing edge weight assignment on the parts and calculating the edge weight of the complex network with the weight; meanwhile, an edge weight quantification method related to the structural and functional relation strength of the product is provided; completing the functional correlation analysis and the structural correlation analysis of the product so as to determine a functional correlation matrix and a structural correlation matrix, and determining the weights of the functions and the structures by an analytic hierarchy process so as to determine a comprehensive correlation matrix of the parts of the product; and finally, realizing module division of the complex mechanical product part weight complex network by adopting a complex network algorithm.
Preferably comprising the steps of:
step one, decomposing a given complex mechanical product into parts to form a part list of the complex mechanical product;
step two, constructing a part relation network model of the complex mechanical product according to the fact that parts of the complex mechanical product are used as network nodes, membership between the parts is used as an edge of a network, and correlation strength between the parts is used as an edge weight of the network;
considering two factors of the structure and the function of the product, respectively adopting interval intuitive fuzzy numbers and intuitive fuzzy numbers to carry out quantitative processing on the function and the structure of the product according to the characteristics of the function and the structure index of the product, and formulating an evaluation standard of the correlation between the structure and the function;
step four, calculating the weight complex network side weight based on a mixed fuzzy attribute decision theory;
step five, completing the functional correlation analysis and the structural correlation analysis of the product, determining a functional correlation matrix and a structural correlation matrix, and further determining a comprehensive correlation matrix of the product parts;
analyzing the comprehensive correlation matrix by adopting a complex network algorithm, thereby realizing the modular division of the complex network of the weight of the parts of the complex mechanical product;
And seventhly, evaluating the division result, selecting an optimal division scheme, and optimizing and adjusting the division scheme correspondingly.
Preferably, the complex network is an undirected weighted complex network.
Preferably, the mixed blur attribute refers to an intuitive blur set and an interval intuitive blur set.
Preferably, the function and structure weight of the product is obtained based on a fuzzy analytic hierarchy process.
Due to the adoption of the technical scheme, compared with the prior art, the invention applies the complex network theory to the module division of the complex mechanical product, takes the parts of the complex mechanical product as network nodes, takes the membership relationship between the parts as the edge of the network, takes the correlation strength between the parts as the edge weight of the network, researches an edge weight quantification method of the structure and function relationship strength, and simultaneously adopts the decision theory based on the mixed fuzzy attribute to calculate the weighted complex network edge weight to construct the part relationship network model of the product based on the edge weight quantification method.
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FIG. 1 is a directed weighted loop-free network of the present invention;
FIG. 2 is a diagram of the correspondence between evaluation semantics and fuzzy sets in the present invention;
FIG. 3 is a schematic diagram of the evaluation criteria for structural relevance in the present invention;
FIG. 4 is a schematic diagram of the evaluation criteria for functional relevance in the present invention;
FIG. 5 is a schematic flow diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments; all other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The embodiment of the invention comprises the following steps:
the detailed description of the implementation and effect of the module partitioning method based on the complex network provided by the invention is as follows:
the specific partitioning method, as shown in fig. 5, includes the following steps:
(1) decomposing a given complex mechanical product into parts to form a part list of the complex mechanical product;
(2) constructing a part relation network model of the complex mechanical product according to the fact that parts of the complex mechanical product are used as network nodes, the membership between the parts is used as an edge of a network, and the correlation strength between the parts is used as an edge weight of the network;
(3) only two factors of the structure and the function of the product are considered, and the function and the structure of the product are quantified by respectively adopting interval intuitive fuzzy numbers and intuitive fuzzy numbers according to the characteristics of the function and the structure index of the product (see figure 2), and an evaluation standard of the correlation between the structure and the function is formulated;
(4) Calculating the edge weight of the weighted complex network based on a mixed fuzzy attribute decision theory;
(5) and (3) completing the functional correlation analysis and the structural correlation analysis of the product (see fig. 3 and 4), determining a functional correlation matrix and a structural correlation matrix, and further determining a comprehensive correlation matrix of the product parts. Let a structural correlation matrix derived from the evaluation criteria be (a)ij)n×nThe function correlation matrix is B ═ Bij)n×nThen the integrated correlation matrix with the product is S ═ waA+wbB; and has wa,wbWeights corresponding to structural and functional dependencies, where wa+wb1, and wa,wb∈[0,1]；
Structural dependence waAnd functional dependency wbThe corresponding weight is obtained by adopting a fuzzy analytic hierarchy process;
(6) analyzing the comprehensive correlation matrix by adopting a complex network algorithm (see the undirected weighted complex network in the figure 1), thereby realizing the module division of the complex network of the complex mechanical product part weight;
(7) and evaluating the partitioning result, selecting the optimal partitioning scheme, and correspondingly optimizing and adjusting the partitioning scheme.
The foregoing embodiments are described in order that those skilled in the art can readily understand and utilize the invention and it is readily apparent that various modifications can be made to the embodiments, and thus, the invention is not limited to the above embodiments, and those skilled in the art can make modifications and variations in the methods of the invention without departing from the scope of the invention.
Claims (3)
1. A complicated mechanical product module division method based on a complicated network is characterized in that: decomposing a given complex mechanical product into parts, taking the parts of the complex mechanical product as network nodes, taking the membership among the parts as the edge of a network, and taking the correlation strength among the parts as the edge weight of the network, thereby constructing a part relation network model of the complex mechanical product; then performing edge weight assignment on the parts and calculating the edge weight of the complex network with the weight; meanwhile, an edge weight quantification method related to the structural and functional relation strength of the product is provided; completing the functional correlation analysis and the structural correlation analysis of the product so as to determine a functional correlation matrix and a structural correlation matrix, and determining the weights of the functions and the structures by an analytic hierarchy process so as to determine a comprehensive correlation matrix of the parts of the product; finally, a complex network algorithm is adopted to realize the module division of the complex network of the weight of the parts of the complex mechanical product;
the method comprises the following steps:
step one, decomposing a given complex mechanical product into parts to form a part list of the complex mechanical product;
step two, constructing a part relation network model of the complex mechanical product according to the fact that parts of the complex mechanical product are used as network nodes, the membership between the parts is used as the edge of the network, and the correlation strength between the parts is used as the edge weight of the network;
Considering two factors of the structure and the function of the product, respectively adopting interval intuitive fuzzy numbers and intuitive fuzzy numbers to carry out quantitative processing on the function and the structure of the product according to the characteristics of the function and the structure index of the product, and formulating an evaluation standard of the correlation between the structure and the function;
calculating the edge weight of the weighted complex network based on a mixed fuzzy attribute decision theory, wherein the mixed fuzzy attribute refers to an intuitionistic fuzzy set and an interval intuitionistic fuzzy set;
step five, completing the functional correlation analysis and the structural correlation analysis of the product, determining a functional correlation matrix and a structural correlation matrix, and further determining a comprehensive correlation matrix of the product parts;
analyzing the comprehensive correlation matrix by adopting a complex network algorithm, thereby realizing the modular division of the complex network of the weight of the parts of the complex mechanical product;
and seventhly, evaluating the division result, selecting an optimal division scheme, and optimizing and adjusting the division scheme correspondingly.
2. The complex mechanical product module division method based on the complex network as claimed in claim 1, wherein: the complex network is an undirected weighted complex network.
3. The complex mechanical product module division method based on the complex network as claimed in claim 1, wherein: the function and structure weight of the product is obtained based on a fuzzy analytic hierarchy process.
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