Realize modular design and evaluation of machine tools

Realizing the modular design of special piston processing machines, according to the overall tasks and requirements put forward by users, the combination of module selection and module assembly design is the key to achieving rapid response to market demands.

The overall design of the piston-based special-purpose processing machine based on the module refers to the combination of module selection and module assembly design by analyzing the user's overall task definition and functional requirements. Due to the multiple solutions of the modular design, the proposed solution must be selected from numerous solutions. To do this, we first evaluate each candidate program and then make decisions based on the results of the evaluation. If the plan can not reach the predetermined goal, it must be redesigned, put forward a new design plan or modify a certain part of the original plan, and get a satisfactory design plan.

Module-based overall plan design

The overall design of the machine tool based on the module can be attributed to two opposite processes, namely decomposition and combination. Decomposition is to define the general function and performance index of the machine tool according to the process information of the object to be processed and the user's functional requirements, determine the overall program form and main performance parameters and characteristic parameter values ​​of the machine tool, and decompose it into a series of easily implemented sub-functions; the combination is According to the sub-function requirements, all the modules that meet the requirements are selected, and through the integration of the modules, a plurality of achievable overall machine tool plans are combined. Because the function structure of the machine tool is very complicated, it is difficult to directly complete the solution of its design task. Therefore, the decomposition of the design task is necessary, and the sub-functions that are decomposed can be completed by the corresponding modules. The basic steps of the overall module-based design of the machine tool are as follows:

(1) Decompose the overall task into some relatively simple sub-functions based on the total function and performance parameters of the machine tool;

(2) According to the requirements of the performance parameters of the sub-functions, find out the modules that meet the requirements;

(3) Since there are more than one module that satisfies a certain sub-function requirement, multiple combinations can be formed;

(4) Conduct module interface analysis to determine the achievable combination scheme;

(5) Establish the assembly model of the plan.

1. Task decomposition

The decomposition of the design task is mainly to allocate the total design parameters to the corresponding sub-functions while performing the function decomposition, and to realize the sub-function structure, or to specify the corresponding design parameters for the sub-functions. When the total function is decomposed, a layered mission system can be obtained, as shown in Figure 1.

Fig. 1 Decomposition of the function of the piston precision bore and drill center hole

2 module selection and combination

The selection of the module is based on the existing machine tool module and the division of the total function requirements of the machine tool. From the established module library, the module that is consistent with the function of the required module is searched. The main content includes the function selection, call and judgment of the existing module.

Taking the piston precision lathe series as an example, the main types of existing modules are: spindle modules, spindle box bearings (bridges), sliding tables, sliding tables, tailstocks, bed bodies and bases. According to the characteristics of the module joint surface, the combination of the modules shown in Fig. 2 can be obtained.

Figure 2 Combination of modules

The combination of modules has S1={1,2,3,4,5,6,7}, S2={1,3,4,5,6,7}, S3={1,3,4,5, 6},S4={1,2,3,4,5,6},S5={1,2,3,4,5,7},S6={1,3,4,5,7}, S7 ={1,3,4,6,7}.

For example, the BHC-50A piston ring groove precision lathe uses the S2={1,3,4,5,6,7} module combination, and the BHC-22 piston precision external lathe uses S5={1,2,3,4, 5,7}, the combination of precision machine and drilling center hole machine tool module adopts S7={1,3,4,6,7}.

3. The connection between modules

Modules are generally chained, tree-shaped or meshed together in the product. Because the role of the module in the product is different, ie, the sub-functions are different, the combination relationship with other modules is also different. According to the number of other modules that a module can connect, it can be divided into one-way connections, two-way connections, and multiple connections (Figure 3).

Figure 3 Module connection

One-way connection refers to a combination of modules that have only one interface and can only be connected to another module. Unidirectionally connected modules are at the end of the chain or tree.

Two-way connected modules have two interfaces that can be connected to two other modules. Bi-directionally connected modules can be combined to expand the system from both ends.

Multi-directional connection refers to a combination of modules that can be connected to more than two other modules at the same time. The so-called multi-directional connection does not mean that there must be other modules in each direction of the three-dimensional connection, nor does it mean that there is only one connection surface in each direction, or only a unique module can be connected thereto. If the machine tool slide module 3 is one-way connection, the bed module 6 is a multi-directional connection module.

4. Establish a module-based assembly model

In order to adapt to the needs of different products in the product family, the assembly model must also be a constraint-based parametric model. The product assembly model based on the module model expresses the constraint relations among the modules such as position, fit, connection and size. This paper establishes a parametric assembly model that adapts to the modular design. The basic idea is to establish an assembly data model that is related to the assembly while establishing the assembly entity model that satisfies various constraints. When the design parameters of a certain module change, other design parameters related to the design parameters are adjusted by the assembly data model so as to externally represent the corresponding adjustment of the assembly entity model and always maintain the original constraint relationship and assembly requirements. The process of assembly modeling is shown in Figure 4.

Figure 4 The process of establishing an assembly model

Figure 5 shows the parametric drive of the assembly model. When the design parameters of the machine tool change, the current design parameter value of the module is generated by the assembly data model, and the physical model of the drive module is changed through the module data model. As a result of various assembly constraints, the change of the module entity model will inevitably cause the assembly entity model to make corresponding changes. For example, as shown in FIG. 6 , when the front axle diameter D1 and the span L change according to the design parameters of the main shaft sub-module, the assembly constraint parameter Ld of the pulley module ensures the assembly position of the pulley relative to the main shaft. Based on this principle, various modules can be constrained by the definition of assembly to form the overall assembly model of the machine tool (Figure 7), complete the overall design of the machine tool, and produce the assembly information table (Figure 8).

Figure 5 Parameterized driving process of the assembly model

Figure 6 Assembly model parameterized drive

Fig. 7 Assembling scheme for fine end and drilling center hole machine tools

Fig. 8 Assembly information of fine hole and drilling center hole machine tool

Evaluation of Modular Design of Machine Tools

1. Evaluation indicators and methods

Due to the multiple solutions of the modular design, the proposed solution must be selected from numerous solutions. To do this, we first evaluate each candidate program and then make decisions based on the results of the evaluation. If the plan can not reach the predetermined goal, it must be redesigned, put forward a new design plan or modify a certain part of the original plan, and get a satisfactory design plan. Figure 9 shows the process of evaluating the modular design of a machine tool. It begins with the evaluation of the modular design solution and discusses its evaluation indicators and decision-making methods.

Figure 9 Evaluation process


As a first step in the evaluation, the evaluation criteria should first be determined. The same evaluation method can be used for different products, but the evaluation index is different. Therefore, the key to evaluating the modular design of a machine tool is to establish its evaluation index system.

The evaluation criteria come from the requirements for the designed product. These requirements include different aspects of the entire product life cycle, such as technology, economy, security, appearance and environment. These aspects have different importance and cannot be treated in the same way. Therefore, there are more than one evaluation criteria and their importance is not the same. They form a system of evaluation indicators. The following principles should be followed when establishing an evaluation index system:

(1) The indicator system should include as much as possible all requirements that are of great importance to the decision. Try to avoid missing important aspects in the evaluation.

(2) Each evaluation index should be as unrelated as possible. In this way, improvements in one area will not affect other areas of evaluation.

(3) According to the quantitative analysis principles followed in the design evaluation, quantitative indicators or at least more specific qualitative indicators should be selected in the establishment of the index system.

After a modular design method is used to form a design program for a special piston machining machine, the next step is to evaluate the solution. The evaluation index is:

(1) Functionality. The function is the essence of the product's nature. Functional performance in the product's intrinsic quality, with clear features, can meet the piston processing technology requirements. Another meaning of functionality is to adapt to people's needs, that is, the rationality of the human-machine system.

(2) Rationality. It refers to the manufacturability of the designed machine tool and the degree of adaptation of the material conditions and working conditions owned by the company.

(3) Economicality. Economical mainly refers to the economic value of the product. Economic value is the relative relationship between product function and cost, namely: economic value k = function/cost (k: coefficient). Without sacrificing the interests of consumers, reducing costs and improving functions can maximize the economic value of products.

(4) originality. In the aesthetic process, people's requirements for form are first of all new, and on the basis of beauty, the shape structure should be original.

(5) Future sex. The design stress map of the product condenses the past inheritance and the understanding of the future in the design concept. The future performance of the design must have advanced concepts and concepts in design, and have a certain degree of permanence in society.

The evaluation of special piston machine tools belongs to a comprehensive evaluation under multiple factors. Fuzzy mathematics establishes the mode of comprehensive evaluation, and evolves a complex evaluation problem into a relatively simple fuzzy transformation.

Let X and Y be finite universes: X = {x1, x2, ..., xn}, Y = {y1, y2, ..., yn}.

R is the fuzzy relation from X to Y, that is, R=(rij)n×m. Given the fuzzy subset A on X, then the synthesis of A and R A?R is a fuzzy set on Y, denoted as B. This transformation, which transforms the fuzzy set on X into a fuzzy set on Y, is called a fuzzy transform.

Let X be a set of factors and Y be a set of decisions. For any xi ∈ X, yj ∈ Y. Since rij represents the feature index (possibility) of xi on yi, for each xi a vector (ri1, ri2,..., rim) is the characteristic index vector of xi about Y, (i=1, 2,... ,n). Then these several vectors are used as the matrix of the row n × m matrix R = (rij) n × m, to get the X to Y fuzzy relationship matrix, called the single factor evaluation matrix.

The fuzzy set A = (a1, a2, ..., an) denotes the weight distribution on X. That is, ai is the quantity index of the factor xi, and A?R=B, then B = (b1, b2, ..., bm) ) Represents the probability coefficient of various decisions on the decision set. Then use the principle of maximum degree of membership to select the largest bj, corresponding to yj as the evaluation result.

(1) First-level evaluation model to determine the set of factors to be evaluated, X = {x1, x2, ..., xn}; to give a decision set, Y = {y1, y2, ..., ym}; to determine single-factor assessment The matrix R=(rij)n×m; a decision of the object set is obtained by the fuzzy transformation AR from X to Y.

(2) Multi-level evaluation model. In the first-order evaluation model, if the number of evaluation factor sets n is too much, because the weight distribution is satisfied, each ai is generally very small, so when the synthesis operation takes hours, the elements of R are filtered too much , causing the evaluation to fail. On the other hand, if n is too large, it is difficult to make a reasonable distribution of weights, that is, it is difficult to reflect the status of each factor in the overall situation. Therefore, it is better to use a multi-level model if the factor set n is too large.

1 The factor set X is divided into s subsets according to a certain attribute, denoted as x1, x2, ..., xs, and satisfied. Each subset xi is denoted by: xi = {xi1, xi2, ..., xip}, (i = 1, 2, ..., s), and.

2 Each xi is evaluated comprehensively according to the first-level model. If the evaluation set is: Y={y1,y2,...,ym}, the single factor evaluation matrix of xi is set to Ri, and the weight factors of xi are assigned to Ai=(ai1,ai2,...,aip). The rating result Ai?Ri=(bi1,bi2,...,bim)=Bi(i=1,2,...,s).

3 Treat each xi as an element and use Bi as its single-factor evaluation vector to obtain a single factor evaluation matrix:

Assign weights to the importance of each xi in X: Ai = (a1, a2, ..., as), then the secondary evaluation result: B = A?R.

This is the secondary evaluation model. If the factor number n of X is too large, s is still too large when dividing X by X=X1U, X2U,..., XsU, and the second-level evaluation still has the phenomenon of excessive factors, so that it can be modeled on each of the preceding Xi split, grading evaluation.

2. Comprehensive evaluation of the piston precision mouth and drilling center hole machine tools

According to the actual situation of the factory, the set of factors is defined as: X = {x1, x2, x3, x4, x5, x6}, where x1, x2, x3, x4, x5, x6 represent functionality, rationality, economy, respectively , originality, future, aesthetics. The evaluation factor set is: Y={y1,y2,y3,y4,y5,y6}, where y1, y2, y3, y4, y5, and y6 represent good, good, good, general, and poor, respectively. Very poor.

First make a single factor assessment. The relevant experts, engineering and technical personnel, manufacturing and maintenance personnel, first-line operators, and other personnel of the company are invited to participate in the evaluation.

(1) Evaluation of functionality.

In the evaluation, 30% of the participants considered it “very good”, 40% considered it “good”, 10% considered it “better”, 10% considered it “general”, and 10% considered it “comparable”. Poor, no one thinks "bad". The result of evaluating x1 is: (0.3, 0.4, 0.1, 0.1, 0.1, 0). Similarly, x2, x3, x4, x5, and x6 are evaluated one by one, and the degree of membership is shown in the table.

Due to a large number of factors, using multi-level model solving, the evaluation factors are divided into two subsystems, namely: X={X1, X2}. Where X1={x1,x2,x3},X2={x4,x5,x6}. The univariate evaluation matrices to which they correspond are:

According to different factors in the assessment of the tendency, such as for the piston processing machine, mainly to evaluate its functionality, that is, whether it can meet the production needs, then the distribution of the weight of the functional value is too large.
The current weights are taken as follows: A1=[0.4 0.32 0.28] and A2=[0.5 0.2 0.3].

Thus, A1?R1=[0.332 0.34 0.16 0.116 0.1 0.016]; A2?R2=[0.24 0.26 0.31 0.15 0.065 0.035].

Because the factory's evaluation of special machine tools focuses on practicality and economy, and the weights assigned to B1 and B2 are A=(0,75,0,25), the overall evaluation result is: B=A?R=[0.28 0.32 0.19 0.11 0.09 0.01]. According to the principle of maximum degree of membership, the corresponding evaluation factor of 0.32 is “good”. Therefore, the comprehensive evaluation of the precision piston and drilling center hole machine tool is “good”.

Conclusion

This article starts with the design and evaluation of the modular scheme and discusses its design method, evaluation index and decision method.

Through the design and evaluation of the modular overall plan of the machine tool, the steps for the design of the overall modularization program of the machine tool are clarified; the selection and combination of the modules determine the principle of the combination program of the machine tool; finally, we apply a fuzzy comprehensive evaluation method to a piston Special machine program for comprehensive evaluation.

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