CN108090280A - The heavy machine tool module partition method that a kind of Oriented Green remanufactures - Google Patents
The heavy machine tool module partition method that a kind of Oriented Green remanufactures Download PDFInfo
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Abstract
The invention discloses the heavy machine tool module partition methods that a kind of Oriented Green remanufactures, belong to Machine Tool design field, and in particular to module partition method and heavy machine tool to heavy machine tool remanufacture technical process.On the basis of Design In Axiomatic Design, being served as theme with four design domains of Design In Axiomatic Design and innovatively being extended to regenerates domain.Consider the difficult point of Remanufacture in advance in the design phase, correlation and similitude of the design parameter between structural domain and regeneration domain are considered using Design Structure Model, preferable heavy machine tool modular design method is sought by the module clustering algorithm based on atomic theory.Using the remanufacturing property for improving lathe, the manufacture cost for reducing lathe as target, so as to extend its seeervice cycle, the competitiveness of enterprise is improved, effectively reduces the consumption of resource.
Description
Technical Field
The invention relates to a heavy machine tool module division method for green remanufacturing, belongs to the field of machine tool design, and particularly relates to a heavy machine tool green remanufacturing process and a module division method.
Background
The machine tool is an important strategic material of the country and is a marking product in the equipment manufacturing industry. Because of large mass, more consumables, high manufacturing energy consumption and high price, the direct scrapping of waste products can cause huge waste of resources and energy. Therefore, how to realize green remanufacturing of the machine tool, so that the old machine tool can generate new activity and prolong the service cycle is an important problem to be solved urgently. In recent years, green remanufacturing, which is a waste product treatment mode more complying with the sustainable development requirement, draws wide attention of the whole society. The green regeneration manufacturing prolongs the service period of the parts through the disassembly, maintenance, replacement, upgrading and the like of the parts, so that the old heavy machine tool can be renewed, and the important ways of saving energy, reducing emission and saving resources are achieved. How to improve the machining precision of numerical control machine tools has become a hot problem for researchers at home and abroad. At present, researchers at home and abroad have done much work in the aspects of machine tool remanufacturing and machine tool module division.
Nakashima et al have studied remanufactured inventory control problems and have proposed an optimal inventory control system. The quality reliability of the reuse of the waste parts is analyzed, judged and researched by Anityasari, and an evaluation model of the residual life is established according to the research result. YDu and the like introduce a machine comprehensive upgrading scheme of machine tool remanufacturing from the aspects of energy conservation, environmental protection, information function and the like, provide a technical path and a technical scheme, and analyze economic benefits and environmental benefits of machine tool remanufacturing.
"Modular design" is a leading-edge design concept and design methodology. The design method is provided for improving the design efficiency, so that the design experience can be transmitted and inherited, and the design and production level can be further improved. The method has the characteristic that units with certain functions and related elements which are interchangeable are combined to form a product, and emphasizes that modules with different functions or the same functions but different performances are combined and interchanged to form various universal and deformable products based on function analysis and market prediction as guidance, so that the product series has great adaptability. The module division is an important content of modular design, and the module construction can be carried out according to different division methods. Erixon and the like decompose product functions to obtain a plurality of small sub-functions, and a general principle of module division is provided for judging whether the sub-functions can become independent modules or not, and clustering functional units by analyzing the product sub-functions. Stone et al presents a heuristic approach that creates modules based on the functionality of the product. Some scholars consider the life cycle factors of the product in the study. Umeda and the like consider life cycle factors of products from the perspective of multiple targets, and evaluate the quality of module division by a quantitative method on the basis of fuzzy mathematical theory. The modular design method has the obvious advantages of meeting the requirements of users on various varieties, shortening the design period and ensuring that enterprises obtain initiative in market competition.
In order to improve design efficiency and reduce complexity, modular design has been widely used in mass production of machine tools, especially large gantry machining centers. In order to improve the remanufacturing capacity of the heavy machine tool, the division standard of the modules not only concerns the functional integrity and the structural rationality, but also predicts the potential remanufacturing requirements in advance, and considers the manufacturing resources, the remanufacturing process difference and the remanufacturing environment. How to consider the difficulty and bottleneck of remanufacturing in advance in the design stage so as to improve the green remanufacturing capability of the remanufacturing machine still has a plurality of contents to be deeply researched. In order to improve the green remanufacturing capability of the heavy machine tool, a heavy machine tool module dividing method for green remanufacturing is provided, and aims to improve the remanufacturing performance of the machine tool and reduce the manufacturing cost of the machine tool, so that the service cycle of the machine tool is prolonged, the competitiveness of an enterprise is improved, and the consumption of resources is effectively reduced.
Disclosure of Invention
The invention aims to provide a heavy machine tool module dividing method facing green remanufacturing, which takes four design domains of an axiom design as main lines and innovatively extends the design domains to a regeneration domain through the axiom design theory, as shown in FIG. 1. On the basis of the functions of the heavy machine tool, a design matrix between a lifting type machine tool structural domain and a regeneration domain is established in the design stage, the design matrix is quantitatively analyzed according to a two-way fuzzy analytic hierarchy process, and the design matrix is converted into the design structural matrix with design parameters considered from the remanufacturing perspective through a quantity product method. And analyzing the interactive relation among the design parameters from the assembly angle, the form and position angle and the physical angle in the structural domain of the heavy machine tool to construct a structure-oriented design parameter correlation design structural matrix. In order to improve the remanufacturing processing and production efficiency of the modular heavy-duty machine tool, a similarity design structure matrix of the remanufacturing technological process of the design parameters of the heavy-duty machine tool is established based on a similarity principle. And weighting and combining the obtained design parameter correlation matrix and the similarity matrix to obtain an interactive relation matrix which is represented by a design structure matrix and comprehensively considered from the aspects of structure and regeneration, thereby providing basis and guarantee for reasonable module division. And finally, analyzing the obtained design structure matrix by using a modular clustering algorithm based on the atomic theory to realize modular division of the heavy machine tool. The effectiveness of the method provided by the invention is proved by taking a heavy planer type milling machine as an example, and the invention can be used for carrying out module division on the heavy machine tool.
In order to achieve the purpose, the technical scheme adopted by the invention is a heavy machine tool module division method for green remanufacturing, which is used for solving the remanufacturing technical problem of a heavy machine tool in the design stage. The method is implemented as follows.
Step one, establishing a remanufacturing correlation design structure matrix of design parameters of the heavy machine tool
According to the rationale design theory basic principle, expressing the relation between the design parameters of the heavy machine tool in a matrix form; and establishing a correlation matrix of the design parameters of the hoisting type machine tool through quantitative analysis of the design matrix and the actual structure of the heavy machine tool.
Step 1.1 Structure drawing of machine tool
And establishing a three-dimensional structure model of the heavy planer type milling machine.
Step 1.2 establishing a reproduction domain-oriented design parameter remanufacturing correlation design structure matrix
Step 1.2.1 axiomatic design based Domain and regenerative Domain decomposition
Applying a design framework provided by an axiom design, adopting zigzag hierarchical mapping, starting from a functional domain, establishing a hierarchical structure between a structural domain and a regeneration domain layer by layer, and describing the relationship between design parameters and a remanufacturing process in the form of a formula (1):
DP＝[A]RP (1)
wherein n and m respectively represent design parameters and the number of remanufacturing processes corresponding to the design parameters. Designing element A in matrix A ij The relationship of the design parameters and the remanufacturing process is described in the binary form "X" and "0". The preliminarily obtained design matrix only indicates whether the corresponding relationship exists between the design parameters and the remanufacturing process, no specific numerical value exists, the information contained in the design matrix is too little, and the corresponding relationship between the design parameters and the remanufacturing process parameters needs to be quantized in order to describe the corresponding relationship more clearly.
Step 1.2.2 design matrix quantization method based on two-way fuzzy analytic hierarchy process
(1) A judgment matrix as shown in table 1 was constructed with the design parameters as references, and the contribution of the relevant remanufacturing process to the design parameters was evaluated.
TABLE 1 arbitrary design parameters DP s Comparison matrix as reference
Aiming at the comparison matrix, the following relations are satisfied, i is a row mark of the matrix, and j is a column mark of the matrix;
i, j =1,2, \ 8230;, n and i = j;
i, j =1,2, \8230nand i ≠ j;
for judging the matrix scale, the meaning is shown in Table 2
Table 2 decision matrix elementsEvaluation criterion of
(2) Calculating the matrix eigenvalue and the corresponding eigenvector obtained in the step (1), after consistency check, standardizing the eigenvector corresponding to the maximum eigenvalue to obtain weight vectors, and arranging the weight vectors in rows to obtain a weight matrix W x 。
(3) The decision matrix shown in Table 3 was constructed based on the remanufacturing process, the elements of whichThe value is taken in the same wayEvaluating design parameters is affected by the associated remanufacturing process.
TABLE 3 optional remanufacturing process RP s Comparison matrix as reference
(4) Calculating the matrix characteristic value obtained in the step (3)And after consistency check, carrying out standardization processing on the eigenvector corresponding to the maximum eigenvalue to obtain weight vectors, and arranging the weight vectors according to columns to obtain a weight matrix W y 。
(5)W x And W y The design matrix is quantized from two angles respectively, and W is calculated x And W y Geometric mean ofA comprehensive design matrix quantization result is obtained.
(6) And setting the diagonal elements of the design matrix as 1, filling the rest of the diagonal elements into 0, and filling the diagonal elements and the quantized result into the design matrix at the same time to obtain the whole quantized design matrix.
Step 1.2.3 converting the quantized design matrix into a design structure matrix
The quantized design matrix is constructed by using a quantity product method in fuzzy mathematics, and the process is shown in formula (2)
Wherein the content of the first and second substances,obtaining the remanufacturing-process-based design structure matrix DSM of the design parameters of the heavy machine tool for the remanufacturing-oriented relevance of the design parameters i and j RP 。
Step 1.3, establishing a structural correlation design structure matrix of the design parameters of the heavy machine tool
In the remanufacturing-oriented process, the difficulty degree of loading and unloading among design parameters is mainly considered, so that the requirements of a customer on disassembling, maintaining and replacing related parts of a machine tool are met, and the use efficiency is improved. Meanwhile, strict position relation exists among design parameters, and the design parameters have form and position correlation. In addition, functional interactions among design parameters are often expressed in physically related forms of materials, energy, information, and the like. To summarize, the structural correlation between design parameters is mainly classified into assembly correlation, form and position correlation, and assembly correlation.
Assembly dependencies are physical couplings, fastenings, dimensions, fits, etc. in terms of space, geometric relationships between the parts that make up a particular module. The main means is a relation formed by combining the parts by welding, bonding, riveting and other connecting methods in the assembling process. Table 4 describes the evaluation criteria of the design parameter assembly correlation.
TABLE 4 design parameter Assemble correlation criteria and assignments
The form and position correlation refers to a position relationship of parts with strict requirements on perpendicularity, parallelism and the like among specific geometric elements. Table 5 describes evaluation criteria of the correlation of the form and position of the design parameters.
TABLE 5 design parameters form and position correlation criteria and assignments
The physical correlation refers to the existence of physical relationships between components, such as the transmission of energy flow, information flow or material flow. Wherein, the energy flow refers to the driving force, torque, power, current or hydraulic pressure transmitted between the parts; the information flow is the transmission of optical, electrical and other information transmitted by the parts; the material flow refers to materials, workpieces and the like transferred between parts. Table 6 shows the physical correlation evaluation indexes of the specific module components.
TABLE 6 design parameter physical correlation criteria and assignments
To heavy machine toolAnalyzing the assembly relationship, the form and position relationship and the physical relationship among the design parameters, formulating the evaluation criteria of the design parameter assembly correlation, the form and position correlation and the physical correlation, and establishing the assembly correlation DSM of the heavy machine tool design parameters according to the correlation criteria Assy Form and position correlation DSM geo And physical correlation DSM phy Then the structural dependence DSM of the design parameters of the heavy-duty machine tool str Obtained by the following formula.
DSM str ＝w Assy DSM Assy +w geo DSM geo +w phy DSM phy (3)
Wherein w Assy 、w geo And w phy Weights representing the assembly correlation, form and position correlation and physical correlation, respectively, can be determined according to an analytic hierarchy process. The importance determination matrix is shown in Table 7, and its determination matrix element c ij The assigned scoring criteria of (a) are shown in table 2.
TABLE 7 structural correlation weight decision matrix table
Step 1.4 Total correlation of design parameters DSM
DSM RP And DSM str The correlation between the design parameters of the heavy machine tool is expressed in terms of remanufacturing process and structure, respectively. At this stage, the overall correlation between design parameters is defined as follows:
DSM cor ＝w str DSM str +w RP DSM RP (4)
in the formula w str And w RP And respectively representing different weight values of the structural correlation degree and the remanufacturing correlation degree in the total correlation degree, and specifically and similarly determining according to an analytic hierarchy process.
Step two, establishing a remanufacturing process similarity design structure matrix of the design parameters of the heavy machine tool
Step 2.1 of establishing a remanufacturing process route string corresponding to each design parameter of the heavy machine tool
Assuming that an incidence matrix corresponding to the design parameters of the heavy-duty machine tool and the remanufacturing process route is T, elements in the matrix are T (I, J), I belongs to I, J belongs to J, wherein I is a design parameter set in the heavy-duty machine tool, J is a remanufacturing process link set, and each element T (I, J) in the matrix represents whether the remanufacturing process route of the design parameters of the heavy-duty machine tool contains a corresponding process link or not through a Boolean value {0,1}, so that a remanufacturing process route string corresponding to each design parameter can be established.
Step 2.2, establishing a remanufacturing process similarity design structure matrix of the design parameters of the heavy machine tool
Through the corresponding incidence matrix of the design parameters of the heavy machine tool and the remanufacturing process route string, a similarity design structure matrix DSM between different design parameters of the remanufacturing process route can be established sim Element DSM in its matrix sim (i, j) can be determined by the following equation (5) according to the semblance measure method
Wherein k and l are the number of processes in the remanufacturing process route string of the design parameters i and j of the heavy machine tool; n is the number of processes with similar design parameters; s is ij The similar characteristic value proportionality coefficient of the jth similar process is between 0 and 1; w is a j Is the weight coefficient of the jth similar process, which can be determined by an analytic hierarchy process, and 0<w j <1,∑w j ＝1.
Step three, establishing a total interactive design structure matrix of the design parameters of the heavy machine tool
Through the analysis, the correlation design structure matrix of the design parameters of the heavy machine tool and the similarity design structure matrix of the remanufacturing process are obtained, and the correlation design structure matrix and the similarity design structure matrix are both n x n dimensional matrices on the assumption that the inter-domain hierarchical decomposition based on the axiom design results in n bottom layer design parameters of the product.
A module is made up of many components that have minimal correlation and similarity to other components outside the module. For module division, the correlation and the similarity have the same preference attribute, and in order to obtain a more reasonable analysis result, a preference aggregation method is adopted to aggregate two indexes
In the formula, DSM int The interactive relation values among the design parameters are comprehensively reflected. w is a cor 、w sim Different weight values representing relevance and similarity, respectively. Mu is a standard of compensation level, and the larger the value of mu is, the greater the preference of one attribute index is. d cor 、d sim Respectively, the correlation and similarity values to be clustered. Each weight can be determined by the above-described analytic hierarchy process.
Step four, clustering modules based on the theory of atoms
Module clustering is a complex comprehensive optimization process with a plurality of influencing factors. The clustering algorithm based on the atomic theory aims to solve the problem of remanufacturing-oriented module division of the heavy gantry machine tool. The clustering algorithm based on the atomic theory is proposed by Smith at 2010, and the clustering result is faster and more reasonable. An atom consists of a positively charged nucleus and a number of negatively charged electrons. The method is characterized in that a module in the heavy gantry machine tool is simulated into an atom by using an atomic theory, design parameters with a plurality of interactivity among the design parameters are defined as a positively charged atomic nucleus, and design parameters with interactivity with the design parameters are defined as negatively charged electrons. And calculating the charge quantity carried by each design parameter, and establishing a distance matrix between the design parameters. And (4) obtaining a coulomb force matrix among the design parameters of the heavy machine tool as shown in the formula (7), extracting the maximum value of each row in the coulomb force matrix, establishing a maximum coulomb force matrix which represents the maximum attractive force between one electron and one atomic nucleus, and forming a module of a product by dividing the design parameters with the same maximum coulomb force together.
The invention will be further understood from the foregoing description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the method and practice of the invention.
Drawings
Figure 1 axiom design theory.
FIG. 2 shows a system for evaluating structural correlation of parameters.
FIG. 3 is a design matrix between DP-RP of a heavy gantry milling machine.
FIG. 4 is a design matrix (quantization) between the DP-RP of the heavy gantry milling machine.
A structural matrix is designed between DP-RP of the heavy gantry milling machine in figure 5.
FIG. 6 is a structural matrix of heavy planer milling machine assembly correlation design.
Figure 7 is a structural matrix designed according to the shape and position correlation of the heavy planer type milling machine.
Figure 8 is a structural matrix designed according to physical correlation of the heavy planer type milling machine.
FIG. 9 is a structural matrix of heavy planer milling machine structural correlation design.
FIG. 10 is a structural matrix of heavy planer milling machine total correlation design.
Figure 11 heavy planer milling machine remanufacturing process route string.
Figure 12 heavy planer milling machine remanufacturing process similarity design structural matrix.
FIG. 13 is a total interaction matrix of design parameters for a heavy planer milling machine.
FIG. 14 is a flow chart of an embodiment of the method of the present invention.
Detailed Description
In order to realize remanufacturing-oriented module division of the heavy machine tool, the module division method is verified by taking a heavy planer type milling machine of a certain model as an example.
The specific implementation steps are as follows:
step one, establishing a remanufacturing correlation design structure matrix of design parameters of the heavy machine tool
According to the basic principle of a axiom design theory, the relationship between the design parameters of the heavy machine tool is expressed in a matrix form; and establishing a correlation matrix of the design parameters of the hoisting type machine tool through quantitative analysis of the design matrix and the actual structure of the heavy machine tool. Step 1.1 machine tool Structure
In this study, a three-dimensional structural model of a heavy planer milling machine.
Step 1.2 of establishing a reproduction domain-oriented design parameter remanufacturing correlation design structure matrix
Step 1.2.1 axiomatic design based Domain and regenerative Domain decomposition
Applying a design framework provided by an axiom design, adopting zigzag hierarchical mapping, starting from a functional domain, establishing a hierarchical structure between a structural domain and a regeneration domain layer by layer, and describing the relationship between design parameters and a remanufacturing process in the form of a formula (8):
DP＝[A]RP (8)
wherein n and m respectively represent design parameters and the number of remanufacturing processes corresponding to the design parameters. Designing element A in matrix A ij The relationship of the design parameters and the remanufacturing process is described in the binary form "X" and "0".
The functional requirement level decomposition table of the heavy planer type milling machine is given by table 8, and based on the character type level mapping of the axiom design theory, a level decomposition table of the design parameters of the heavy planer type milling machine and a level decomposition table facing the remanufacturing process are obtained, as shown in tables 9 and 10. A design matrix between the structural and regeneration domains may be established from a hierarchical decomposition table of design parameters and the remanufacturing process as shown in figure 3.
Table 8 function requirement level decomposition table for heavy planer type milling machine
Table 9 design parameter level decomposition table for heavy planer type milling machine
TABLE 10 layer decomposition table for remanufacturing process of heavy planer type milling machine
Step 1.2.2 design matrix quantization method based on two-way fuzzy analytic hierarchy process
The preliminarily obtained design matrix only indicates whether there is a corresponding relationship between the design parameters and the remanufacturing process, and there is no specific numerical value, and the information contained in the design matrix is too little, so that the corresponding relationship between the design parameters and the remanufacturing process parameters needs to be quantized in order to describe more clearly.
(1) A judgment matrix shown in table 11 was constructed with the design parameters as references, and the contribution of the relevant remanufacturing process to the design parameters was evaluated.
TABLE 11 arbitrary design parameters DP s Comparison matrix for reference
For the above comparison matrix, the following relationship should be satisfied
i, j =1,2, \ 8230;, n and i = j;
i, j =1,2, \8230nand i ≠ j;
for judging the matrix scale, the meaning is shown in Table 12
Table 12 decision matrix elementsEvaluation criterion of
(2) Calculating the matrix characteristic values and the corresponding characteristic vectors obtained in the step (1), after consistency check is carried out, carrying out standardization processing on the characteristic vectors corresponding to the maximum characteristic values to obtain weight vectors, and arranging the weight vectors in rows to obtain a weight matrix W x 。
(3) The decision matrix shown in Table 13 was constructed based on the remanufacturing process, the elements of whichThe value is taken in the same wayEvaluating design parameters is affected by the associated remanufacturing process.
TABLE 13 Reproductions Process RP s Comparison matrix as reference
(4) Calculating the matrix characteristic values and the corresponding characteristic vectors obtained in the step (3), after consistency check is carried out, carrying out standardization processing on the characteristic vectors corresponding to the maximum characteristic values to obtain weight vectors, and arranging the weight vectors in columns to obtain a weight matrix W y 。
(5)W x And W y The design matrix is quantized from two angles respectively, and W is calculated x And W y Geometric mean value ofA comprehensive design matrix quantization result is obtained.
(6) And setting the diagonal elements of the design matrix as 1, filling the rest of the diagonal elements into 0, and filling the diagonal elements and the quantized result into the design matrix at the same time to obtain the whole quantized design matrix.
The design matrix is subjected to quantitative analysis by adopting the two-way fuzzy analytic hierarchy process introduced by the invention, is limited to space, omits each judgment matrix, and directly provides the quantized design matrix as shown in figure 4.
Step 1.2.3 converting the quantized design matrix into a design structure matrix
The quantized design matrix is constructed by using the number product method in fuzzy mathematics, and the process is shown in formula (9)
Wherein the content of the first and second substances,obtaining the remanufacturing-process-based design structure matrix DSM of the design parameters of the heavy machine tool for the remanufacturing-oriented relevance of the design parameters i and j RP . The design matrix is transformed into a design structure matrix, and the transformation result is shown in fig. 5.
Step 1.3, establishing a structural correlation design structure matrix of the design parameters of the heavy machine tool
In the remanufacturing-oriented process, the difficulty degree of loading and unloading among design parameters is mainly considered, so that the requirements of a customer on disassembling, maintaining and replacing related parts of a machine tool are met, and the use efficiency is improved. Meanwhile, strict position relation exists among design parameters, and the design parameters have form and position correlation. In addition, functional interactions among design parameters are often expressed in physically related forms of materials, energy, information, and the like. In summary, as shown in fig. 2, the structural correlation between design parameters is mainly classified into assembly correlation, form and position correlation, and assembly correlation.
Assembly dependencies are physical couplings, fastenings, dimensions, fits, etc. in terms of space, geometric relationships between the parts that make up a particular module. The main means is a relation formed by combining the parts by welding, bonding, riveting and other connecting methods in the assembling process. Table 14 describes evaluation criteria of the design parameter assembly correlation.
TABLE 14 design parameter Assemble dependency criteria and assignments
The form and position correlation refers to a position relationship of parts with strict requirements on perpendicularity, parallelism and the like among specific geometric elements. Table 15 describes evaluation criteria for the form and position dependence of the design parameters.
TABLE 15 design parameters form and location correlation criteria and assignments
The physical correlation refers to the existence of physical relationships between components, such as the transmission of energy flow, information flow or material flow. Wherein, the energy flow refers to the driving force, torque, power, current or hydraulic pressure transmitted between the parts; the information flow is the transmission of optical, electrical and other information transmitted by the parts; the material flow refers to materials, workpieces and the like transferred between parts. Table 16 shows the physical correlation evaluation indexes of the specific module components.
TABLE 16 design parameters physical correlation criteria and assignments
Analyzing the assembly relationship, the form and position relationship and the physical relationship among the design parameters of the heavy machine tool, formulating the evaluation criteria of the assembly correlation, the form and position correlation and the physical correlation of the design parameters, and establishing the assembly correlation DSM of the design parameters of the heavy machine tool according to the correlation criteria Assy Form and position correlation DSM geo And physical correlation DSM phy Then the structural dependence DSM of the design parameters of the heavy-duty machine tool str Can be obtained by the following formula.
DSM str ＝w Assy DSM Assy +w geo DSM geo +w phy DSM phy (10)
Wherein, w Assy 、w geo And w phy Weights representing the assembly correlation, form and position correlation and physical correlation, respectively, can be determined according to an analytic hierarchy process. The importance determination matrix table is shown in Table 17, and its determination matrix element c ij The assigned scoring criteria of (a) are shown in table 12.
Table 17 structural correlation weight judgment matrix table
According to the actual assembly relationship, the form and position relationship and the physical relationship among the parts of the heavy planer type milling machine, according to the method, the assembly correlation, the form and position correlation and the physical correlation of the heavy planer type milling machine are respectively established to design a structural matrix, as shown in figures 6, 7 and 8. According to the formula (10), a structural correlation design structural matrix of the heavy planer type milling machine can be obtained, as shown in fig. 9.
Step 1.4 Total correlation of design parameters DSM
DSM RP And DSM str The correlation between the heavy machine design parameters is expressed from a remanufacturing process and structure perspective, respectively. At this stage, the overall correlation of the design parameters is defined as follows:
DSM cor ＝w str DSM str +w RP DSM RP (11)
in the formula w str And w RP The different weight values of the structural correlation degree and the remanufacturing correlation degree in the total correlation degree are respectively represented, and the weight values can be determined according to an analytic hierarchy process. The overall correlation design structure matrix is shown in fig. 10.
Step two, establishing a remanufacturing process similarity design structure matrix of the design parameters of the heavy machine tool
Step 2.1 of establishing a remanufacturing process route string corresponding to each design parameter of the heavy machine tool
Assuming that an incidence matrix corresponding to the design parameters of the heavy-duty machine tool and the remanufacturing process route is T, elements in the matrix are T (I, J), I belongs to I, J belongs to J, wherein I is a design parameter set in the heavy-duty machine tool, J is a remanufacturing process link set, and each element T (I, J) in the matrix represents whether the remanufacturing process route of the design parameters of the heavy-duty machine tool contains a corresponding process link or not through a Boolean value {0,1}, so that a remanufacturing process route string corresponding to each design parameter can be established. The process involved in the remanufacturing process of each part of the heavy planer type milling machine was first numbered as shown in table 18. And then obtaining a remanufacturing process route string of each part of the heavy planer type milling machine shown in the figure 11.
Remanufacturing process of table 18 heavy planer type milling machine
Step 2.2, establishing a remanufacturing process similarity design structure matrix of the design parameters of the heavy machine tool
Through the corresponding relation matrix of the design parameters of the heavy machine tool and the remanufacturing process route string, a similarity design structure matrix DSM between different design parameters of the remanufacturing process route can be established sim Element DSM in its matrix sim (i, j) can be determined by the following equation (12) according to the semblance measure method
Wherein k and l are the number of processes in the remanufacturing process route string of the design parameters i and j of the heavy machine tool; n is the number of processes with similar design parameters; s ij The similar characteristic value proportion coefficient of the jth similar process can be between 0 and 1; w is a j Is the weight coefficient of the jth similar process, which can be determined by an analytic hierarchy process, and 0<w j <1,∑w j ＝1.
From this, a structural matrix can be designed based on the similarity of the remanufacturing process for the design parameters of the heavy planer type milling machine, as shown in fig. 13.
Step three, establishing a total interactive design structure matrix of design parameters of the heavy machine tool
Through the analysis, the correlation design structure matrix of the design parameters of the heavy machine tool and the similarity design structure matrix of the remanufacturing process are obtained, and the correlation design structure matrix and the similarity design structure matrix are both n x n dimensional matrixes assuming that the inter-domain hierarchical decomposition based on the axiom design and the products have n bottom layer design parameters in total.
A module is made up of many components that have minimal correlation and similarity to other components outside the module. For module division, the correlation and the similarity have the same preference attribute, and in order to obtain a more reasonable analysis result, a preference aggregation method is adopted to aggregate two indexes
In the formula, DSM int The interactive relation values among the design parameters are comprehensively reflected. w is a cor 、w sim Different weight values representing relevance and similarity, respectively. Mu is a standard of compensation level, and the larger the value of mu is, the greater the preference of one attribute index is. d cor 、d sim Respectively, the correlation and similarity values to be clustered. Each weight may be determined by the above-described analytic hierarchy process.
And (3) a total interaction relation matrix of the design parameters of the heavy planomiller, as shown in figure 13.
Step four, clustering modules based on the theory of atoms
An atom consists of a positively charged nucleus and a number of negatively charged electrons. The method is characterized in that a module in the heavy gantry machine tool is simulated into an atom by using an atomic theory, design parameters with a plurality of interactivity among the design parameters are defined as a positively charged atomic nucleus, and design parameters with interactivity with the design parameters are defined as negatively charged electrons. And calculating the charge quantity carried by each design parameter, and establishing a distance matrix between the design parameters.
And establishing a correlation matrix M between the design parameters based on the total interaction matrix between the design parameters of the heavy planer type milling machine, so as to describe whether the two design parameters are correlated or not. The association matrix establishment criteria are shown in table 19.
TABLE 19 Association matrix establishment criteria
Summing each row of the correlation matrix, and determining the minimum number of design parameters of the electronic components associated with the kernel based on the number of modules required. The more modules that are needed, the larger the defined minimum number. Assuming that the minimum number is α, a matrix Q describing the amount of charge carried by the design parameters is established, and the establishment criterion of the charge amount matrix Q is shown in equation (14).
Wherein, TM i A is the minimum number, summed for each row of the correlation matrix; q i Is the amount of charge carried by the design parameter.
Based on the total interaction matrix, a distance matrix D describing the size of the interval between the design parameters is established, the higher the correlation between every two elements is, the smaller the distance is, and according to the quantization values of the elements in the total interaction matrix, the matrix D is established, and the distance matrix value criterion is shown in table 20.
TABLE 20 design parameters distance matrix establishment criteria
A coulomb force matrix F is established according to equation (15) to describe the magnitude of the attractive or repulsive force between each design parameter. In order to make formula (15) better applicable to the present method, it is modified accordingly, as shown in formula (16), by adding a negative sign before the coulomb number, when Q i 、Q j Coulomb force F with the same sign ij Less than 0, when Q i 、Q j Coulomb force F with opposite signs ij Is 0 a greater.
In the formula F ij Is the coulomb force between the design parameters i and j; q i 、Q j The amount of charge carried is the design parameters i and j; d ij Is the distance between the design parameters i and j; k is a coulomb constant, which generally takes 1, but when two or more nuclei have the same charge number after the nuclei are determined, for better module differentiation, the coulomb constants of the nuclei with the same charge number take values from 1, the first one takes k =1, the second one takes k =2, the third one takes k =3, and so on, when calculating coulomb force. The value of the coulomb constant k does not influence the division result.
After the Coulomb force matrix F is obtained, the maximum value of each row in the matrix F is extracted to establish the maximum Coulomb force matrix MF which represents the maximum attractive force between an electron and an atomic nucleus, MF i ＝max(F ij ). All electrons attracted by each nucleus can be found by the maximum coulomb force matrix. Since nuclei with the same charge have different k values, the maximum coulomb force associated with each nucleus is different. Thus, a module of a product can be formed by grouping together design parameters having the same maximum coulomb force. Table 21 gives the final partitioning results.
TABLE 21 results of modular division for heavy planer milling machine
According to the traditional module division, a motor and a lead screw form a transmission module, each guide rail forms a guide module, and a lathe bed, a cross beam and a gantry frame form a support module, so that the interchangeability of the modules is improved in the aspect of functions of the formed modules, and the modules are convenient to assemble, transport and store in the aspect of structures. According to the invention, on the basis of considering remanufacturing factors, a beam, a slide carriage, a Y-axis ball screw and a Y-axis guide rail form a beam module, a gantry frame, a lathe bed, a slide carriage, an X-axis ball screw and an X-axis guide rail form a lathe bed and a movable gantry module, and a ram, a Z-axis ball screw and a Z-axis guide rail form a ram module. The dividing mode reflects structural relevance factors, and reflects the dividing rationality in the angle of the remanufacturing process, for example, the lead screw, the guide rail and the structural part are divided into the same module, so that the uniform size change and the re-assembly remanufacturing operation among the structural part, the lead screw and the guide rail are facilitated. The workbench module and the spindle module mainly reflect the correlation of internal design parameters structurally. The transmission module and the auxiliary protection module mainly provide division basis by the similarity of remanufacturing processes. Therefore, the division of each module meets the requirement of active remanufacturing design of each stage of each life cycle of the heavy gantry machine tool, and meanwhile, the correlation of design parameters in a structural domain and a regeneration domain and the similarity of the design parameters based on the remanufacturing process are considered.
Claims (1)
1. The utility model provides a heavy lathe module division method towards green refabrication which characterized in that: the implementation process of the method is as follows,
step one, establishing a remanufacturing correlation design structure matrix of design parameters of the heavy machine tool
According to the rationale design theory basic principle, expressing the relation between the design parameters of the heavy machine tool in a matrix form; establishing a correlation matrix of the design parameters of the lifting type machine tool through quantitative analysis of the design matrix and the actual structure of the heavy machine tool;
step 1.1 machine tool Structure
Establishing a three-dimensional structure model of a heavy planer type milling machine;
step 1.2 of establishing a reproduction domain-oriented design parameter remanufacturing correlation design structure matrix
Step 1.2.1 axiomatic design based Domain and regenerative Domain decomposition
Applying a design framework provided by an axiom design, adopting zigzag hierarchical mapping, starting from a functional domain, establishing a hierarchical structure between a structural domain and a regeneration domain layer by layer, and describing the relationship between design parameters and a remanufacturing process in the form of a formula (1):
DP＝[A]RP (1)
n and m respectively represent design parameters and the number of remanufacturing processes corresponding to the design parameters; designing element A in matrix A ij The relationship of design parameters and remanufacturing process is described in binary shapes "X" and "0"; the preliminarily obtained design matrix only shows whether the corresponding relation exists between the design parameters and the remanufacturing process, no specific numerical value exists, the information contained in the design matrix is too little, and the corresponding relation between the design parameters and the parameters of the remanufacturing process needs to be quantized in order to describe the corresponding relation more clearly;
step 1.2.2 design matrix quantization method based on bidirectional fuzzy analytic hierarchy process
(1) Constructing a judgment matrix shown in table 1 by taking the design parameters as a reference, and evaluating the contribution of the relevant remanufacturing process to the design parameters;
TABLE 1 arbitrary design parameters DP s Comparison matrix as reference
Aiming at the comparison matrix, the following relations are satisfied, i is a row mark of the matrix, and j is a column mark of the matrix;
i, j =1,2, \ 8230;, n and i = j;
i，j =1,2, \8230, n and i ≠ j;
for judging the matrix scale, the meaning is shown in Table 2
Table 2 judgment matrix elementsValue assignment criteria of
(2) Calculating the matrix eigenvalue and the corresponding eigenvector obtained in the step (1), after consistency check, standardizing the eigenvector corresponding to the maximum eigenvalue to obtain weight vectors, and arranging the weight vectors in rows to obtain a weight matrix W x ；
(3) The decision matrix shown in Table 3 was constructed based on the remanufacturing process, the elements of whichThe value is taken in the same wayEvaluating the influence of design parameters on related remanufacturing processes;
TABLE 3 optional remanufacturing process RP s Comparison matrix as reference
(4) Calculating the matrix eigenvalue and the corresponding eigenvector obtained in the step (3), after consistency check, standardizing the eigenvector corresponding to the maximum eigenvalue to obtain weight vectors, and arranging the weight vectors in columns to obtain a weight matrix W y ；
(5)W x And W y The design matrix is quantized from two angles respectively, and W is calculated x And W y Geometric mean ofObtaining a quantization result of a comprehensive design matrix;
(6) Setting diagonal elements of the design matrix as 1, filling the rest of diagonal elements and quantized results into the design matrix to obtain a whole quantized design matrix;
step 1.2.3 converting the quantized design matrix into a design structure matrix
The quantified design matrix is constructed by using a quantity product method in fuzzy mathematics, and the process is shown as a formula (2)
Wherein, the first and the second end of the pipe are connected with each other, obtaining the remanufacturing-process-based design structure matrix DSM of the design parameters of the heavy machine tool for the remanufacturing-oriented relevance of the design parameters i and j RP ；
Step 1.3, establishing a structural correlation design structure matrix of the design parameters of the heavy machine tool
In the remanufacturing-oriented process, the difficulty degree of loading and unloading among design parameters is mainly considered so as to meet the requirements of a customer on disassembling, maintaining and replacing related parts of the machine tool and improve the use efficiency; meanwhile, strict position relation exists among design parameters, and the design parameters have form and position correlation; in addition, functional interaction among design parameters is usually expressed in a physically related form of materials, energy and information; summarizing, the structural correlation among the design parameters is mainly divided into assembly correlation, form and position correlation and assembly correlation; the assembly dependency is the physical coupling, fastening, sizing, fitting relationship in space, geometric relationship between the parts that make up a particular module; a relationship between the component parts formed by welding, bonding, riveting, and joining them together during assembly; table 4 describes evaluation criteria of the design parameter assembly correlation;
TABLE 4 design parameter Assemble correlation criteria and assignments
The form and position correlation refers to a position relation of parts with strict requirements on perpendicularity and parallelism among specific geometric elements; table 5 describes evaluation criteria for the form and position correlation of the design parameters;
TABLE 5 design parameters form and position correlation criteria and assignments
The physical correlation refers to the transmission physical relationship of energy flow, information flow or material flow among parts; wherein, the energy flow refers to the driving force, torque, power, current or hydraulic pressure transmitted between parts; the information flow is the transmission of optical and electric information transmitted by parts; the material flow refers to materials and workpieces transferred among parts; the physical correlation evaluation indexes among the components constituting the specific module are shown in table 6;
TABLE 6 design parameter physical correlation criteria and assignments
Analyzing the assembly relationship, the form and position relationship and the physical relationship among the design parameters of the heavy machine tool, and formulating the assembly correlation, the form and position correlation and the physical correlation of the design parametersAccording to the correlation criterion, establishing an assembly correlation DSM of the design parameters of the heavy machine tool Assy Form and position correlation DSM geo And physical correlation DSM phy Then the structure dependence DSM of the design parameters of the heavy-duty machine tool str Can be obtained by the following formula;
DSM str ＝w Assy DSM Assy +w geo DSM geo +w phy DSM phy (3)
wherein w Assy 、w geo And w phy Weights respectively representing the assembly correlation shape and position correlation and the physical correlation can be determined according to an analytic hierarchy process; the importance determination matrix is shown in Table 7, and its determination matrix element c ij The assigned score criteria of (3) are shown in table 2;
TABLE 7 structural correlation weight determination matrix table
Step 1.4 Total correlation of design parameters DSM
DSM RP And DSM str The correlation between the design parameters of the heavy machine tool is expressed from the aspects of remanufacturing process and structure respectively;
at this stage, the overall correlation between design parameters is defined as follows:
DSM cor ＝w str DSM str +w RP DSM RP (4)
in the formula w str And w RP Respectively representing different weight values of the structural correlation degree and the remanufacturing correlation degree in the total correlation degree, and specifically determining according to an analytic hierarchy process;
step two, establishing a remanufacturing process similarity design structure matrix of the design parameters of the heavy machine tool
Step 2.1, establishing remanufacturing process route strings corresponding to each design parameter of the heavy-duty machine tool
Assuming that an incidence matrix corresponding to the design parameters of the heavy-duty machine tool and the remanufacturing process route is T, elements in the matrix are T (I, J), I belongs to I, J belongs to J, wherein I is a design parameter set in the heavy-duty machine tool, J is a remanufacturing process link set, and each element T (I, J) in the matrix represents whether the remanufacturing process route of the design parameters of the heavy-duty machine tool contains a corresponding process link or not through a Boolean value {0,1}, so that a remanufacturing process route string corresponding to each design parameter can be established;
step 2.2, establishing a remanufacturing process similarity design structure matrix of the design parameters of the heavy machine tool
Through the corresponding incidence matrix of the design parameters of the heavy machine tool and the remanufacturing process route string, a similarity design structure matrix DSM between different design parameters of the remanufacturing process route can be established sim Element DSM in its matrix sim (i, j) can be determined by the following equation (5) according to the semblance measure method
Wherein k and l are the number of processes in the remanufacturing process route string of the design parameters i and j of the heavy machine tool; n is the number of processes with similar design parameters; s ij Is the similar characteristic value proportional coefficient of the jth similar process, and can be taken as a value between 0 and 1; w is a j Is the weight coefficient of the jth similar process, can be determined by an analytic hierarchy process, and is more than 0 and less than w j ＜1，∑w j ＝1.
Step three, establishing a total interactive design structure matrix of the design parameters of the heavy machine tool
Obtaining a correlation design structure matrix of the design parameters of the heavy machine tool and a similarity design structure matrix of the remanufacturing process, and assuming that inter-domain hierarchical decomposition based on axiom design is adopted, and the product has n bottom layer design parameters in total, wherein the correlation design structure matrix and the similarity design structure matrix are both n multiplied by n dimensional matrices;
the module is composed of a plurality of parts with the least correlation and similarity with other parts except the module; for module division, the correlation and the similarity have the same preference attribute, and in order to obtain a more reasonable analysis result, a preference aggregation method is adopted to aggregate two indexes
In the formula, DSM int The interactive relation value among the design parameters is comprehensively reflected; w is a cor 、w sim Different weight values representing relevance and similarity, respectively; mu is a standard of the compensation level, and the larger the value of the mu is, the greater the preference of one attribute index is; d cor 、d sim Respectively are the correlation and similarity values to be clustered; each weight can be determined by the above-described analytic hierarchy process;
step four, clustering modules based on the theory of atoms
Module clustering is a complex comprehensive optimization process with numerous influencing factors; the invention solves the problem of remanufacturing-oriented module division of the heavy gantry machine tool based on the clustering algorithm of the atomic theory; simulating a module in the heavy gantry machine tool into an atom by using an atomic theory, defining design parameters with a plurality of interactivity among the design parameters as an atomic nucleus with positive charge, and defining the design parameters with interactivity with the atomic nucleus as electrons with negative charge; calculating the charge quantity carried by each design parameter, and establishing a distance matrix between the design parameters; obtaining a coulomb force matrix among the design parameters of the heavy machine tool as shown in formula (7), extracting the maximum value of each row in the coulomb force matrix, establishing a maximum coulomb force matrix which represents the maximum attraction between an electron and an atomic nucleus, and dividing the design parameters with the same maximum coulomb force together to form a module of a product;
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